Best Paper Award
}, publisher = {Springer}, keywords = {[Project Phase 2] Topology-based Visual Analysis of Information Spaces}, url = {http://visualanalytics.de/sites/default/files/upload/publications/2015_Computing_and_Visualizing_Time-Varying_Merge_Trees_for_High-Dimensional_Data.pdf}, author = {Patrick Oesterling and Christian Heine and Gunther H. Weber and Dmitriy Morozov and Gerik Scheuermann} } @proceedings {482, title = {Convolutional Neural Network for Paraphrase Identification}, journal = {2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies}, year = {2015}, address = {Denver, USA}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Convolutional.Neural.Network.for_.Paraphrase.Identification.2015.pdf}, author = {H. Sch{\"u}tze and Wenpeng Yin} } @conference {yaghoobzadeh-schutze:2015:EMNLP, title = {Corpus-level Fine-grained Entity Typing Using Contextual Information}, booktitle = {Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing}, year = {2015}, pages = {715{\textendash}725}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Yadollah Yaghoobzadeh and Hinrich Sch{\"u}tze} } @inbook {kottke_et_al_15a, title = {Data-Driven Spine Detection for Multi-Sequence {MRI}}, booktitle = {Bildverarbeitung f{\"u}r die Medizin}, year = {2015}, pages = {5-10}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/kottke_et_al_15a.pdf}, author = {Kottke, D. and Gulamhussene, G. and K. D. T{\"o}nnies} } @inbook {rak_et_al_15c, title = {Density Difference Detection with Application to Exploratory Visualization}, booktitle = {Lecture Notes in Computer Science}, year = {2015}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets, [Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/rak_et_al_15c.pdf}, author = {M. Rak and T. K{\"o}nig and J. Steffen and K. D. T{\"o}nnies and D. J. Lehmann} } @inbook {568, title = {Detecting Dysregulated Processes and Pathways}, booktitle = {Nucleic Acids as Molecular Diagnostics}, year = {2015}, pages = {309-324}, publisher = {Wiley-VCH Verlag}, organization = {Wiley-VCH Verlag}, chapter = {14}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, issn = {978-3-527-33556-5}, author = {D. St{\"o}ckel and H.-P. Lenhof} } @proceedings {483, title = {Discriminative Phrase Embedding for Paraphrase Identification}, journal = {2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies}, year = {2015}, address = {Denver, USA}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Discriminative.Phrase.Embedding.for_.Paraphrase.Identification.2015.pdf}, author = {H. Sch{\"u}tze and Wenpeng Yin} } @proceedings {468, title = {Enhancing Time Series Segmentation and Labeling Through the Knowledge Generation Model}, journal = {Eurographics Conference on Visualization (EuroVis 2015)}, year = {2015}, address = {Cagliari, Italy}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Gschwandtner--EnhancingTimeSeriesSegmentationandLabelingthroughtheKnowledgeGenerationModel--2015.pdf}, author = {T. Gschwandtner and Heidrun Schumann and J{\"u}rgen Bernard and Thorsten May and Markus B{\"o}gl and Silvia Miksch and J{\"o}rn Kohlhammer and Martin R{\"o}hlig and Bilal Alsallakh} } @mastersthesis {Gast{\textendash}EntwicklungeinesInterfaceszurvisuellenInspektionvonWorkflows{\textendash}2015, title = {Entwicklung eines Interfaces zur visuellen Inspektion von Workflows}, volume = {M.Sc.}, year = {2015}, school = {University of Rostock, Germany}, address = {Rostock, Germany}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {Philipp Gast} } @article {641, title = {Evaluation of Multi-view 3D Reconstruction Software}, journal = {Computer Analysis of Images and Patterns (CAIP)}, year = {2015}, pages = {450-461}, publisher = {Springer International Publishing}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, isbn = {978-3-319-23116-7}, doi = {http://dx.doi.org/10.1007/978-3-319-23117-4_39}, author = {J. Sch{\"o}ning and G. Heidemann} } @article {471, title = {An explicit numerical scheme to efficiently simulate molecular diffusion in environments with dynamically changing barriers}, journal = {Mathematical and Computer Modelling of Dynamical Systems}, volume = {21}, year = {2015}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, doi = {10.1080/13873954.2015.1033823}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Kossow--Anexplicitnumericalschemetoefficientlysimulatemoleculardiffusioninenvironmentswithdynamicallychangingbarriers--2015.pdf}, author = {Christina Kossow and S. Rybacki and Thomas Millat and Katja Rateitschak and Robert Jaster and A. Uhrmacher and Olaf Wolkenhauer} } @article {590, title = {Exploratory Search Through Visual Analysis of Topic Models}, journal = {Digital Humanities Quarterly (special issue)}, year = {2015}, note = {(accepted for publication, still under review)
}, keywords = {[Project Phase 2] Topology-based Visual Analysis of Information Spaces}, url = {http://visualanalytics.de/sites/default/files/upload/publications/2015-Eploratory_Search_Through_Visual_Analysis_of_Topic_Models.pdf}, author = {Patrick J{\"a}hnichen and Patrick Oesterling and Gerhard Heyer and Tom Liebmann and Gerik Scheuermann and Christoph Kuras} } @conference {SFO+15, title = {Feature-Based Visual Exploration of Text Classification}, booktitle = {Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015}, year = {2015}, keywords = {[Project Phase 2] Feature-based Visualization and Analysis of Natural Language Documents}, url = {https://bib.dbvis.de/publications/details/634}, author = {Florian Stoffel and Lucie Flekova and Oelke, Daniela and Iryna Gurevych and Keim, Daniel A.} } @article {toennies_et_al_15a, title = {Image analysis in epidemiological applications}, journal = {it - Information Technology}, volume = {57}, year = {2015}, pages = {22-29}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/toennies_et_al_15a.pdf}, author = {K. D. T{\"o}nnies and Gloger, O. and M. Rak and Winkler, C. and P. Klemm and B. Preim and H. V{\"o}lzke} } @article {467, title = {Interactive presentation of geo-spatial climate data in multi-display environments}, journal = {ISPRS International Journal of Geo-Information}, volume = {4}, year = {2015}, pages = {493-514}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, issn = {2220-9964}, doi = {10.3390/ijgi4020493}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Eichner--Interactivepresentationofgeo-spatialclimatedatainmulti-displayenvironments--2015.pdf}, author = {C. Eichner and T. Nocke and H.-J. Schulz and H. Schumann} } @proceedings {DH2015, title = {Interactive Visual Analysis Of German Poetics}, journal = {Proceedings of the Digital Humanities 2014 (Short Paper)}, year = {2015}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {John, Markus and Koch, Steffen and Heimerl, Florian and Andreas M{\"u}ller and Ertl, Thomas and Jonas Kuhn} } @inbook {rak_et_al_15b, title = {Measurement of the Aortic Diameter in Plain Axial Cardiac Cine {MRI}}, booktitle = {Bildverarbeitung f{\"u}r die Medizin}, year = {2015}, pages = {293-298}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/rak_et_al_15b.pdf}, author = {M. Rak and Schnurr, A. K. and Alpers, J. and K. D. T{\"o}nnies} } @conference {jaimez15_mocoop, title = {Motion Cooperation: Smooth Piece-Wise Rigid Scene Flow from RGB-D Images}, booktitle = {Proc. of the Int. Conference on 3D Vision (3DV)}, year = {2015}, note = {{[video]}
}, keywords = {[Project Phase 1] Variational Methods for Model-based Interactive Analysis of Flows}, author = {M. Jaimez and M. Souiai and J. Stueckler and J. Gonzalez-Jimenez and D. Cremers} } @conference {yin-schutze:2015:CoNLL, title = {Multichannel Variable-Size Convolution for Sentence Classification}, booktitle = {Proceedings of the Nineteenth Conference on Computational Natural Language Learning}, year = {2015}, pages = {204{\textendash}214}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Wenpeng Yin and Hinrich Sch{\"u}tze} } @conference {yin-schutze:2015:ACL-IJCNLP, title = {MultiGranCNN: An Architecture for General Matching of Text Chunks on Multiple Levels of Granularity}, booktitle = {Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)}, year = {2015}, pages = {63{\textendash}73}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Wenpeng Yin and Hinrich Sch{\"u}tze} } @mastersthesis {522, title = {Navigationskonzepte fuer die visuelle Exploration spatialisierter Dokumente}, volume = {B. Sc.}, year = {2015}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Adrian Lanksweirt} } @conference {jaimez15icra, title = {A Primal-Dual Framework for Real-Time Dense RGB-D Scene Flow}, booktitle = {Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA)}, year = {2015}, note = {{[video]}
}, keywords = {[Project Phase 1] Variational Methods for Model-based Interactive Analysis of Flows}, author = {M. Jaimez and M. Souiai and J. Gonzalez-Jimenez and D. Cremers} } @proceedings {642, title = {Semi-automatic Ground Truth Annotation in Videos: An InteractiveTool for Polygon-based Object Annotation and Segmentation}, journal = {International Conference on Knowledge Capture (K-CAP)}, volume = {17}, year = {2015}, pages = {17:1-17:4}, publisher = {ACM}, address = {New York}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, isbn = {978-1-4503-3849-3}, author = {J. Sch{\"o}ning and P. Faion and G. Heidemann} } @proceedings {rak_et_al_15a, title = {Spotting Differences Among Observations}, journal = {Proceedings of the International Conference on Pattern Recognition Applications and Methods}, year = {2015}, pages = {5-13}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/rak_et_al_15a.pdf}, author = {M. Rak and T. K{\"o}nig and K. D. T{\"o}nnies} } @article {preim_et_al_15a, title = {Visual Analytics of Image-Centric Cohort Studies in Epidemiology}, journal = {arXiv preprint arXiv:1501.04009}, year = {2015}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/preim_et_al_15a.pdf}, author = {B. Preim and P. Klemm and H. Hauser and K. Hegenscheid and S. Oeltze and K. D. T{\"o}nnies and H. V{\"o}lzke} } @mastersthesis {521, title = {Webbasierte visuelle Analyse der Verbreitungswege historischer Abschriften}, volume = {B. Sc.}, year = {2015}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Marco Loureiro} } @conference {628, title = {Wifbs: A Web-based Image Feature Benchmark System}, booktitle = {MultiMedia Modeling - 21th Anniversary International Conference, {MMM} 2015, Sydney, Australia, January 5-7, 2015, Proceedings}, year = {2015}, keywords = {[Project Phase 1] Zoomable Cell}, author = {Spehr, Marcel and Gumhold, Stefan and Grottel, Sebastian} } @article {490, title = {Wind parameters extraction from aircraft trajectories}, journal = {Computers, Environment and Urban Systems}, volume = {47(1)}, year = {2014}, month = {September 2014}, pages = {28-43}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1016/j.compenvurbsys.2014.01.005}, author = {C. Hurter and R. Alligier and D. Gianazza and S. Puechmorel and G. Andrienko and N. Andrienko} } @conference {Strobel-et-al-gcpr2014, title = {Flow and Color Inpainting for Video Completion}, booktitle = {German Conference on Pattern Recognition (GCPR)}, year = {2014}, month = {September}, address = {M{\"u}nster, Germany}, keywords = {[Project Phase 1] Variational Methods for Model-based Interactive Analysis of Flows}, doi = {10.1007/978-3-319-11752-2_23}, author = {M. Strobel and J. Diebold and D. Cremers} } @proceedings {528, title = {Hierarchical Brushing of High-Dimensional Data Sets Using Quality Metrics}, journal = {Vision, Modeling and Visualization (VMV) 2014}, year = {2014}, month = {October 2014}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, url = {http://europa.cg.cs.tu-bs.de/media/publications/Albuquerque2014HBH.pdf}, author = {G. Albuquerque and M. Eisemann and T. L{\"o}we and M. Magnor} } @article {Bruegmann2014, title = {Towards content-oriented patent document processing: Intelligent patent analysis and summarization}, journal = {World Patent Information}, year = {2014}, month = {December 2014}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, issn = {0172-2190}, doi = {http://dx.doi.org/10.1016/j.wpi.2014.10.003}, author = {S{\"o}ren Br{\"u}gmann and Nadjet Bouayad-Agha and Alicia Burga and Serguei Carrascosa and Alberto Ciaramella and Marco Ciaramella and Joan Codina-Filba and Enric Escorsa and Alex Judea and Simon Mille and Andreas M{\"u}ller and Horacio Saggion and Patrick Ziering and Hinrich Sch{\"u}tze and Leo Wanner} } @proceedings {529, title = {A Nested Hierarchy of Localized Scatterplots}, journal = {SIBGRAPI (Conference on Graphics, Patterns and Images) 2014}, year = {2014}, month = {August 2014}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, url = {http://europa.cg.cs.tu-bs.de/media/publications/Eisemann14NHL.pdf}, author = {M. Eisemann and G. Albuquerque and M. Magnor} } @proceedings {494, title = {Workshop: GeoVisual Analytics: Interactivity, Dynamics, and Scale}, journal = {GIScience}, year = {2014}, month = {23.09.2014}, address = {Vienna, AT}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://geoanalytics.net/GeoVA2014/}, author = {G. Andrienko and J. Dykes and M.-J. Kraak and Anthony Robinson} } @mastersthesis {509, title = { Visueller Vergleich von Segmentierungsalgorithmen von medizinischen 3D-Bildern}, volume = {B. Sc.}, year = {2014}, month = {2014}, address = {Darmstadt}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {Alexander Geurts} } @conference {492, title = {Analysis of Mobility Behaviors in Geographic and Semantic Spaces}, booktitle = {VAST Challenge @ IEEE VAST 2014}, year = {2014}, month = {2014}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://geoanalytics.net/and/papers/vast14b.pdf}, author = {N. Andrienko and G. Andrienko and G. Fuchs} } @proceedings {560, title = {Benchmark Data for Evaluating Visualization and Analysis Techniques for Eye Tracking for Video Stimuli}, journal = {BELIV{\textquoteright}14: Beyond time and errors: novel evaluation methods for information visualization}, year = {2014}, month = {2014}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {K. Kurzhals and Cyrill Fabian Bopp and B{\"a}ssler, Jochen and Ebinger, Felix and Weiskopf, Daniel} } @article {533, title = {Blood Flow Clustering and Applications in Virtual Stenting of Intracranial Aneurysms}, journal = {IEEE Transactions on Visualization and Computer Graphics}, year = {2014}, month = {2014}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, url = {http://vc.cs.ovgu.de/files/publications/2014/Oeltze_2014_TVCG.pdf}, author = {S. Oeltze and D. J. Lehmann and A. Kuhn and G. Janiga and H. Theisel and B. Preim} } @proceedings {500, title = {Characterizing the Swarm Movement on Map for Spatial Visualization}, journal = {IEEE Transactions on Visualization and Computer Graphics}, year = {2014}, month = {2014}, address = {Paris, France}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, author = {C. Kumar and U. Gruenefeld and W. Heuten and S. Boll} } @mastersthesis {503, title = {A Computational Intelligence Framework for Multidimensional Regional Search}, volume = {MsC}, year = {2014}, month = {2014}, school = {University of Oldenburg}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, author = {U. Gruenefeld} } @conference {493, title = {Detecting and Tracking Dynamic Clusters of Spatial Events}, booktitle = {IEEE VAST 2014}, year = {2014}, month = {2014}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://geoanalytics.net/and/papers/vast14a.pdf}, author = {N. Andrienko and G. Andrienko and G. Fuchs and H. Stange} } @proceedings {561, title = {Evaluating Visual Analytics with Eye Tracking}, journal = {BELIV{\textquoteright}14: Beyond time and errors: novel evaluation methods for information visualization}, year = {2014}, month = {2014}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {K. Kurzhals and B. Fisher and Burch, Michael and D. Weiskopf} } @proceedings {501, title = {Event Based Characterization and Comparison of Geosocial Environment}, journal = {Temporal, Social and Spatially-aware Information Access}, year = {2014}, month = {2014}, address = {Gold Coast, Australia}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, author = {C. Kumar and W. Heuten and S. Boll} } @article {491, title = {A General Framework for Trajectory DataWarehousing and Visual OLAP}, journal = {Geoinformatica}, volume = {18(2)}, year = {2014}, month = {2014}, pages = {273-312}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1007/s10707-013-0181-3}, author = {L. Leonardi and S. Orlando and A. Raffaet{\textquoteright}a and A. Roncato and C. Silvestri and G. Andrienko and N. Andrienko} } @mastersthesis {510, title = {Patientenspezifische Planung f{\"u}r die Multi-Port Otobasischirurgie}, volume = {PhD}, year = {2014}, month = {2014}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {Meike Becker} } @proceedings {499, title = {A Regional Exploration and Recommendation System based on Georeferenced Images}, journal = {International Conference on Mobile Web Information Systems}, year = {2014}, month = {2014}, edition = {11}, address = {Barcelona, Spain}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, author = {C. Kumar and S. Barton and W. Heuten and S. Boll} } @mastersthesis {495, title = {Relating mobility patterns to socio-demographic profiles}, volume = {PhD}, year = {2014}, month = {2014}, school = {Univ. Bonn}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, author = {Thomas Liebig} } @mastersthesis {496, title = {A semi-supervised method for topic extraction from micro postings}, volume = {MsC}, year = {2014}, month = {2014}, school = {Univ. Bonn}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, author = {Ahmed Samiei} } @article {532, title = {Sparse Representation and Visualization for Direct Numerical Simulation of Premixed Combustion}, journal = {Computer Graphics Forum}, volume = {33}, year = {2014}, month = {2014}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, url = {http://vc.cs.ovgu.de/files/publications/2014/Oster_2014_EuroVis.pdf}, author = {T. Oster and D. J. Lehmann and G. Fru and H. Theisel and D. Th{\'e}venin} } @article {553, title = {State of-the-Art of Visualization for Eye Tracking Data}, journal = {EuroVis STAR}, year = {2014}, month = {2014}, pages = {63-82}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {Blascheck, Tanja and Kurzhals, Kuno and Raschke, Michael and Burch, Michael and Weiskopf, Daniel and Ertl, Thomas} } @proceedings {498, title = {Swarming in the Urban Web Space to Discover the Optimal Region}, journal = {IEEE/WIC/ACM International Conference on Web Intelligence}, year = {2014}, month = {2014}, edition = {WI-1}, address = {Warsaw, Poland}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, author = {C. Kumar and U. Gruenefeld and W. Heuten and S. Boll} } @mastersthesis {534, title = {Vector Field Design}, volume = {M.Sc.}, year = {2014}, month = {2014}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, author = {Thomas Weiss} } @proceedings {512, title = {Visual Analytics Science and Technology (VAST)}, journal = {2014 IEEE Conference}, year = {2014}, month = {2014}, pages = {93 {\textendash} 102}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {Olav Lenz and Frank Keul and S. Bremm and K. Hamacher and T. von Landesberger} } @article {513, title = {Visual Exploration of Parameter Influence on Phylogenetic Trees}, journal = {IEEE Computer Graphics and Applications}, volume = {34}, year = {2014}, month = {2014}, pages = {48-56}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {M. Hess and S. Bremm and S. Weissgraeber and K. Hamacher and M. Goesele and J. Wiemeyer and T. von Landesberger} } @mastersthesis {504, title = {Visual Representation of Similar Touristic Regions Using Georeferenced Images}, volume = {BsC}, year = {2014}, month = {2014}, school = {University of Oldenburg}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, author = {S. Barton} } @proceedings {557, title = {Visual Task Solution Strategies in Public Transport Maps}, journal = {Proceedinsg of the 2nd International Workshop on Eye Tracking for Spatial Research}, year = {2014}, month = {2014}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {Burch, Michael and Kurzhals, Kuno and Weiskopf, Daniel} } @proceedings {voegele2014a, title = {Efficient Unsupervised Temporal Segmentation of Human Motion}, journal = {2014 ACM SIGGRAPH/Eurographics Symposium on Computer Animation}, year = {2014}, month = {07/2014}, address = {Copenhagen, Denmark}, abstract = {This work introduces an efficient method for fully automatic temporal segmentation of human motion sequences and similar time series. The method relies on a neighborhood graph to partition a given data sequence into distinct activities and motion primitives according to self-similar structures given in that input sequence. In particular, the fast detection of repetitions within the discovered activity segments is a crucial problem of any motion processing pipeline directed at motion analysis and synthesis. The same similarity information in the neighborhood graph is further exploited to cluster these primitives into larger entities of semantic significance. The elements subject to this classification are then used as prior for estimating the same target values for entirely unknown streams of data. The technique makes no assumptions about the motion sequences at hand and no user interaction is required for the segmentation or clustering. Tests of our techniques are conducted on the CMU and HDM05 motion capture databases demonstrating the capability of our system handling motion segmentation, clustering, motion synthesis and transfer-of-label problems in practice - the latter being an optional step which relies on the preexistence of a small set of labeled data.}, keywords = {[Project Phase 2] Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes}, url = {http://cg.cs.uni-bonn.de/de/publikationen/paper-details/voegele2014a/}, author = {V{\"o}gele, Anna and Kr{\"u}ger, Bj{\"o}rn and Reinhard Klein} } @proceedings {hermann2014-shape, title = {Anatomic Segmentation of Statistical Shape Models}, journal = {Symposium on Statistical Shape Models \& Applications (SHAPE2014)}, year = {2014}, note = {Best poster award}, month = {06/2014}, address = {Del{\'e}mont, Switzerland}, abstract = {Shape segmentation is one of the fundamental tools in shape processing and provides the starting point for building part based shape models. A multitude of methods for segmenting static and dynamic shapes has been developed over the last decades based on various intrinsic and extrinsic geometric features. Interestingly, so far no method considering information from an available statistical shape model seems to exist. In this work a segmentation based on statistical covariance analysis is derived. Its results show meaningful parts in the sense that all points in a part share similar (co-)variability, i.e. behave similar according to the model, while different parts show distinct variation patterns. We show initial results in two application domains where this is a desired property: In morphometrics independent modules are sought relating to an underlying independent evolutionary development; in motion analysis correlated movement is relevant for motion understanding and compression.}, keywords = {[Project Phase 2] Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes}, url = {http://cg.cs.uni-bonn.de/de/publikationen/paper-details/hermann2014-shape/}, author = {Hermann, Max and Schunke, Anja C. and Reinhard Klein} } @proceedings {570, title = {Boundary Labeling Methods for Dynamic Focus Regions}, journal = {Pacific Visualization Symposium (PacificVis), 2014 IEEE}, year = {2014}, month = {03/2014}, pages = {243 - 247}, publisher = {IEEE}, address = {Yokohama}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, doi = {10.1109/PacificVis.2014.20}, url = {http://visualanalytics.de/sites/default/files/upload/publications/FocusRegion.pdf}, author = {Niklas Heinsohn and Andreas Gerasch and Michael Kaufmann} } @proceedings {579, title = {Rebuilding KEGG Maps - An integrative approach for visual analytics of metabolic networks}, journal = {PacificVis 2014}, year = {2014}, month = {03/2014}, pages = {97-104}, address = {Yokohama}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Kegg.pdf}, author = {Andreas Gerasch and Michael Kaufmann and Oliver Kohlbacher} } @book {554, title = {Background Modeling and Foreground Detection for Video Surveillance}, year = {2014}, publisher = {CRC Press}, organization = {CRC Press}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {Antoine Vacavant and Benjamin H{\"o}ferlin and Bouwmans, Thierry and Fatih Porikli} } @proceedings {380, title = {BiNA: a visual analytics tool for biological network data}, year = {2014}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, author = {A. Gerasch and D. Faber and J. K{\"u}ntzer and P. Niermann and O. Kohlbacher and H.-P. Lenhof and M. Kaufmann} } @proceedings {422, title = {Clustering Socio-demographic and Medical Attribute Data in Cohort Studies}, journal = {Bildverarbeitung f{\"u}r die Medizin (BVM)}, year = {2014}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Clustering Socio-demographic and Medical Attribute Data in Cohort Studies.pdf}, author = {P. Klemm and L. Frauenstein and D. Perlich and K. Hegenscheid and H. V{\"o}lzke and B. Preim} } @article {toennies_et_al_14a, title = {Deformable part models for object detection in medical images}, journal = {BioMedical Engineering OnLine}, volume = {13}, year = {2014}, pages = {S1}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/toennies_et_al_14a.pdf}, author = {K. D. T{\"o}nnies and M. Rak and K. Engel} } @proceedings {477, title = {Developing simulation models - from conceptual to executable model and back - an artifact-based workflow approach}, journal = {Simutools}, year = {2014}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Rybacki--Developingsimulationmodels-fromconceptualtoexecutablemodelandback-anartifact-basedworkflowapproach--2014.pdf}, author = {S. Rybacki and F. Haack and Karsten Wolf and A. Uhrmacher} } @mastersthesis {574, title = {Effiziente Berechnung station{\"a}rer Flussfelder zur Bilddeformation}, volume = {Diploma}, year = {2014}, keywords = {[Project Phase 2] Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes}, author = {Armin Bruske} } @conference {Stoffel2014Enhan-29999, title = {Enhanced News-reading : Interactive and Visual Integration of Social Media Information}, booktitle = {Proceedings of LREC 2014 : Ninth International Conference on Language Resources and Evaluation : May 26-31, 2014, Reykjavik, Iceland ; VisLR workshop : visualization as added value in the development, use and evaluation of Language Resources}, year = {2014}, pages = {21{\textendash}28}, publisher = {European Language Resources Association (ELRA)}, organization = {European Language Resources Association (ELRA)}, keywords = {[Project Phase 2] Feature-based Visualization and Analysis of Natural Language Documents}, author = {Florian Stoffel and Dominik J{\"a}ckle and Keim, Daniel A.} } @mastersthesis {Neuber{\textendash}EntwicklungeinesHistory-MechanismusfuerMulti-PraesenterSzenarien{\textendash}2014, title = {Entwicklung eines History-Mechanismus f{\"u}r Multi-Pr{\"a}senter Szenarien}, volume = {B. Sc.}, year = {2014}, school = {University of Rostock, Germany}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {Arne Neuber} } @inbook {583, title = {Fitting Planar Graphs on Planar Maps}, booktitle = {SOFSEM 2014: Theory and Practice of Computer Science}, series = {Lecture Notes in Computer Science}, volume = {8327}, year = {2014}, pages = {52-64}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, isbn = {978-3-319-04297-8}, doi = {10.1007/978-3-319-04298-5_6}, url = {http://dx.doi.org/10.1007/978-3-319-04298-5_6}, author = {Alam, Md.Jawaherul and Michael Kaufmann and Kobourov, StephenG. and Mchedlidze, Tamara} } @mastersthesis {435, title = {Flexible Visualisierung von Wetterdaten im r{\"a}umlichen Kontext unter Ber{\"u}cksichtigung von Unsicherheiten}, year = {2014}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. R{\"o}hlig} } @article {479, title = {Foreword to the special section on visual analytics}, journal = {Computers \& Graphics}, volume = {38}, year = {2014}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Schulz--ForewordtotheSpecialSectiononVisualAnalytics--2014.pdf}, author = {H.-J. Schulz and H. Schumann and Margit Pohl} } @article {470, title = {A Generic Adaptive Simulation Algorithm for Component-based Simulation Systems}, journal = {ACM Transactions on Modeling and Computer Simulation}, volume = {1}, year = {2014}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, doi = {10.1145/0000000.0000000}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Helms--AGenericAdaptiveSimulationAlgorithmforComponent-basedSimulationSystems--.pdf}, author = {T. Helms and R. Ewald and S. Rybacki and A. Uhrmacher} } @proceedings {593, title = {A Geological Metaphor for Geospatial-temporal Data Analysis.}, journal = {IVAPP {\textquoteright}14: Proceedings of the 5th International Conference on Information Visualization Theory and Application}, year = {2014}, pages = {161{\textendash}169}, publisher = {SciTePress}, keywords = {[Project Phase 2] Topology-based Visual Analysis of Information Spaces}, doi = {10.5220/0004742901610169}, url = {http://visualanalytics.de/sites/default/files/upload/publications/2014_A_Landscape_Metaphor_for_Geo-Temporal_Data_Analysis.pdf}, author = {Tom Liebmann and Patrick Oesterling and Stefan J{\"a}nicke and Gerik Scheuermann} } @proceedings {558, title = {How Do People Read Metro Maps? An Eye Tracking Study}, journal = {Proceedings of 1st International Workshop on Schematic Mapping}, year = {2014}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {Burch, Michael and Raschke, Michael and Blascheck, Tanja and Kurzhals, Kuno and Weiskopf, Daniel} } @proceedings {458, title = {Improving Citation Polarity Classification with Product Reviews}, journal = {52nd Annual Meeting of the Association for Computational Linguistics (ACL)}, year = {2014}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, url = {http://visualanalytics.de/sites/default/files/upload/publications/jochim,schuetze,acl,2014.pdf}, author = {H. Sch{\"u}tze and C. Jochim} } @book {449, title = {Interaction taxonomy for tracking of user actions in visual analytics applications}, series = {Handbook of Human Centric Visualization}, year = {2014}, pages = {653-670}, publisher = {Springer New York}, organization = {Springer New York}, address = {New York}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {T. von Landesberger and S. Fiebig and S. Bremm and A. Kuijper and D. Fellner} } @article {460, title = {Interactive Visual Analysis of Image-Centric Cohort Study Data}, journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)}, year = {2014}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Interactive Visual Analysis of Image-Centric Cohort StudyData.pdf}, author = {P. Klemm and S. Oeltze and K. Lawonn and K. Hegenscheid and H. V{\"o}lzke and B. Preim} } @mastersthesis {523, title = {Interaktive Optimierung automatischer Sprachverabeitung}, volume = {B. Sc.}, year = {2014}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Constanze Sudra} } @mastersthesis {525, title = {Interaktive Visualisierung f{\"u}r Sequenzen geordneter und verkn{\"u}pfter Daten}, volume = {Diploma}, year = {2014}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Georg Robin Minorics} } @proceedings {2014_ISeeCube_-_Visual_Analysis_of_Gaze_Data_for_Video, title = {ISeeCube - Visual Analysis of Gaze Data for Video}, journal = {Proceedings of the 2014 Symposium on Eye Tracking Research and Applications (ETRA)}, year = {2014}, pages = {43{\textendash}50}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, doi = {10.1145/2578153.2578158}, url = {http://doi.acm.org/10.1145/2578153.2578158}, author = {Kurzhals, Kuno and Heimerl, Florian and Weiskopf, Daniel} } @article {SSS+14a, title = {Knowledge Generation Model for Visual Analytics}, journal = {IEEE Transactions on Visualization and Computer Graphics (Proceedings Visual Analytics Science and Technology 2014}, volume = {20}, year = {2014}, pages = {1613}, chapter = {1604}, keywords = {[Project Phase 2] Feature-based Visualization and Analysis of Natural Language Documents}, doi = {10.1109/TVCG.2014.2346481}, author = {Dominik Sacha and Andreas Stoffel and Florian Stoffel and Bum Chul Kwon and Geoffrey Ellis and Keim, Daniel A.} } @article {Bittig{\textendash}Membranerelateddynamicsandtheformationofactinincellsgrowingonmicro-topographiesAspatialcomputationalmodel{\textendash}2014, title = {Membrane related dynamics and the formation of actin in cells growing on micro-topographies: A spatial computational model}, journal = {BMC Systems Biology}, volume = {8}, number = {106}, year = {2014}, pages = {1{\textendash}19}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, doi = {10.1186/s12918-014-0106-2}, author = {Bittig, Arne T. and Matschegewski, Claudia and Nebe, J. Barbara and St{\"a}hlke, Susanne and Uhrmacher, Adelinde M.} } @article {466, title = {A Modular Degree-of-Interest Specification for the Visual Analysis of Large Dynamic Networks}, journal = {IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS}, volume = {20}, year = {2014}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Abello--AModularDegree-of-InterestSpecificationfortheVisualAnalysisofLargeDynamicNetworks--2014.pdf}, author = {J. Abello and S. Hadlak and H. Schumann and H.-J. Schulz} } @mastersthesis {524, title = {Multi-Dokumenten-Analyse mittels erweiterter Word-Cloud-Visualisierung}, volume = {B. Sc.}, year = {2014}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Cyrill Fabian Bopp} } @article {383, title = {Myeloid cell RelA/p65 promotes lung cancer proliferation through Wnt/β-catenin signaling in murine and human tumor cells}, journal = {Oncogene}, year = {2014}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, doi = {10.1038/onc.2013.75}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Li et al., 2013.pdf}, author = {D. Li and C. Beisswenger and C. Herr and J. Hellberg and G. Han and T. Zakharkina and M. Voss and R. Wiewrodt and R.M. Bohle and M.D. Menger and R.M. Schmid and D. St{\"o}ckel and H.-P. Lenhof and R. Bals} } @article {mzTab\_MCP\_2014, title = {The mzTab Data Exchange Format: communicating MS-based proteomics and metabolomics experimental results to a wider audience}, journal = {Mol. Cell. Prot.}, year = {2014}, pages = {2765-2775}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Mol Cell Proteomics-2014-Griss-2765-75-2.pdf}, author = {Griss, Johannes and Jones, Andrew R and Sachsenberg, Timo and Walzer, Mathias and Gatto, Laurent and Hartler, J{\"u}rgen and Thallinger, Gerhard G and Salek, Reza M and Steinbeck, Christhop and Neuhauser, Nadin and Cox, J{\"u}rgen and Neumann, Steffen and Fan, Jun and Reisinger, Florian and Xu, Qing-Wei and Bandeira, Nuno and Xenarios, Ioannis and Oliver Kohlbacher and Vizcaino, Juan Antonio and Hermjakob, Henning} } @mastersthesis {520, title = {Natural Language Processing and Information Retrieval Methods for Intellectual Property Analysis}, volume = {PhD}, year = {2014}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {C. Jochim} } @article {Bekos20141, title = {A note on maximum differential coloring of planar graphs}, journal = {Journal of Discrete Algorithms}, volume = {29}, year = {2014}, pages = {1 - 7}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, issn = {1570-8667}, doi = {http://dx.doi.org/10.1016/j.jda.2014.06.004}, url = {http://www.sciencedirect.com/science/article/pii/S1570866714000458}, author = {M.A. Bekos and M. Kaufmann and S. Kobourov and S. Veeramoni} } @conference {DBLP:conf/ieeevast/FischerS14, title = {NStreamAware: Real-Time visual analytics for data streams (VAST Challenge 2014 MC3)}, booktitle = {2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014}, year = {2014}, pages = {373{\textendash}374}, keywords = {[Project Phase 2] Feature-based Visualization and Analysis of Natural Language Documents}, doi = {10.1109/VAST.2014.7042572}, url = {http://dx.doi.org/10.1109/VAST.2014.7042572}, author = {Fabian Fischer and Florian Stoffel} } @article {schaefer_et_al_14a, title = {Semi-automatic motion compensation of contrast-enhanced ultrasound images from abdominal organs for perfusion analysis}, journal = {Computers in Biology and Medicine}, year = {2014}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/schaefer_et_al_14a.pdf}, author = {S. Sch{\"a}fer and K. Nylund and S{\ae}vik, F. and Engjom, T. and M{\'e}zl, M. and Ji{\v r}{\'\i}k, R. and Dimcevski, G. and O.H. Gilja and K. D. T{\"o}nnies} } @proceedings {604, title = {SMVC: Semi-Supervised Multi-View Clustering in Subspace Projections}, journal = {ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD{\textquoteright}14)}, volume = {20}, year = {2014}, pages = {253-262}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {S. G{\"u}nnemann and I. F{\"a}rber and T. Mausbach and T. Seidl} } @proceedings {478, title = {A Stream-Based Architecture for the Management and On-Line Analysis of Unbounded Amounts of Simulation Data}, journal = {SIGSIM-PADS {\textquoteright}14}, year = {2014}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, doi = {10.1145/2601381.2601399}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Schuetzel--AStream-basedArchitecturefortheManagementandOn-lineAnalysisofUnboundedAmountsofSimulationData--2014.pdf}, author = {J. Sch{\"u}tzel and H. Meyer and A. Uhrmacher} } @proceedings {473, title = {Supporting an Early Detection of Diabetic Neuropathy by Visual Analytics}, journal = {EuroVis Workshop on Visual Analytics}, year = {2014}, publisher = {Eurographics Association}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, doi = {10.2312/eurova.20141145}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Luboschik--SupportinganEarlyDetectionofDiabeticNeuropathybyVisualAnalytics--2014.pdf}, author = {M. Luboschik and M. R{\"o}hlig and G. Kundt and O. Stachs and S. Pechsel and A. Zhivov and R. F. Guthoff and K. Winter and H. Schumann} } @article {474, title = {Supporting the Integrated Visual Analysis of Input Parameters and Simulation Trajectories}, year = {2014}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Luboschik--SupportingtheIntegratedVisualAnalysisofInputParametersandSimulationTrajectories--2014.pdf}, author = {M. Luboschik and S. Rybacki and F. Haack and H.-J. Schulz} } @article {PlateletsBlood2013, title = {Time-resolved characterization of cAMP/PKA-dependant signaling reveals that platelet inhibition is a concerted process involving multiple signaling pathways}, journal = {Blood}, volume = {123}, number = {4}, year = {2014}, pages = {e1-e10}, abstract = {One of the most important physiological platelet inhibitors is endothelium-derived prostacyclin which stimulates the platelet cAMP/PKA signaling cascade and inhibits virtually all platelet activating key mechanisms. Using quantitative mass spectrometry, we analyzed time resolved phosphorylation patterns in human platelets after treatment with Iloprost, a stable prostacyclin analogue, for 0, 10, 30 and 60 seconds to characterize key mediators of platelet inhibition and activation in three independent biological replicates. We quantified over 2,700 different phosphorylated peptides of which 360 were significantly regulated upon stimulation. This comprehensive and time-resolved analysis indicates that platelet inhibition is a multi-pronged process involving different kinases and phosphatases as well as many previously unanticipated proteins and pathways.}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, author = {Beck, Florian and Geiger, J{\"o}rg and Gambaryan, Stepan and Veit, Johannes and Marc Vaudel and Nollau, Peter and Oliver Kohlbacher and Martens, Lennart and Walter, Ulrich and Sickmann, Albert and Zahedi, Ren{\'e} P} } @inbook {592, title = {A Topology-Based Approach to Visualize the Thematic Composition of Document Collections}, booktitle = {Text Mining, Theory and Applications of Natural Language Processing}, year = {2014}, pages = {63-85}, keywords = {[Project Phase 2] Topology-based Visual Analysis of Information Spaces}, doi = {10.1007/978-3-319-12655-5_4}, url = {http://visualanalytics.de/sites/default/files/upload/publications/2014_A_Topology-Based_Approach_to_Visualize_the_Thematic_Composition_of_Document_Collections.pdf}, author = {Patrick Oesterling and Christian Heine and Gunther H. Weber and Gerik Scheuermann} } @article {koenig_et_al_14a, title = {Ultrasound texture-based CAD system for detecting neuromuscular diseases}, journal = {International Journal of Computer Assisted Radiology and Surgery}, year = {2014}, pages = {1-11}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/koenig_et_al_14a.pdf}, author = {T. K{\"o}nig and J. Steffen and M. Rak and G. Neumann and L. von Rohden and K. D. T{\"o}nnies} } @proceedings {459, title = {Unsupervised Training Set Generation for Automatic Acquisition of Technical Terminology in Patents}, journal = {25th International Conference on Computational Linguistics (Coling)}, year = {2014}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, url = {http://visualanalytics.de/sites/default/files/upload/publications/judea,schutze,brugmann,coling,2014.pdf}, author = {A. Judea and H. Sch{\"u}tze and S. Bruegmann} } @conference {judea-schutze-bruegmann:2014:Coling, title = {Unsupervised Training Set Generation for Automatic Acquisition of Technical Terminology in Patents}, booktitle = {Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers}, year = {2014}, pages = {290{\textendash}300}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Alex Judea and Hinrich Sch{\"u}tze and Bruegmann, Soeren} } @conference {DBLP:conf/ieeevast/StoffelF14, title = {Using a knowledge graph data structure to analyze text documents (VAST challenge 2014 MC1)}, booktitle = {2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014}, year = {2014}, pages = {331{\textendash}332}, keywords = {[Project Phase 2] Feature-based Visualization and Analysis of Natural Language Documents}, doi = {10.1109/VAST.2014.7042551}, url = {http://dx.doi.org/10.1109/VAST.2014.7042551}, author = {Florian Stoffel and Fabian Fischer} } @conference {DBLP:conf/ieeevast/FischerSMSK14, title = {Using visual analytics to support decision making to solve the Kronos incident (VAST challenge 2014)}, booktitle = {2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014}, year = {2014}, pages = {301{\textendash}302}, keywords = {[Project Phase 2] Feature-based Visualization and Analysis of Natural Language Documents}, doi = {10.1109/VAST.2014.7042537}, url = {http://dx.doi.org/10.1109/VAST.2014.7042537}, author = {Fabian Fischer and Florian Stoffel and Sebastian Mittelst{\"a}dt and Tobias Schreck and Keim, Daniel A.} } @mastersthesis {455, title = {Vieldimensionale Qualit{\"a}tsma{\ss}e f{\"u}r die Suche in Unterr{\"a}umen hochdimensionaler Datens{\"a}tze}, volume = {M. Sc.}, year = {2014}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, author = {T. L{\"o}we} } @conference {kwon2014visjockey, title = {VisJockey: Enriching Data Stories through Orchestrated Interactive Visualization (Poster)}, booktitle = {Computation+ Journalism Symposium 2014}, year = {2014}, keywords = {[Project Phase 2] Feature-based Visualization and Analysis of Natural Language Documents}, author = {Bum Chul Kwon and Florian Stoffel and Dominik J{\"a}ckle and Bongshin Lee and Keim, Daniel A.} } @article {476, title = {Visual Analysis for an Early Detection of Diabetic Neuropathy}, year = {2014}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, doi = {10.1055/s-0034-1383332}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Roehlig--VisuelleAnalysezurFruherkennungeinerDiabetischenNeuropathie--2014.pdf}, author = {M. R{\"o}hlig and M. Luboschik and G. Kundt and O. Stachs and S. Pechsel and A. Zhivov and R. F. Guthoff and K. Winter and H. Schumann} } @mastersthesis {454, title = {Visual Analysis of High-Dimensional Spaces}, volume = {PhD}, year = {2014}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, author = {G. Albuquerque} } @mastersthesis {Glasser2014, title = {Visual Analysis, Clustering, and Classification of Contrast-Enhanced Tumor Perfusion MRI Data}, volume = {PhD}, year = {2014}, school = {Otto-von-Guericke University Magdeburg}, address = {Magdeburg, Germany}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, author = {Sylvia Gla{\ss}er} } @proceedings {378, title = {A Visual Analytics Approach to Study Anatomic Covariation}, journal = {IEEE PacificVis 2014}, year = {2014}, keywords = {[Project Phase 2] Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes}, url = {http://cg.cs.uni-bonn.de/de/publikationen/paper-details/hermann2014-covariance/}, author = {M. Hermann and A.C. Schunke and R. Klein} } @inbook {461, title = {Visual Analytics of Image-Centric Cohort Studies in Epidemiology}, booktitle = {Visualization in Medicine and Life Sciences III}, year = {2014}, pages = {in print}, publisher = {Springer}, organization = {Springer}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Visual Analytics of Image-Centric Cohort Studies in Epidemiology.pdf}, author = {B. Preim and P. Klemm and H. Hauser and K. Hegenscheid and S. Oeltze and K. Toennies and H. V{\"o}lzke} } @conference {lrec2014, title = {A Visual Focus+Context Approach for Text Comparison Tasks}, booktitle = {VisLR Workshop, LREC 2014}, year = {2014}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {John, Markus and Heimerl, Florian and Andreas M{\"u}ller and Koch, Steffen} } @mastersthesis {Stecker{\textendash}VisualisierungvonProvenanceInformationzurExplorationvonSimulationsdaten{\textendash}2014, title = {Visualisierung von Provenanceinformation zur Exploration von Simulationsdaten}, volume = {B. Sc.}, year = {2014}, school = {University of Rostock, Germany}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {Matthias Stecker} } @proceedings {392, title = {Visualization of Trajectory Attributes in Space{\textendash}Time Cube and Trajectory Wall}, journal = {Cartography from Pole to Pole - Lecture Notes in Geoinformation and Cartography}, year = {2014}, pages = {157--163}, publisher = {Springer}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, isbn = {978-3-642-32617-2}, author = {G. Andrienko and N. Andrienko and H. Schumann and C. Tominski} } @mastersthesis {Perlich2014, title = {Visuell-interaktive, merkmalsbasierte Analyse von Fu{\ss}ball-Bewegungsdaten}, volume = {M.Sc.}, year = {2014}, note = {Bachelorthesis}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, author = {David Perlich} } @article {Roehlig{\textendash}VisuelleAnalysezurFruherkennungeinerDiabetischenNeuropathie{\textendash}2014, title = {Visuelle Analyse zur Fr{\"u}herkennung einer Diabetischen Neuropathie}, journal = {Klinische Monatsbl{\"a}tter f{\"u}r Augenheilkunde, Sonderausgabe zu Neuen Technologien}, volume = {231}, year = {2014}, pages = {1162{\textendash}1169}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, doi = {10.1055/s-0034-1383332}, author = {Martin R{\"o}hlig and Martin Luboschik and G{\"u}nther Kundt and Oliver Stachs and Sabine Peschel and Andrey Zhivov and Rudolf F. Guthoff and Karsten Winter and Heidrun Schumann} } @conference { TUD-CS-2014-0013, title = {What Makes a Good Biography? Multidimensional Quality Analysis Based on Wikipedia Article Feedback Data}, booktitle = {Proceedings of the 23rd International World Wide Web Conference (WWW 2014)}, year = {2014}, pages = {855-866}, publisher = {International World Wide Web Conferences Steering Committee}, organization = {International World Wide Web Conferences Steering Committee}, address = {Republic and Canton of Geneva, Switzerland}, keywords = {[Project Phase 2] Feature-based Visualization and Analysis of Natural Language Documents}, author = {Lucie Flekova and Oliver Ferschke and Iryna Gurevych} } @proceedings {366, title = {Word Cloud Explorer: Text Analytics based on Word Clouds (to appear)}, journal = {System Sciences (HICSS), 2014 47th Hawaii International Conference on}, year = {2014}, pages = {31-39}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {F. Heimerl and S. Lohmann and S. Lange and T. Ertl} } @mastersthesis {505, title = {Geovisual analytics for lay users: A user-centred approach}, volume = {MsC}, year = {2013}, month = {2013}, school = {University of Oldenburg}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, author = {D. Hauser} } @mastersthesis {535, title = {Jacobian Optimization with Multi Scaled Elastic Registration using Decomposition by the Jacobian Nullset}, volume = {M.Sc.}, year = {2013}, month = {2013}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, author = {Stephan Fischer} } @mastersthesis {511, title = {The probabilistic active shape model}, volume = {PhD}, year = {2013}, month = {2013}, address = {Darmstadt}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {M. Kirschner} } @mastersthesis {536, title = {Tracking of mesoscale eddies in the Agulhas current in different spatial and temporal resolutions}, volume = {B. Sc.}, year = {2013}, month = {2013}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, author = {Johannes Jendersie} } @proceedings {348, title = {An Adaptive Subdivision Scheme for Quadratic Programming in Multi-label Image Segmentation}, journal = {Proceedings of the British Machine Vision Conference}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, author = {M. Rak and T. K{\"o}nig and K. D. T{\"o}nnies} } @article {394, title = {Analyzing Simulations of Biochemical Systems with Feature-Based Visual Analytics}, journal = {Computers \& Graphics}, volume = {38}, year = {2013}, pages = {18-26}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, doi = {10.1016/j.cag.2013.09.001}, author = {C. Eichner and A. Bittig and H. Schumann and C. Tominski} } @mastersthesis {417, title = {An approach for steerable visual subspace search for pattern discovery in high dimensional data}, volume = {Master of Science}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {F. Maa{\ss}} } @proceedings {399, title = {An Approximate Execution of Rule-Based Multi-level Models}, journal = {Computational Methods in Systems Biology}, volume = {8130}, year = {2013}, pages = {19--32}, publisher = {Springer Berlin Heidelberg}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, isbn = {978-3-642-40707-9}, author = {T. Helms and M. Luboschik and H. Schumann and A. Uhrmacher} } @proceedings {415, title = {Assessing End-User Interaction for Multi-Criteria Local Search with Heatmap and Icon based Visualizations }, journal = {ACM SIGSPATIAL International Workshop on Interacting with Maps (MapInteract)}, year = {2013}, address = {Orlando}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/MapInteract13_Kumar.pdf}, author = {C. Kumar and B. Poppinga and D. Haeuser and W. Heuten and S. Boll} } @proceedings {372, title = {Bootstrapping lexicons for technical domains. To Appear}, journal = {Proceedings of the 6th International Joint Conference on Natural Language Processing}, year = {2013}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {P. Ziering and L. van der Plas and H. Sch{\"u}tze} } @conference { TUD-CS-2013-0166, title = {Can We Hide in the Web? Large Scale Simultaneous Age and Gender Author Profiling in Social Media - Notebook for PAN at CLEF 2013}, booktitle = {CLEF 2013 Labs and Workshops - Online Working Notes}, year = {2013}, publisher = {PROMISE}, organization = {PROMISE}, address = {Padua, Italy}, keywords = {[Project Phase 2] Feature-based Visualization and Analysis of Natural Language Documents}, isbn = {978-88-904810-5-5}, issn = {2038-4963}, author = {Lucie Flekova and Iryna Gurevych}, editor = {Pamela Forner and Roberto Navigli and Dan Tufis} } @proceedings {345, title = {Classification of Benign and Malignant DCE-MRI Breast Tumors by Analyzing the Most Suspect Region}, journal = {Proc. of Bildverarbeitung f{\"u}r die Medizin}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Classification of Benign and Malignant DCE-MRI Breast Tumors by Analyzing the Most Suspect Region.pdf}, author = {S. Gla{\ss}er and U. Niemann and U. Preim and M. Spiliopoulou and B. Preim} } @conference {rak_et_al_13b, title = {Closed-Form Hierarchical Finite Element Models for Part-Based Object Detection}, booktitle = {Proceedings of the International Workshop on Vision, Modeling and Visualization}, year = {2013}, pages = {137-144}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/rak_et_al_13b.pdf}, author = {M. Rak and K. Engel and K. D. T{\"o}nnies} } @proceedings {364, title = {Combining an SVM Classifier and Character N-gram Language Models for Sentiment Analysis on Twitter Text}, journal = {Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)}, year = {2013}, pages = {520-524}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Q. Han and J. Guo and H. Sch{\"u}tze} } @mastersthesis {418, title = {Constraint-based Susbpace Clustering utilizing Combined Graph clustering Methods}, volume = {Master of Science}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {P. Gerwert} } @article {400, title = {Constructing and Visualizing Chemical Reaction Networks from Pi-Calculus Models}, journal = {Formal Aspects of Computing}, volume = {25}, year = {2013}, pages = {723--742}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. John and H.-J. Schulz and H. Schumann and A. Uhrmacher and A. Unger} } @proceedings {414, title = {Criteria of Query-Independent Page Significance in Geospatial Web Search }, journal = {7th ACM SIGSPATIAL Workshop on Geographic Information Retrieval (GIR) }, year = {2013}, address = {Orlando}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = { http://visualanalytics.de/sites/default/files/upload/publications/GIR13-Kumar.pdf}, author = {C. Kumar and S. Boll} } @article {405, title = {A Design Space of Visualization Tasks}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {19}, year = {2013}, pages = {2366--2375}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {H.-J. Schulz and T. Nocke and M. Heitzler and H. Schumann} } @mastersthesis {456, title = {Design und Implementierung einer Landschaftsmetapher zur visuellen Analyse geografisch und zeitlich markierter Daten}, year = {2013}, keywords = {[Project Phase 2] Topology-based Visual Analysis of Information Spaces}, author = {T. Liebmann} } @proceedings {387, title = {Detecting and Exploring Clusters in Attributed Graphs}, journal = {Proceedings of the 22nd ACM Conference on Information and Knowledge Management (CIKM 2013)}, year = {2013}, address = {San Francisco, CA, USA}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {B. Boden and R. Haag and T. Seidl} } @article {355, title = {Discovering Thematic Patterns in Geo-Referenced Tweets through Space-Time Visual Analytics}, journal = {Computing in Science and Engineering}, volume = {v.15(3)}, year = {2013}, pages = {pp.72-82}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://doi.ieeecomputersociety.org/10.1109/MCSE.2013.70}, author = {G. Andrienko and N. Andrienko and H. Bosch and T. Ertl and G. Fuchs and P. Jankowski and D. Thom} } @mastersthesis {450, title = {Ein neues Abstandsma{\ss} f{\"u}r den Vergleich von form{\"a}hnlichen Meshes mit lokalen Abweichungen}, volume = {M. Sc.}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {R. Getto} } @mastersthesis {rak_13a, title = {Eine geschlossene Formulierung f{\"u}r hiearchische Finite-Elemente-Modelle - Anwendungsfall: Erkennung von Wirbels{\"a}ulen in Magnetresonanztomographien}, volume = {M.Sc.}, year = {2013}, school = {Otto von Guericke University}, address = {Magdeburg, Germany}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/rak_et_al_13a.pdf}, author = {M. Rak} } @proceedings {374, title = {Evaluation of Attention-Guiding Video Visualization}, journal = {Computer Graphics Forum 32}, volume = {3}, year = {2013}, pages = {51-60}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/2 - Evaluation of Attention-Guiding Video Visualization.pdf}, author = {K. Kurzhals and M. H{\"o}ferlin and D. Weiskopf} } @mastersthesis {447, title = {Evaluationsmethoden zum Vergleich linearer und nichtlinearer Formenr{\"a}ume basierend auf geod{\"a}tischen Pfaden}, volume = {B. Sc. }, year = {2013}, keywords = {[Project Phase 2] Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes}, author = {H. P{\"o}ttker} } @conference {627, title = {Feature propagation on image webs for enhanced image retrieval}, booktitle = {Proceedings of the 3rd ACM conference on International conference on multimedia retrieval. ACM, 2013}, year = {2013}, keywords = {[Project Phase 1] Zoomable Cell}, author = {Brachmann, Eric and Spehr, Marcel and Gumhold, Stefan} } @article {406, title = {Feature-based Automatic Identification of Interesting Data Segments in Group Movement Data}, journal = {Information Visualization}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, doi = {10.1177/1473871613477851 }, author = {T. von Landesberger and S. Bremm and T. Schreck and D. Fellner} } @proceedings {395, title = {Feature-Based Visual Analytics for Studying Simulations of Dynamic Bi-Stable Spatial Systems}, journal = {Proceedings of the EuroVis Workshop on Visual Analytics (EuroVA{\textquoteright}13)}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {C. Eichner and A. Bittig and H. Schumann and C. Tominski} } @article {359, title = {A General Framework for Trajectory DataWarehousing and Visual OLAP}, journal = {Geoinformatica}, year = {2013}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1007/s10707-013-0181-3}, author = {L. Leonardi and S. Orlando and A. Raffaet{\textquoteright}a and A. Roncato and C. Silvestri and G. Andrienko and N. Andrienko} } @proceedings {398, title = {A Generic Adaptive Simulation Algorithm for Component-based Simulation Systems}, journal = {Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {T. Helms and R. Ewald and S. Rybacki and A. Uhrmacher} } @proceedings {409, title = {Geovisual interfaces to find suitable urban regions for citizens: a user-centered requirement study }, journal = {Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication}, year = {2013}, pages = {741-744}, publisher = {UbiComp }, address = {Z{\"u}rich}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/UbiComp13_Kumar.pdf}, author = {C. Kumar and B. Poppinga and D. Haeuser and W. Heuten and S. Boll} } @proceedings {412, title = {Geovisualization for End User Decision Support: Easy and Effective Exploration of Urban Areas }, journal = {GeoViz}, year = {2013}, address = {Hamburg}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/GeoViz13_Kumar.pdf}, author = {C. Kumar and W. Heuten and S. Boll} } @mastersthesis {434, title = {Illustrative Informationsvisualisierung}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Luboschik} } @mastersthesis {526, title = {Improvements of Patent Retrieval: Does Automatic Terminology Recognition improve Information Retrieval on Patents}, volume = {B. Sc.}, year = {2013}, author = {Patrik Eckebrecht} } @mastersthesis {419, title = {Integration von Vorwissen in mischverteilungsbasierte Multi-View Subspace Clusteringverfahren}, volume = {Master of Science}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {M. R{\"u}diger} } @proceedings {411, title = {Interactive Exploration of Geographic Regions with Web-based Keyword Distributions }, journal = {Proceedings of the 3rd European Workshop on Human-Computer Interaction and Information Retrieval}, year = {2013}, pages = {11-14}, publisher = {SIGIR }, address = {Dublin}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/EuroHCIR13_Main.pdf}, author = {C. Kumar and D. Ahlers and W. Heuten and S. Boll} } @article {375, title = {Interactive Schematic Summaries for Faceted Exploration of Surveillance Video}, journal = {IEEE Transactions on Multimedia 15}, volume = {4}, year = {2013}, pages = {908-920}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/4 - Interactive Schematic Summaries for Faceted Exploration of Surveillance Video.pdf}, author = {M. H{\"o}ferlin and B. H{\"o}ferlin and G. Heidemann and D. Weiskopf} } @mastersthesis {436, title = {Interactive Steering of Analytic Clustering}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Egibyan} } @mastersthesis {527, title = {Interaktiver Ansatz fuer die visuelle Analyse von Textdokumenten basierend auf der Word-Cloud Visualisierungstechnik}, volume = {Diploma}, year = {2013}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {Simon Lange} } @article {358, title = {The Liberation of Mobile Location Data and its Implications for Privacy Research}, journal = {ACM SIGMOBILE Mobile Computing and Communication review}, volume = {v.17(2)}, year = {2013}, pages = {pp.7-18}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1145/2505395.2505398}, author = {G. Andrienko and A. Gkoulalas-divanis and M. Gruteser and C. Kopp and T. Liebig and K. Rechert} } @article {390, title = {A Modular Degree-of-Interest Specification for the Visual Analysis of Large Dynamic Networks}, journal = {IEEE Transactions on Visualization and Computer Graphics}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {J. Abello and S. Hadlak and H. Schumann and H.-J. Schulz} } @mastersthesis {421, title = {Modularity-based determination of node clusters and their significant edge subspaces in networks with vector-labeled edges}, volume = {Bachelor of Science}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {G. Stepien} } @proceedings {371, title = {Multilingual lexicon bootstrapping - Improving a lexicon induction system using a parallel corpus. To appear}, journal = {Proceedings of the 6th International Joint Conference on Natural Language Processing}, year = {2013}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {P. Ziering and L. van der Plas and H. Sch{\"u}tze} } @proceedings {396, title = {Navigation Recommendations for Exploring Hierarchical Graphs}, journal = {Advances in Visual Computing}, year = {2013}, publisher = {Springer}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {S. Gladisch and H. Schumann and C. Tominski} } @article {384, title = {NetworkTrail--a web service for identifying and visualizing deregulated subnetworks}, journal = {Bioinformatics (Oxford, England)}, volume = {29(13)}, year = {2013}, pages = {1702-3}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/St{\"o}ckel et al., 2013.pdf}, author = {D. St{\"o}ckel and O. M{\"u}ller and T. Kehl and A. Gerasch and C. Backes and A. Rurainski and A. Keller and M. Kaufmann and H.-P. Lenhof} } @article {356, title = {Opening up the "black box" of Medical Image Segmentation with Statistical Shape Models}, journal = {The Visual Computer}, volume = {v.29(9)}, year = {2013}, pages = {pp.893-905}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context, [Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, doi = {http://dx.doi.org/10.1007/s00371-013-0852-y}, author = {T. von Landesberger and G. Andrienko and N. Andrienko and S. Bremm and M. Kirschner and S. Wesarg and A. Kujper} } @proceedings {376, title = {Orthographic Star Coordinates}, journal = {IEEE Transactions on Visualization and Computer Graphics (Proceedings IEEE Information Visualization)}, year = {2013}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, url = {http://vc.cs.ovgu.de/files/publications/2013/Lehmann_2013_InfoVis.pdf}, author = {D. J. Lehmann and H. Theisel} } @proceedings {362, title = {Privacy-preserving Distributed Movement Data Aggregation}, journal = {AGILE}, year = {2013}, publisher = {Springer }, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1007/978-3-319-00615-4_13}, author = {A. Monreale and W. Hui Wang and F. Pratesi and S. Rinzivillo and D. Pedreschi and G. Andrienko and N. Andrienko} } @proceedings {370, title = {Prolix - Visual Prediction Analysis for Box Office Success}, journal = {Visual Analytics Science and Technology (VAST)}, year = {2013}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {R. Kr{\"u}ger and H. Bosch and D. Thom and E. P{\"u}ttmann and Q. Han and S. Koch and F. Heimerl and T. Ertl} } @article {352, title = {Scalable Analysis of Movement Data for Extracting and Exploring Significant Places}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {v. 19(7)}, year = {2013}, pages = {pp.1078-1094}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1109/TVCG.2012.311}, author = {G. Andrienko and N. Andrienko and C. Hurter and S. Rinzivillo and S. Wrobel} } @article {373, title = {Scalable Video Visual Analytics}, journal = {Information Visualization Journal}, year = {2013}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, doi = {10.1177/1473871613488571}, url = {http://visualanalytics.de/sites/default/files/upload/publications/1 - Scalable video visual analytics.pdf}, author = {B. H{\"o}ferlin and M. H{\"o}ferlin and D. Weiskopf and G. Heidemann} } @mastersthesis {429, title = {Scalable Visual Analytics in Video Surveillance }, year = {2013}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {B. H{\"o}ferlin} } @proceedings {363, title = {ScatterBlogs2: Real-Time Monitoring of Microblog Messages Through User-Guided Filtering (to appear)}, journal = {Visualization and Computer Graphics}, year = {2013}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {H. Bosch and D. Thom and F. Heimerl and E. P{\"u}ttmann and S. Koch and R. Kr{\"u}ger and M. W{\"o}rner and T. Ertl} } @article {357, title = {Semantic Trajectories Modeling and Analysis}, journal = {ACM Computing Surveys}, volume = {v.45(4)}, year = {2013}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, author = {C. Parent and S. Spaccapietra and C. Renso and G. Andrienko and N. Andrienko and V. Bogorny and M. L. Damiani and A. Gkoulalas-divanis and J. Macedo and N. Pelekis and Y. Theodoridis and Y. Zan} } @article {382, title = {Smooth Orthogonal Layouts}, journal = {Journal of Graph Algorithms and Applications}, volume = {17}, year = {2013}, pages = {575-595}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Bekos et al., accepted.pdf}, author = {M. Bekos and M. Kaufmann and S. Kobourov and A. Symvonis} } @article {351, title = {Space Transformation for Understanding Group Movement}, journal = {IEEE Transactions on Visualization and Computer Graphics (Proceedings IEEE VAST 2013)}, volume = {vol. 19(12)}, year = {2013}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, author = {N. Andrienko and G. Andrienko and L. Barrett and M. Dostie and P. Henzi} } @proceedings {388, title = {Spectral Subspace Clustering for Graphs with Feature Vectors}, journal = {Proceedings of the IEEE International Conference on Data Mining (ICDM 2013)}, year = {2013}, address = {Dallas, TX, USA}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {S. G{\"u}nnemann and I. F{\"a}rber and S. Raubach and T. Seidl} } @article {469, title = {Studying the Role of Lipid Rafts on Protein Receptor Bindings with Cellular Automata}, journal = {IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS}, volume = {10}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Haack--StudyingtheRoleofLipidRaftsonProteinReceptorBindingswithCellularAutomata--2013.pdf}, author = {F. Haack and K. Burrage and R. Redmer and A. Uhrmacher} } @article {401, title = {Supporting the Integrated Visual Analysis of Input Parameters and Simulation Trajectories}, journal = {Computers \& Graphics}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Luboschik and S. Rybacki and F. Haack and H.-J. Schulz} } @article {397, title = {Supporting the Visual Analysis of Dynamic Networks by Clustering associated Temporal Attributes}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {19}, year = {2013}, pages = {2267--2276}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {S. Hadlak and H. Schumann and C.H. Cap and T. Wollenberg} } @inbook {424, title = {Texture-Based Detection of Myositis in Ultrasonographies}, booktitle = {Bildverarbeitung f{\"u}r die Medizin}, year = {2013}, pages = {81-86}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/koenig_et_al_13a.pdf}, author = {T. K{\"o}nig and M. Rak and J. Steffen and G. Neumann and L. von Rohden and K. D. T{\"o}nnies} } @mastersthesis {438, title = {Touchinteraktion f{\"u}r die Exploration und Manipulation von Graphen}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {B. Waldhauer} } @proceedings {391, title = {Towards a Contextualized Visual Analysis of Heterogeneous Manufacturing Data}, journal = {Proceedings of the International Symposium on Visual Computing (ISVC{\textquoteright}2013)}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Aehnelt and H.-J. Schulz and B. Urban} } @proceedings {360, title = {Towards Privacy-Preserving Semantic Mobility Analysis}, journal = {EuroVA, International Workshop on Visual Analytics}, year = {2013}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, author = {N. Andrienko and G. Andrienko and G. Fuchs} } @proceedings {393, title = {Towards Visualizing Geo-Referenced Climate Networks}, journal = {Workshop GeoViz Interactive Maps that Help People Think}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {S. Buschmann and T. Nocke and C. Tominski} } @mastersthesis {428, title = {Video Visual Analytics}, year = {2013}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {M. H{\"o}ferlin} } @mastersthesis {451, title = {Visual Analysis of Local Correspondence in Segmentation Quality}, volume = {B. Sc.}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {D. Basgier} } @proceedings {344, title = {Visual analysis of longitudinal brain tumor perfusion}, journal = {Proc. of SPIE Medical Imaging}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Visual analysis of longitudinal brain tumor perfusion.pdf}, author = {S. Gla{\ss}er and S. Oeltze and U. Preim and A. Bjornerud and H. Hauser and B. Preim} } @mastersthesis {453, title = {Visual Analytics Approaches for Descriptor Space Comparison and the Exploration of Time Dependent Data}, volume = {PhD}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {S. Bremm} } @article {407, title = {Visual Analytics for model-based medical image segmentation: Opportunities and challenges}, journal = {Expert Syst. Appl.}, volume = {40 (12)}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {T. von Landesberger and S. Bremm and M. Kirschner and S. Wesarg and A. Kuijper} } @article {301, title = {A Visual Analytics Framework for Spatio-temporal Analysis and Modelling}, journal = {Data Mining and Knowledge Discovery}, year = {2013}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1007/s10618-012-0285-7}, author = {N. Andrienko and G. Andrienko} } @article {353, title = {A Visual Analytics Framework for Spatio-temporal Analysis and Modelling}, journal = {Data Mining and Knowledge Discovery}, volume = { vol. 27(1)}, year = {2013}, pages = {pp.55-83}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1007/s10618-012-0285-7}, author = {N. Andrienko and G. Andrienko} } @book {350, title = {Visual Analytics of Movement}, year = {2013}, publisher = {Springer}, organization = {Springer}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://www.springer.com/computer/database+management+\%26+information+retrieval/book/978-3-642-37582-8}, author = {G. Andrienko and N. Andrienko and P. Bak and D.A. Keim and S. Wrobel} } @article {302, title = {Visual Analytics of Movement: an Overview of Methods, Tools, and Procedures}, journal = {Information Visualization}, year = {2013}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1177/1473871612457601}, author = {N. Andrienko and G. Andrienko} } @article {354, title = {Visual Analytics of Movement: an Overview of Methods, Tools, and Procedures}, journal = {Information Visualization}, volume = {vol. 12(1)}, year = {2013}, pages = {pp.3-24}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1177/1473871612457601}, author = {N. Andrienko and G. Andrienko} } @mastersthesis {416, title = {Visual Analytics of Patterns in High-Dimensional Data}, volume = {Dr. }, year = {2013}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {A. Tatu} } @proceedings {369, title = {Visual Document Retrieval: Supporting Text Search and Analysis with Visual Analytics}, journal = {Computing in Science \& Engineering}, volume = {15}, year = {2013}, pages = {66-74}, publisher = {IEEE}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, url = {http://visualanalytics.de/sites/default/files/upload/publications/CiSE2013.pdf}, author = {S. Koch and F. Heimerl and T. Ertl} } @proceedings {413, title = {A Visual Interactive System for Spatial Querying and Ranking of Geographic Regions }, journal = {Proceedings of the 13th ACM International Conference on Knowledge Management and Knowledge Computing}, year = {2013}, address = {Graz}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/i-KNOW13_Kumar.pdf}, author = {C. Kumar and W. Heuten and S. Boll} } @proceedings {361, title = {Visual Task Solution Strategies in Tree Diagrams}, journal = {IEEE Pacific Visualization}, year = {2013}, publisher = {IEEE Computer Society Press}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data, [Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, author = {M. Burch and G. Andrienko and N. Andrienko and M. H{\"o}ferlin and M. Raschke and D. Weiskopf} } @mastersthesis {437, title = {Visualisierung multivariater Daten entlang von Bewegungstrajektorien}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {F. Breuel} } @proceedings {349, title = {Visualization and Analysis of Lumbar Spine Canal Variability in Cohort Study Data}, journal = {Proceedings of the International Workshop on Vision, Modeling and Visualization}, year = {2013}, pages = {121-128}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/klemm_et_al_13a.pdf}, author = {P. Klemm and K. Lawonn and M. Rak and B. Preim and K. D. T{\"o}nnies and K. Hegenscheid and H. V{\"o}lzke and S. Oeltze} } @proceedings {404, title = {A Visualization Approach for Cross-level Exploration of Spatiotemporal Data}, journal = {Proceedings of the International Conference on Knowledge Management and Knowledge Technologies (iKNOW{\textquoteright}13)}, year = {2013}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {H.-J. Schulz and S. Hadlak and H. Schumann} } @proceedings {410, title = {Visualization Support for Multi-criteria Decision Making in Geographic Information Retrieval }, journal = {Availability, Reliability, and Security in Information Systems and HCI }, year = {2013}, pages = {363-375}, publisher = {CD-ARES}, address = {Regensburg}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = { http://visualanalytics.de/sites/default/files/upload/publications/HCI-KDD_ARES13_Kumar.pdf}, author = {C. Kumar and W. Heuten and S. Boll} } @proceedings {313, title = {Visualizing nD Point Clouds as Topological Landscape Profiles to Guide Local Data Analysis}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {19}, year = {2013}, pages = {514{\textendash}526}, publisher = {IEEE TVCG}, edition = {3}, keywords = {[Project Phase 2] Topology-based Visual Analysis of Information Spaces}, url = {http://www.computer.org/csdl/trans/tg/preprint/ttg2012990060-abs.html}, author = {Oesterling, P. and Heine, C. and G. H. Weber and Scheuermann, G.} } @mastersthesis {452, title = {Visuell-interaktiver Vergleich vieler hierarchischer Strukturen}, volume = {M. Sc.}, year = {2013}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, author = {M. He{\ss}} } @proceedings {377, title = {Volumetric Segmentation of Complex Bone Structures from Medical Imaging Data Using Reeb Graphs}, journal = {In proceedings of Central European Seminar on Computer Graphics for Students (CSCG{\textquoteright}2013)}, year = {2013}, pages = {113-120}, keywords = {[Project Phase 2] Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes}, url = {http://visualanalytics.de/sites/default/files/upload/publications/wiens2013-cescg.pdf}, author = {V. Wiens} } @proceedings {402, title = {Web-Based Exploration of Photos with Time and Geospace}, journal = {Web Information Systems and Technologies}, volume = {140}, year = {2013}, pages = {153--166}, publisher = {Springer Berlin Heidelberg}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, isbn = {978-3-642-36607-9}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Nguyen--Web-BasedExplorationofPhotoswithTimeandGeospace--2013.pdf}, author = {D. Nguyen and H. Schumann} } @article {heimerl2012, title = {Visual Classifier Training for Text Document Retrieval}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {18}, number = {12}, year = {2012}, month = {Dec}, pages = {2839-2848}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, issn = {1077-2626}, doi = {10.1109/TVCG.2012.277}, author = {F. Heimerl and S. Koch and H. Bosch and T. Ertl} } @mastersthesis {537, title = {Novel Methods and Applications for the Feature Extraction from Visualizations of Multi-Parameter Data}, volume = {PhD}, year = {2012}, month = {2012}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, author = {Dirk J. Lehmann} } @mastersthesis {538, title = {Studie ueber die Perzeptivitaet von Quality Measures fuer Daten-Visualisierungen hochdimensionaler Daten}, volume = {Diploma}, year = {2012}, month = {2012}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, author = {Sebastian Hundt} } @conference {615, title = {A Data-Driven Approach to Hue-Preserving Color-Blending}, booktitle = {Proceedings of the 19th IEEE Visualization Conference (SCIVIS), IEEE Transactions on Visualization and Computer Graphics 18}, year = {2012}, keywords = {[Project Phase 1] Visually guided exploration of point cloud data in Euclidean space}, author = {L. K{\"u}hne and J. Giesen and Zhiyuan Zhang and Sungsoo Ha and K. Mueller} } @book {283, title = {Active Learning for Coreference Resolution}, series = {HLT-NAACL}, volume = {2012}, year = {2012}, pages = {508--512}, publisher = {The Association for Computational Linguistics}, organization = {The Association for Computational Linguistics}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, url = {http://aclweb.org/anthology-new/N/N12/N12-1055.pdf}, author = {F. Laws and F. Heimerl and H. Sch{\"u}tze} } @article {332, title = {An adaptive simulator for ML-rules}, year = {2012}, pages = {Poster @ Winter Simulation Conference (WSC{\textquoteright}12)}, type = {Poster}, address = {Berlin}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {T. Helms and S. Rybacki and R. Ewald and A. Uhrmacher} } @article {208, title = {Analysing the spatial dimension of eye movement data using a visual analytic approach}, journal = {Expert Systems with Applications, 2012, v.39 (1)}, year = {2012}, pages = {1324-1332}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, doi = {dx.doi.org/10.1016/j.eswa.2011.08.013}, author = {K. Ooms and G. Andrienko and N. Andrienko and P. Da Maeyer and V. Fack} } @proceedings {595, title = {ASV Monitor: Creating Comparability of Machine Learning Methods for Content Analysis}, journal = {ECML-PKDD 2012}, year = {2012}, publisher = {Springer}, keywords = {[Project Phase 2] Topology-based Visual Analysis of Information Spaces}, url = {http://visualanalytics.de/sites/default/files/upload/publications/2012-ASV_Monitor.pdf}, author = {Andreas Niekler and Patrick J{\"a}hnichen and Gerhard Heyer} } @inbook {263, title = {Auditory Support for Situation Awareness in Video Surveillance}, booktitle = {In Proceedings of the International Conference on Auditory Display (ICAD)}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2012b.pdf}, author = {B. H{\"o}ferlin and M. H{\"o}ferlin and B. Goloubets and G. Heidemann and D. Weiskopf} } @proceedings {334, title = {Automatic Detection and Visualization of Qualitative Hemodynamic Characteristics in Cerebral Aneurysms}, journal = {IEEE Transactions on Visualization and Computer Graphics}, year = {2012}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, url = {http://wwwisg.cs.uni-magdeburg.de/visual/files/publications/2012/GaststeigerLehmann_2012_VIS.pdf}, author = {R. Gasteiger and D. J. Lehmann and R. van Pelt and G. Janiga and O. Beuing and A. Vilanova and H. Theisel and B. Preim} } @article {336, title = {Automating Transfer Function Design with Valley Cell-Based Clustering of 2D Density Plots}, journal = {Computer Graphics Forum (In Proc. EuroVis 2012)}, year = {2012}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/WangZhangLehmann_2012_CGF2.pdf}, author = {Y. Wang and J. Zhang and D. J. Lehmann and H. Theisel and X. Chi} } @mastersthesis {448, title = {Beispielbasierte Finite Elemente Deformation}, volume = {B. Sc.}, year = {2012}, keywords = {[Project Phase 2] Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes}, author = {S. Krumpen} } @proceedings {307, title = {ClustNails: Visual Analysis of Subspace Clusters}, journal = {Tsinghua Science and Technology, Special Issue on Visualization and Computer Graphics}, volume = {17(4)}, year = {2012}, pages = {419-428}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging, [Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {A. Tatu and L. Zhang and E. Bertini and T. Schreck and D.A. Keim and S. Bremm and T. von Landesberger} } @article {231, title = {Constructing and Visualizing Chemical Reaction Networks from Pi-Calculus Models}, journal = {to appear in Formal Aspects of Computing}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. John and H.-J. Schulz and H. Schumann and A. Uhrmacher and A. Unger} } @proceedings {292, title = {Correlation-based Arrangement of Time Series for Movement Analysis in Behavioural Ecology}, journal = {Progress on Movement Analysis Workshop}, year = {2012}, address = {Zurich}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, author = {Mansmann, F. and D. Spretke and H. Janetzko and B. Kranstauber and K. Safi} } @mastersthesis {443, title = {Effiziente Visualisierung grosser Microarraydaten}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {J. Glaser} } @mastersthesis {441, title = {Einsatz von Visualisierungsmethoden zur {\"U}berpr{\"u}fung von strukturver{\"a}nderlichen Simulationen}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {J. Glaser} } @article {284, title = {An Environmental Search Engine based on Interactive Visual Classification}, journal = {ACM International Workshop on Multimedia Analysis for Ecological Data (MAED 2012)}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {S. Vrochidis and H. Bosch and A. Moumtzidou and F. Heimerl and T. Ertl and Y. Kompatsiaris} } @mastersthesis {Podlech_2012_thesis, title = {Erprobung, Weiterentwicklung und Vergleich von Clusteringtechniken f{\"u}r die visuelle Analyse von Tumorherden}, volume = {M.Sc.}, year = {2012}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, author = {Sandra Podlech} } @article {291, title = {Evaluation of Fast-Forward Video Visualization}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {18}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2012e.pdf}, author = {M. H{\"o}ferlin and K. Kurzhals and B. H{\"o}ferlin and G. Heidemann and D. Weiskopf} } @mastersthesis {430, title = {Fast-Forward Video Visualization}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {K. Kurzhals} } @proceedings {282, title = {Feature-based visual analysis of interesting data segments in large group movement data}, journal = {GIScience workshop on GeoVisual Analytics}, year = {2012}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, url = {http://visualanalytics.de/sites/default/files/upload/publications/geovat2012optimized.pdf}, author = {S. Bremm and T. von Landesberger and T. Schreck and D. Fellner} } @mastersthesis {442, title = {Feature-basierte Visualisierung der Next-Subvolume Methode}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {C. Eichner} } @proceedings {365, title = {FeatureForge: A Novel Tool for Visually Supported Feature Engineering and Corpus Revision}, journal = {Proceedings of COLING 2012}, year = {2012}, pages = {461-470}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, url = {http://visualanalytics.de/sites/default/files/upload/publications/C12-2046.pdf}, author = {F. Heimerl and C. Jochim and S. Koch and T. Ertl} } @proceedings {294, title = {Getting There First: Real-Time Detection of Real-World Incidents on Twitter}, journal = {2nd IEEE Workshop on Interactive Visual Text Analytics {\textquotedblright}Task-Driven Analysis of Social Media{\textquotedblright} as part of the IEEE VisWeek 2012}, year = {2012}, address = {Seattle, Washington, USA}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://bib.dbvis.de/uploadedFiles/submission_webpage.pdf}, author = {M. Krstajic and C. Rohrdantz and M. Hund and A. Weiler} } @mastersthesis {439, title = {Graph-based Visualization of Heterogeneous Information Landscapes}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {G. Tshagharyan} } @proceedings {322, title = {The Great Wall of Space-Time}, journal = {Proceedings of the 17th International Workshop on Vision, Modeling and Visualization (VMV{\textquoteright}12)}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {C. Tominski and H.-J. Schulz} } @proceedings {316, title = {Heterogeneity-based guidance for exploring multiscale data in Systems Biology}, journal = {Proceedings of the IEEE Symposium on Biological Data Visualization (BioVis{\textquoteright}12)}, year = {2012}, address = {Seattle, USA}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Luboschik and C. Maus and H.-J. Schulz and H. Schumann and A. Uhrmacher} } @article {472, title = {Heterogeneity-based Guidance for Exploring Multiscale Data in Systems Biology}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Luboschik--Heterogeneity-basedGuidanceforExploringMultiscaleDatainSystemsBiology--2012.pdf}, author = {M. Luboschik and C. Maus and H.-J. Schulz and H. Schumann and A. Uhrmacher} } @proceedings {287, title = {HIVEBEAT - A Highly Interactive Visualization Environment for Broad-Scale Exploratory Analysis and Tracing}, journal = {2012 IEEE Conference on Visual Analytics Science and Technology (VAST)}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {R. Kr{\"u}ger and H. Bosch and S. Koch and C. M{\"u}ller and G. Reina and D. Thom and T. Ertl} } @proceedings {270, title = {Identifying Place Histories from Activity Traces with an Eye to Parameter Impact}, journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)}, volume = {v.18 (5)}, year = {2012}, pages = {675-688}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1109/TVCG.2011.153}, author = {G. Andrienko and N. Andrienko and M. Mladenov and M. Mock and C. Poelitz} } @proceedings {290, title = {Inter-Active Learning of Ad-Hoc Classifiers for Video Visual Analytics}, journal = {IEEE Conference on Visual Analytics Science and Technology (VAST)}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2012d.pdf}, author = {B. H{\"o}ferlin and R. Netzel and M. H{\"o}ferlin and D. Weiskopf and G. Heidemann} } @proceedings {326, title = {Interaction Support for Visual Comparison Inspired by Natural Behavior}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {18(12)}, year = {2012}, pages = {2719--2728}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {C. Tominski and C. Forsell and J. Johansson} } @inbook {261, title = {Interaction Taxonomy for Tracking of User Actions in Visual Analytics Applications}, booktitle = {Human centric visualization}, year = {2012}, publisher = {Springer}, organization = {Springer}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, url = {http://visualanalytics.de/sites/default/files/upload/publications/HCV2012landesberger.pdf}, author = {T. von Landesberger and S. Fiebig and S. Bremm and A. Kuijper and D. Fellner} } @proceedings {275, title = {Interactive exploration of events and presence of people in space and time through KD-photomap}, journal = {AVI{\textquoteright}12, Proceedings of the International Working Conference on Advanced Visual Interfaces}, year = {2012}, pages = {804-805}, publisher = {ACM Press}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1145/2254556.2254723}, author = {K. Vrotsou and H. Zhi and I. Peca and G. Andrienko and N. Andrienko} } @mastersthesis {431, title = {Interactive Learning}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {R. Netzel} } @proceedings {342, title = {Interactive Steering of Mesh Animations}, journal = {In proceedings of 2012 ACM SIGGRAPH/Eurographics Symposium on Computer Animation}, year = {2012}, address = {Lausanne, Switzerland}, keywords = {[Project Phase 2] Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes}, url = {http://visualanalytics.de/sites/default/files/upload/publications/voegele_SCA2012-steering_mesh_animations.pdf}, author = {A. V{\"o}gele and M. Hermann and B. Kr{\"u}ger and R. Klein} } @proceedings {317, title = {Interactive Visual Exploration of Simulator Accuracy: A Case Study for Stochastic Simulation Algorithms}, journal = {Proceedings of the Winter Simulation Conference (WSC{\textquoteright}2012)}, year = {2012}, address = {Berlin}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Luboschik and S. Rybacki and R. Ewald and B. Schwarze and H. Schumann and A. Uhrmacher} } @inbook {262, title = {Learning a Visual Attention Model for Adaptive Fast-Forward in Video Surveillance}, booktitle = {Proceedings of International Conference on Pattern Recognition Applications and Methods (ICPRAM)}, volume = {2}, year = {2012}, pages = {25--32}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, doi = {10.5220/0003720000250032}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2012a.pdf}, author = {B. H{\"o}ferlin and H. Pfl{\"u}ger and M. H{\"o}ferlin and G. Heidemann and D. Weiskopf} } @proceedings {256, title = {LocateThisPage: Drive-by Location-Aware Browsing}, journal = {GI Zeitgeist Young researchers forum on Geographic Information Science 2012(GI Zeitgeist-12)}, year = {2012}, address = {Munster, Germany}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/KumarAhlersBoll2012LocateThisPage.pdf}, author = {C. Kumar and D. Ahlers and S. Boll} } @proceedings {259, title = {Mapping the Web resources of a developing country}, journal = {GI Zeitgeist Young researchers forum on Geographic Information Science 2012(GI Zeitgeist-12)}, year = {2012}, address = {Munster, Germany}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/GI2012MappingWebResources.pdf}, author = {D. Ahlers and J. Matute and I. Martinez and C. Kumar} } @proceedings {594, title = {Matching Results of Latent Dirichlet Allocation for Text}, journal = {Proceedings of ICCM 2012, 11th International Conference on Cognitive Modeling}, year = {2012}, pages = {317{\textendash}322}, publisher = {Universit{\"a}tsverlag der TU Berlin}, keywords = {[Project Phase 2] Topology-based Visual Analysis of Information Spaces}, url = {http://visualanalytics.de/sites/default/files/upload/publications/2012-Matching_Results_of_Latent_Dirichlet_Allocation_for_Text.pdf}, author = {Andreas Niekler and Patrick J{\"a}hnichen} } @article {304, title = {miRTrail - a comprehensive webserver for analyzing gene and miRNA patterns to enhance the understanding of regulatory mechanisms in diseases. BMC Bioinformatics}, journal = {BMC Bioinformatics}, volume = {13(1):36}, year = {2012}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, author = {C. Laczny and P. Leidinger and J. Haas and N. Ludwig and C. Backes and A. Gerasch and M. Kaufmann and B. Vogel and H.-A. Katus and B. Meder and C. Stahler and E. Meese and H.-P. Lenhof and A. Keller} } @proceedings {320, title = {Model-Driven Design for the Visual Analysis of Heterogeneous Data}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {18(6)}, year = {2012}, pages = {998--1010}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Streit and H.-J. Schulz and A. Lex and D. Schmalstieg and H. Schumann} } @proceedings {339, title = {Motion compensation of ultrasonic perfusion images}, journal = {Medical Imaging 2012: Ultrasonic Imaging, Tomography, and Therapy}, year = {2012}, publisher = {SPIE}, address = {San Diego, California, USA}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, doi = {10.1117/12.911236}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Schaefer_2012_SPIE.pdf}, author = {S. Sch{\"a}fer and K. Nylund and O.H. Gilja and K. D. T{\"o}nnies}, editor = {J.G. Bosch and M.M. Doyley} } @proceedings {309, title = {Multi-view clustering using mixture models in subspace projections}, journal = {Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD{\textquoteright}12)}, year = {2012}, pages = {132-140}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {S. G{\"u}nnemann and I. F{\"a}rber and T. Seidl} } @article {385, title = {No longer confidential: Estimating the Confidence of Individual Regression Predictions}, journal = {PLoS One}, year = {2012}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Briesemeister et al., 2012.pdf}, author = {S. Briesemeister and J. Rahnenf{\"u}hrer and O. Kohlbacher} } @proceedings {260, title = {PCDC - On the Highway to Data - A Tool for the Fast Generation of Large Synthetic Data Sets}, journal = {International Workshop on Visual Analytics (EuroVA)}, year = {2012}, pages = {7-11}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, url = {http://visualanalytics.de/sites/default/files/upload/publications/007-011.pdf}, author = {S. Bremm and T. von Landesberger and M. He{\ss} and D. Fellner} } @proceedings {288, title = {Preliminary study of technical terminology for the retrieval of scientific book metadata records}, journal = {Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval}, year = {2012}, pages = {1131--1132}, publisher = {ACM}, address = {Portland, Oregon, USA}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, isbn = {978-1-4503-1472-5}, doi = {10.1145/2348283.2348504}, author = {B. Larsen and C. Lioma and I. Frommholz and H. Sch{\"u}tze} } @proceedings {276, title = {Privacy Issues in Geospatial Visual Analytics}, journal = {Advances in Location-Based Services, Lecture Notes in Geoinformation and Cartography}, year = {2012}, pages = {239-246}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1007/978-3-642-24198-7_16}, author = {G. Andrienko and N. Andrienko} } @mastersthesis {420, title = {Projected Spectral Clustering on Graphs with Feature Vectors}, volume = {Master of Science}, year = {2012}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {S. Raubach} } @proceedings {295, title = {Proportions in Categorical and Geographic Data: Visualizing the Results of Political Elections.}, journal = {Proceedings of the AVI 2012, May 21 - 25,}, year = {2012}, publisher = {ACM Press}, address = {Capri Island (Naples)}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://bib.dbvis.de/uploadedFiles/submission.pdf}, author = {F. Stoffel and H. Janetzko and Mansmann, F.} } @proceedings {340, title = {Registration of Temporal Ultrasonic Image Sequences Using Markov Random Fields}, journal = {VMV 2012 - Vision, Modeling and Visualization}, year = {2012}, pages = {151--166}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Schaefer_2012_VMV.pdf}, author = {S. Sch{\"a}fer and K. D. T{\"o}nnies} } @proceedings {277, title = {Scalable Cluster Analysis of Spatial Events}, journal = {International Workshop on Visual Analytics (2012) EuroGraphics}, year = {2012}, pages = {19-23}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.2312/PE/EuroVAST/EuroVA12/019-023}, author = {I. Peca and G. Fuchs and K. Vrotsou and N. Andrienko and G. Andrienko} } @article {335, title = {Selecting Coherent and Relevant Plots in Large Scatterplot Matrices}, journal = {Computer Graphics Forum}, year = {2012}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Lehmann_2012_CGF.pdf}, author = {D. J. Lehmann and G. Albuquerque and M. Eisemann and M. Magnor and H. Theisel} } @article {274, title = {Semantic Trajectories Modeling and Analysis}, journal = {ACM Computing Surveys}, year = {2012}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, author = {C. Parent and S. Spaccapietra and C. Renso and G. Andrienko and N. Andrienko and V. Bogorny and M. L. Damiani and A. Gkoulalas-divanis and J. Macedo and N. Pelekis and Y. Theodoridis and Z. Yan} } @booklet {Albuquerque2012SAC, title = {Semi-Automatic Classification of Weather Maps}, number = {17}, year = {2012}, publisher = {Computer Graphics Lab, {TU} Braunschweig}, keywords = {[Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, author = {Albuquerque, Georgia and D. J. Lehmann and Rodermund, Torben and Eisemann, Martin and Nocke, Thomas and Theisel, Holger and Magnor, Marcus} } @mastersthesis {432, title = {Skizzenbasierte Trajektoriensuche in Videos}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {J. Engelhardt} } @proceedings {286, title = {Spatiotemporal Anomaly Detection through Visual Analysis of Geolocated Twitter Messages}, journal = {IEEE Pacific Visualization Symposium (PacificVis)}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {D. Thom and H. Bosch and S. Koch and M. W{\"o}rner and T. Ertl} } @proceedings {321, title = {Stacking-Based Visualization of Trajectory Attribute Data}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {18(12)}, year = {2012}, pages = {2565--2574}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {C. Tominski and H. Schumann and G. Andrienko and N. Andrienko} } @article {266, title = {State of the Art Report on Video-based Graphics and Video Visualizations}, journal = {Computer Graphics Forum}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {R. Borgo and M. Chen and B. Daubney and E. Grundy and G. Heidemann and B. H{\"o}ferlin and M. H{\"o}ferlin and H. J{\"a}nicke and D. Weiskopf and X. Xie} } @article {324, title = {StratomeX: Visual Analysis of Large-Scale Heterogeneous Genomics Data for Cancer Subtype Characterization}, journal = {Computer Graphics Forum}, volume = {31(3)}, year = {2012}, pages = {1175--1184}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {A. Lex and M. Streit and H.-J. Schulz and C. Partl and D. Schmalstieg and P.J. Park and N. Gehlenborg} } @article {333, title = {Streaming data management for the online processing of simulation data}, year = {2012}, pages = {Poster @ Winter Simulation Conference (WSC{\textquoteright}12)}, type = {Poster}, address = {Berlin}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {J. Sch{\"u}tzel and J. Himmelspach and H. Meyer and A. Heuer and A. Uhrmacher} } @article {315, title = {Studying the role of lipid rafts on protein-receptor bindings with Cellular Automata}, journal = {To Appear in IEEE/ACM Trans. Comput. Biol. Bioinformatics}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {F. Haack and K. Burrage and R. Redmer and A. Uhrmacher} } @proceedings {310, title = {Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data}, journal = {Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD{\textquoteright}12)}, year = {2012}, pages = {352-360}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {S. G{\"u}nnemann and I. F{\"a}rber and K. Virochsiri and T. Seidl} } @proceedings {306, title = {Subspace Search and Visualization to Make Sense of Alternative Clusterings in High-Dimensional Data}, journal = {Procedings of IEEE Symposium on Visual Analytics Science and Technology (VAST)}, year = {2012}, pages = {63-72}, publisher = {IEEE CS Press}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {A. Tatu and F. Maa{\ss} and I. F{\"a}rber and E. Bertini and T. Schreck and T. Seidl and D.A. Keim} } @proceedings {318, title = {Supporting Visual Analysis in Smart Meeting Rooms}, journal = {Proceedings of the EuroVis Workshop on Visual Analytics (EuroVA{\textquoteright}12)}, year = {2012}, address = {Wien}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {A. Radloff and G. Fuchs and H. Schumann} } @proceedings {308, title = {A Taxonomy of Visual Cluster Separation Factors}, journal = {Computer Graphics Forum (Proc. EuroVis 2012)}, volume = {31(3)}, year = {2012}, pages = {1335-1344}, keywords = {[Project Phase 2] Visual Analytics methods to steer the subspace clustering process}, author = {M. Sedlmair and A. Tatu and T. Munzner and M. Tory} } @proceedings {330, title = {Template and Frame based Experiment Workflows in Modeling and Simulation Software with WORMS}, journal = {Seventh IEEE 2012 World Congress on Services - Sixth International Workshop on Scientific and Engineering Workflows: Advances in Data and Event-Driven Workflows}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {S. Rybacki and S. Leye and J. Himmelspach and A. Uhrmacher} } @proceedings {329, title = {Toward a language for the flexible observation of simulations}, journal = {Proc. of the Winter Simulation Conference (WSC{\textquoteright}12)}, year = {2012}, address = {Berlin}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {T. Helms and J. Himmelspach and C. Maus and O. R{\"o}wer and J. Sch{\"u}tzel and A. Uhrmacher} } @proceedings {367, title = {Towards a Generic and Flexible Citation Classifier Based on a Faceted Classification Scheme}, journal = {Proceedings of COLING 2012}, year = {2012}, pages = {1343-1358}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, url = {http://visualanalytics.de/sites/default/files/upload/publications/C12-1082.pdf}, author = {C. Jochim and H. Sch{\"u}tze} } @proceedings {325, title = {Towards Interactive Visual Analysis of Microscopic-Level Simulation Data}, journal = {Proceedings of the Annual SIGRAD Conference, Special Theme: Interactive Visual Analysis of Data}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Luboschik and C. Tominski and A.T. Bittig and A. Uhrmacher and H. Schumann} } @proceedings {331, title = {Using workflows to control the experiment execution in M\&S Software}, journal = {Proceedings of the 5th SimuTools conference}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {S. Rybacki and J. Himmelspach and A. Uhrmacher} } @proceedings {289, title = {Visual Analysis of Geo-Social Web for Spatial Decision Support}, journal = {Workshop on Interactive Visual Text Analytics at VisWeek}, year = {2012}, address = {Seattle, USA}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Kumar_VTA_12.pdf}, author = {C. Kumar and W. Heuten and S. Boll} } @proceedings {319, title = {Visual Analysis of Spatiotemporal Multilevel Data}, journal = {Proceedings of the Workshop GeoVA(t) - Geospatial Visual Analytics: Focus on Time}, year = {2012}, address = {Columbus OH, USA}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {R. Rosenbaum and H.-J. Schulz and S. Hadlak and H. Schumann} } @proceedings {267, title = {Visual Analytics for Dynamic Evacuation Planning}, journal = {International Workshop on Visual Analytics (EuroVA)}, year = {2012}, pages = {13--17}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Reddy2012.pdf}, author = {R. Reddy and M. H{\"o}ferlin and M. Dambier and D. Weiskopf} } @proceedings {272, title = {Visual Analytics for Understanding Spatial Situations from Episodic Movement Data}, journal = {K{\"u}nstliche Intelligenz}, year = {2012}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1007/s13218-012-0177-4}, author = {N. Andrienko and G. Andrienko and H. Stange and T. Liebig and D. Hecker} } @article {299, title = {Visual Analytics Methodology for Eye Movement Studies}, journal = {IEEE Transactions on Visualization and Computer Graphics (Proceedings IEEE VAST 2012)}, volume = {vol. 18(12)}, year = {2012}, pages = {2889-2898}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1109/TVCG.2012.276}, author = {G. Andrienko and N. Andrienko and M. Burch and D. Weiskopf} } @proceedings {281, title = {Visual Analytics Methods for Categoric Spatio-Temporal Data}, journal = {VisWeek Vast}, year = {2012}, keywords = {[Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, url = {http://visualanalytics.de/sites/default/files/upload/publications/paper162final.pdf}, author = {T. von Landesberger and S. Bremm and N. Andrienko and G. Andrienko and M. Tekusova} } @conference {303, title = {Visual Analytics Methods for Categoric Spatio-Temporal Data}, booktitle = {IEEE Visual Analytics Science and Technology (VAST 2012) Proceedings}, year = {2012}, publisher = {IEEE Computer Society Press}, organization = {IEEE Computer Society Press}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, author = {T. von Landesberger and S. Bremm and N. Andrienko and G. Andrienko and M. Tekusova} } @proceedings {265, title = {Visual Analytics of Mobile Data}, journal = {Proceedings of the Nokia Mobile Data Challenge 2012 Workshop}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2012c.pdf}, author = {B. H{\"o}ferlin and M. H{\"o}ferlin and J. R{\"a}uchle} } @mastersthesis {368, title = {Visual Search and analysis of documents in the intellectual property domain}, year = {2012}, school = {Universit{\"a}t Stuttgart}, keywords = {[Project Phase 2] Scalable Visual Analysis of Patent and Scientific Document Collections}, author = {S. Koch} } @proceedings {423, title = {Visualization and Exploration of Shape Variance for the Analysis of Cohort Study Data}, journal = {VMV 2012 - Vision, Modeling and Visualization}, year = {2012}, pages = {221--222}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Visualization and Exploration of Shape Variance for the Analysis of Cohort Study Data.pdf}, author = {P. Klemm and S. Oeltze and K. Hegenscheid and H. V{\"o}lzke and K. D. T{\"o}nnies and B. Preim} } @mastersthesis {440, title = {Visualization of the Primary and Secondary Source Information of data sets}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Melkonyan} } @proceedings {314, title = {Visualizing Uncertainty in Biological Expression Data}, journal = {Proceedings of the Conference on Visualization and Data Analysis (VDA{\textquoteright}12)}, year = {2012}, address = {Francisco, USA}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {C. Holzh{\"u}ter and A. Lex and D. Schmalstieg and H.-J. Schulz and H. Schumann and M. Streit} } @article {207, title = {Visually Exploring Movement Data via Similarity-based Analysis}, journal = {Journal of Intelligent Information Systems}, year = {2012}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, doi = {http://dx.doi.org/10.1007/s10844-011-0159-2}, author = {N. Pelekis and G. Andrienko and N. Andrienko and I. Kopanakis and G. Marketos and Y. Theodoridis} } @article {271, title = {Visually Exploring Movement Data via Similarity-based Analysis}, journal = {Journal of Intelligent Information Systems}, volume = {v.38 (2)}, year = {2012}, pages = {343-391}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, doi = {http://dx.doi.org/10.1007/s10844-011-0159-2}, author = {N. Pelekis and G. Andrienko and N. Andrienko and I. Kopanakis and G. Marketos and Y. Theodoridis} } @mastersthesis {433, title = {Visuelle Analyse mobiler Daten}, year = {2012}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, author = {J. R{\"a}uchle} } @proceedings {323, title = {A Wall-Like Visualization of Spatio-Temporal Data}, journal = {Proceedings of the Workshop GeoVA(t) - Geospatial Visual Analytics: Focus on Time}, year = {2012}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {C. Tominski and H.-J. Schulz} } @proceedings {293, title = {What{\textquoteright}s Going On? How Twitter and Online News Can Work in Synergy to Increase Situational Awareness}, journal = {2nd IEEE Workshop on Interactive Visual Text Analytics {\textquotedblright}Task-Driven Analysis of Social Media{\textquotedblright} as part of the IEEE VisWeek 2012}, year = {2012}, address = {Seattle, Washington, USA}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://bib.dbvis.de/uploadedFiles/1_submission_webpage.pdf}, author = {C. Rohrdantz and M. Krstajic and M. El-Assady and D.A. Keim} } @article {koch2011, title = {Iterative Integration of Visual Insights during Scalable Patent Search and Analysis}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {17}, number = {5}, year = {2011}, month = {May}, pages = {557-569}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, issn = {1077-2626}, doi = {10.1109/TVCG.2010.85}, author = {S. Koch and H. Bosch and M. Giereth and T. Ertl} } @mastersthesis {539, title = {Uebersicht, Gegenueberstellung und Bewertung der Analyseregeln von Datenvisualisierungen hochdimensionaler Datensaetze}, volume = {Diploma}, year = {2011}, month = {2011}, keywords = {[Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, author = {Marco Kirschke} } @article {480, title = {Analytical, Visual, and Interactive Concepts for Geo-Visual Analytics}, journal = {Journal of Visual Languages \& Computing}, year = {2011}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Schumann--AnalyticalVisualandInteractiveConceptsforGeo-VisualAnalytics--2011.pdf}, author = {H. Schumann and C. Tominski} } @article {234, title = {Analytical, Visual, and Interactive Concepts for Geo-Visual Analytics.}, journal = {Visual Languages \& Computing}, volume = {Vol. 22, No. 4}, year = {2011}, pages = {pp.257-267}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Schumann11GeoVA.pdf}, author = {H. Schumann and C. Tominski} } @article {195, title = {Assisted Descriptor Selection Based on Visual Comparative Data Analysis}, journal = {Wiley-Blackwell Computer Graphics Forum, Proceedings of Eurographics/IEEE-VGTC Symposium on Visualization 2011. To appear.}, year = {2011}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/ComparativeFeatureAnalysis.pdf}, author = {S. Bremm and T. von Landesberger and J. Bernard and T. Schreck} } @proceedings {121, title = {Automated Analytical Methods to Support Visual Exploration of High-Dimensional Data}, journal = {IEEE Trans. Visualization and Computer Graphics}, year = {2011}, keywords = {[Project Phase 1] Coordination Project, [Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Tatu10AAM.pdf}, author = {A. Tatu and G. Albuquerque and M. Eisemann and P. Bak and H. Theisel and M. Magnor and D.A. Keim} } @article {386, title = {Bioinformatics for Qualitative and Quantitative Proteomics}, journal = {Bioinformatics for Omics Data: Methods and Protocols}, year = {2011}, pages = {1-19}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Bielow et al., 2011, Bioinformatics for Omics Data}, author = {C. Bielow and C. Gr{\"o}pl and O. Kohlbacher and K. Reinert} } @article {279, title = {Challenging Problems in Geovisual Analytics}, journal = {Visual Languages and Computing}, year = {2011}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, issn = {1045-926X}, doi = {http://dx.doi.org/10.1016/j.jvlc.2011.04.001}, author = {G. Andrienko and N. Andrienko and D.A. Keim and A. MacEachren and S. Wrobel} } @article {211, title = {Challenging Problems of Geospatial Visual Analytics}, journal = {Journal of Visual Languages and Computing}, volume = {v.22 (4)}, year = {2011}, pages = {251-256}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, doi = {http://dx.doi.org/10.1016/j.jvlc.2011.04.001}, author = {G. Andrienko and N. Andrienko and D.A. Keim and A. MacEachren and S. Wrobel} } @proceedings {224, title = {A Clustering-based Visualization Technique to Emphasize Meaningful Regions of Vector Fields}, journal = {Proc. VMV}, year = {2011}, keywords = {[Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, author = {A. Kuhn and D. J. Lehmann and R. Gaststeiger and M. Neugebauer and B. Preim and H. Theisel} } @article {212, title = {Composite Density Maps for Multivariate Trajectories}, journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)}, volume = {v.17 (12)}, year = {2011}, pages = {2518-2527}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2011.181}, author = {R. Scheepens and N. Willems and H. van de Wetering and G. Andrienko and N. Andrienko and J. vanWijk} } @article {201, title = {Computer-Aided Diagnosis in Breast DCE-MRI - Quantification of the Heterogeneity of Breast Lesions}, journal = {European Journal of Radiology}, year = {2011}, keywords = {[Project Phase 1] Efficient Visual Analysis of Dynamic Medical Image Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Computer-Aided Diagnosis in Breast DCE-MRI - Quantification of the Heterogeneity of Breast Lesions.pdf}, author = {U. Preim and S. Gla{\ss}er and B. Preim and F. Fischbach and J. Ricke} } @article {210, title = {A Conceptual Framework and Taxonomy of Techniques for Analyzing Movement}, journal = {Journal of Visual Languages and Computing}, volume = {v.22 (3)}, year = {2011}, pages = {213-232}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = {http://dx.doi.org/10.1016/j.jvlc.2011.02.003}, author = {G. Andrienko and N. Andrienko and P. Bak and D.A. Keim and S. Kisilevich and S. Wrobel} } @proceedings {192, title = {Data Driven Color Mapping}, journal = {Proc. EuroVA 2011}, year = {2011}, address = {Bergen, Norway}, keywords = {[Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Eisemann11DDC.pdf}, author = {M. Eisemann and G. Albuquerque and M. Magnor} } @proceedings {186, title = {Deformable Registration of Differently-weighted Breast Magnetic Resonance Images}, journal = {Bildverarbeitung f{\"u}r die Medizin}, year = {2011}, keywords = {[Project Phase 1] Efficient Visual Analysis of Dynamic Medical Image Data}, author = {T. B{\"o}hler and S. Gla{\ss}er and H.-O. Peitgen} } @inbook {178, title = {Developing Analytical GIS Applications with GEO-SPADE: Three Success Case Studies (to appear)}, year = {2011}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and D.A. Keim and A. Lasry and L. Bam and L. Rokach} } @proceedings {193, title = {Directed Image Search with Local Parallel Feature Axes}, journal = {The Second Workshop on Visual Content Identification and Search}, year = {2011}, keywords = {[Project Phase 1] Zoomable Cell}, author = {S. Gumhold and M. Spehr} } @proceedings {219, title = {Dynamic Time Transformations for Visualizing Multiple Trajectories in Interactive Space-Time Cube}, journal = {International Cartographic Conference (ICC 2011)}, year = {2011}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko} } @proceedings {151, title = {EdgeAnalyzer: Exploratory Analysis through Advanced Edge Interaction}, journal = {HICCS}, year = {2011}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/HICSS2011.pdf}, author = {A. Panagiotidis and H. Bosch and S. Koch and T. Ertl} } @mastersthesis {446, title = {Effiziente Motivsuche f{\"u}r die interaktive Analyse von Graphen}, year = {2011}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {C. Eichner} } @proceedings {190, title = {Evaluation of Background Subtraction Techniques for Video Surveillance}, journal = {Computer Vision and Pattern Recognition (CVPR), IEEE}, year = {2011}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Brutzer2011.pdf}, author = {S. Brutzer and B. H{\"o}ferlin and G. Heidemann} } @article {264, title = {Evaluation of Traditional, Orthogonal, and Radial Tree Diagrams by an Eye Tracking Study}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {17}, year = {2011}, pages = {2440--2448}, keywords = {[Project Phase 2] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Burch2011c.pdf}, author = {M. Burch and J. Heinrich and N. Konevtsova and M. H{\"o}ferlin and D. Weiskopf} } @article {209, title = {An Event-Based Conceptual Model for Context-Aware Movement Analysis}, journal = {International Journal Geographical Information Science}, volume = {v.25 (9)}, year = {2011}, pages = {1347-1370}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, doi = {http://www.tandfonline.com/doi/abs/10.1080/13658816.2011.556120}, author = {G. Andrienko and N. Andrienko and M. Heurich} } @proceedings {200, title = {Expanding queries with term and phrase translations in patent retrieval}, journal = {IRFC}, year = {2011}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, author = {C. Jochim and C. Lioma and H. Sch{\"u}tze} } @proceedings {296, title = {Exploration through Enrichment: A Visual Analytics Approach for Animal Movement}, journal = {Proceedings of the 19th SIGSPATIAL International Conference on Advances in Geographic Information Systems}, year = {2011}, pages = {421--424}, publisher = {ACM}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://bib.dbvis.de/uploadedFiles/355.pdf}, author = {D. Spretke and H. Janetzko and Mansmann, F. and P. Bak and B. Kranstauber and S. Davidson and M. Mueller} } @proceedings {217, title = {Exploring City Structure from Georeferenced Photos Using Graph Centrality Measures}, journal = {Machine Learning and Knowledge Discovery in Databases (PKDD 2011)}, volume = {6913}, year = {2011}, pages = {654-657}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, doi = {http://dx.doi.org/10.1007/978-3-642-23808-6_50}, author = {K. Vrotsou and N. Andrienko and G. Andrienko and P. Jankowski} } @proceedings {216, title = {Exploring Spatiotemporal Patterns By Integrating Visual Analytics With A Moving Objects Database System}, journal = {ACM GIS 2011 - Proceedings of 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2011)}, year = {2011}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {M. Sakr and T. Behr and R. H. G{\"u}ting and G. Andrienko and N. Andrienko and C. Hurter} } @article {237, title = {Exploring the Performance of Spatial Stochastic Simulation Algorithms}, journal = {Journal of Computational Physics}, year = {2011}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {M. Jeschke and R. Ewald and A. Uhrmacher} } @proceedings {223, title = {Features in Continuous Parallel Coordinates}, journal = {IEEE Transactions on Visualization and Computer Graphics (and In Proc. IEEE Visualization)}, year = {2011}, keywords = {[Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, author = {D. J. Lehmann and H. Theisel} } @proceedings {184, title = {The File-Card-Browser View for Breast DCE-MRI Data}, journal = {Bildverarbeitung f{\"u}r die Medizin (accepted for publication)}, year = {2011}, keywords = {[Project Phase 1] Efficient Visual Analysis of Dynamic Medical Image Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/The File-Card-Browser View for Breast DCE-MRI Data.pdf}, author = {S. Gla{\ss}er and U. Preim and S. Oeltze and B. Preim} } @proceedings {214, title = {From Movement Tracks through Events to Places: Extracting and Characterizing Significant Places from Mobility Data (best paper award)}, journal = {IEEE Visual Analytics Science and Technology (VAST 2011) Proceedings}, year = {2011}, pages = {161-170}, publisher = {IEEE Computer Society Press}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko and C. Hurter and S. Rinzivillo and S. Wrobel} } @article {278, title = {GeoViz {\textendash} Linking Geovisualization with Spatial Analysis and Modelling}, journal = {Cartographica}, volume = { v.46 (4)}, year = {2011}, pages = {209-261}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, issn = {1045-926X}, url = {http://utpjournals.metapress.com/content/w3071444v272}, author = {G. Andrienko and J. Dykes and B. Jiang and J. Schiewe} } @article {327, title = {In Situ Exploration of Large Dynamic Networks}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {17}, year = {2011}, pages = {2334--2343}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {S. Hadlak and H.-J. Schulz and H. Schumann} } @article {305, title = {An integer linear programming approach for finding deregulated subgraphs in regulatory networks}, journal = {Nucleic Acids Res}, volume = {40(6):e43}, year = {2011}, keywords = {[Project Phase 2] Network-based interactive navigation and analysis of large biological datasets}, url = {http://www.ncbi.nlm.nih.gov/pubmed/22210863}, author = {C. Backes and A. Rurainski and G. Klau and O. M{\"u}ller and D. St{\"o}ckel and A. Gerasch and J. K{\"u}ntzer and D. Maisel and N. Ludwig and M. Hein and A. Keller and H. Burtscher and M. Kaufmann and E. Meese and H.-P. Lenhof} } @proceedings {194, title = {Interactive Analysis of Object Group Changes over Time}, journal = {EuroVA International Workshop on Visual Analytics}, year = {2011}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/ParallelTimeSets.pdf}, author = {S. Bremm and T. von Landesberger and G. Andrienko and N. Andrienko and T. Schreck} } @proceedings {198, title = {Interactive Auditory Display to Support Situational Awareness in Video Surveillance}, journal = {In Proceedings of the International Conference on Auditory Display (ICAD)}, year = {2011}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2011b.pdf}, author = {B. H{\"o}ferlin and M. H{\"o}ferlin and M. Raschke and G. Heidemann and D. Weiskopf} } @proceedings {229, title = {Interactive Comparison of Multiple Trees}, journal = {IEEE Symposium on Visual Analytics Science and Technology}, year = {2011}, publisher = {IEEE Computer Society}, keywords = {[Project Phase 1] Visual feature space analysis, [Project Phase 2] Visual Analytics Methods for Modeling in Medical Imaging}, url = {http://visualanalytics.de/sites/default/files/upload/publications/vast11.pdf}, author = {S. Bremm and T. von Landesberger and M. He{\ss} and T. Schreck and P. Weil and K. Hamacher} } @proceedings {191, title = {Interactive Schematic Summaries for Exploration of Surveillance Video}, journal = {ACM International Conference on Multimedia Retrieval (ICMR)}, year = {2011}, pages = {9:1--9:8}, publisher = {ACM}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, doi = {10.1145/1991996.1992005}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2011a.pdf}, author = {M. H{\"o}ferlin and B. H{\"o}ferlin and D. Weiskopf and G. Heidemann} } @mastersthesis {445, title = {Kantenb{\"u}ndelung in interaktiven und zoombaren Visualisierungsumgebungen}, year = {2011}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {S. Gladisch} } @proceedings {215, title = {KD-Photomap: Exploring Photographs in Space and Time}, journal = {IEEE Visual Analytics Science and Technology (VAST 2011) Proceedings}, year = {2011}, pages = {291-292}, publisher = {IEEE Computer Society Press}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {I. Peca and H. Zhi and K. Vrotsou and N. Andrienko and G. Andrienko} } @proceedings {196, title = {Layered TimeRadarTrees}, journal = {In Proceedings of 15th International Conference on Information Visualization (IV)}, year = {2011}, publisher = {IEEE Computer Society}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Burch2011b.pdf}, author = {M. Burch and M. H{\"o}ferlin and D. Weiskopf} } @proceedings {297, title = {Lessons Learned from Tool Development for Animal Movement Analysis}, journal = {Poster Proc. 1st IEEE Symposium on Biological Data Visualization (IEEE BioVis)}, year = {2011}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://bib.dbvis.de/uploadedFiles/329.pdf}, author = {Mansmann, F. and D. Spretke and H. Janetzko} } @article {337, title = {Local similarity measures for lesion registration in DCE-MRI of the breast}, journal = {Annals of the BMVA}, volume = {3}, year = {2011}, pages = {1--13}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/2011-0003.pdf}, author = {S. Sch{\"a}fer and U. Preim and S. Gla{\ss}er and B. Preim and K. D. T{\"o}nnies} } @proceedings {181, title = {Multiscale Visual Quality Assessment for Cluster Analysis with Self-Organizing Maps}, journal = {IS\&T/SPIE Conference on Visualization and Data Analysis}, year = {2011}, keywords = {[Project Phase 1] Visual feature space analysis}, author = {J. Bernard and T. von Landesberger and S. Bremm and T. Schreck} } @proceedings {221, title = {Perception-based Visual Quality Measures}, journal = {Proc. {IEEE} Symposium on Visual Analytics Science and Technology {(VAST)} 2011}, year = {2011}, pages = {13--20}, keywords = {[Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Albuquerque2011PBQ.pdf}, author = {G. Albuquerque and M. Eisemann and M. Magnor} } @proceedings {257, title = {Personalized Relevance in Mobile Geographic Information Retrieval}, journal = {Proc. of 8th International Symposium on Location-Based Services 2011(LBS-11)}, year = {2011}, address = {Vienna, Austria}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Kumar_LBS11.pdf}, author = {C. Kumar and S. Boll} } @proceedings {218, title = {Privacy Issues in Geospatial Visual Analytics}, journal = {8th Symposium on Location-Based Services (LBS 2011)}, year = {2011}, publisher = {Springer}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko} } @proceedings {338, title = {Registration of ultrasonography sequences based on temporal regions}, journal = {7th Intl. Symp. on Image and Signal Processing and Analysis (ISPA 2011)}, year = {2011}, pages = {749--759}, address = {Dubrovnik, Croatia}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Schaefer_2011.pdf}, author = {S. Sch{\"a}fer and P. Angelelli and K. Nylund and O.H. Gilja and K. D. T{\"o}nnies} } @proceedings {258, title = {Relevance and Ranking in Geographic Information Retrieval}, journal = {4th Symposium on Future Directions in Information Access 2011(FDIA-11)}, year = {2011}, address = {Koblenz, Germany}, keywords = {[Project Phase 2] Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Kumar_ewic_fdia11.pdf}, author = {C. Kumar} } @proceedings {227, title = {ScatterBlogs: Geo-Spatial Document Analysis}, journal = {IEEE Conference on Visual Analytics Science and Technology}, year = {2011}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/paper114.pdf}, author = {H. Bosch and D. Thom and M. W{\"o}rner and S. Koch and E. P{\"u}ttmann and D. J{\"a}ckle and T. Ertl} } @proceedings {341, title = {Semantically Steered Visual Analysis of Highly Detailed Morphometric Shape Spaces}, journal = {In proceedings of BioVis 2011: 1st IEEE Symposium on biological data visualization, Providence}, year = {2011}, pages = {151-158}, address = {Rhode Island, USA}, keywords = {[Project Phase 2] Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes}, url = {http://visualanalytics.de/sites/default/files/upload/publications/hermann2011-semantically.pdf}, author = {M. Hermann and A.C. Schunke and R. Klein} } @proceedings {199, title = {Sense Discrimination for Physics Retrieval}, journal = {ACM SIGIR}, year = {2011}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, author = {A. Kothari and C. Lioma and H. Sch{\"u}tze} } @article {132, title = {Spatial Generalization and Aggregation of Massive Movement Data}, journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)}, year = {2011}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = {http://visualanalytics.de/sites/default/files/upload/publications/ttg2010990025.pdf}, author = {N. Andrienko and G. Andrienko} } @article {220, title = {Special issue on "Challenging Problems in Geovisual Analytics"}, volume = {v.22 (4)}, year = {2011}, pages = {251-304}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, doi = {http://dx.doi.org/10.1016/j.jvlc.2011.04.001}, author = {G. Andrienko and N. Andrienko and D.A. Keim and A. MacEachren and S. Wrobel} } @proceedings {225, title = {Sum-of-Superellipses - A Low Parameter Model for Amplitude Spectra of Natural Images}, journal = {International Conference on Image Analysis and Processing 2011}, volume = {6978/2011}, year = {2011}, pages = {128--138}, publisher = {Lecture Notes in Computer Science}, keywords = {[Project Phase 1] Zoomable Cell}, author = {M. Spehr and S. Gumhold and R. W. Fleming} } @proceedings {403, title = {Supporting Display Scalability by Redundant Mapping}, journal = {Proceedings of Advances in Visual Computing - International Symposium on Visual Computing (ISVC{\textquoteright}11)}, year = {2011}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {A. Radloff and M. Luboschik and M. Sips and H. Schumann} } @inbook {204, title = {A Survey on Video-based Graphics and Video Visualization}, booktitle = {EG 2011 - State of the Art Reports}, year = {2011}, pages = {1--23}, publisher = {Eurographics Association}, organization = {Eurographics Association}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Borgo2011.pdf}, author = {R. Borgo and M. Chen and E. Grundy and B. Daubney and G. Heidemann and B. H{\"o}ferlin and M. H{\"o}ferlin and H. J{\"a}nicke and D. Weiskopf and X. Xie} } @article {222, title = {Synthetic Generation of High-dimensional Datasets}, journal = {{IEEE} Transactions on Visualization and Computer Graphics {(TVCG,} Proc. Visualization / InfoVis)}, volume = {17}, year = {2011}, keywords = {[Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets, [Project Phase 2] Higher Order Visual Search for Information in Multidimensional Data Sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Albuquerque2011SGH.pdf}, author = {G. Albuquerque and T. L{\"o}we and M. Magnor} } @mastersthesis {444, title = {Unterst{\"u}tzung von Visualisierungszielen durch verschiedene Arten der Abbildung von Daten auf Farbe}, year = {2011}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {I. Wilke} } @proceedings {180, title = {Using multiplicative hybrid hedonic pricing model for improving revenue management in hotel business}, journal = {GeoVis 2011}, year = {2011}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and D.A. Keim and Y. Palivatkel and L. Rokach} } @inbook {RuWi10, title = {Variational methods in shape analysis}, booktitle = {Handbook of Mathematical Methods in Imaging}, year = {2011}, pages = {1363{\textendash}1401}, publisher = {Springer}, organization = {Springer}, keywords = {[Project Phase 1] Variational Methods for Model-based Interactive Analysis of Flows}, doi = {10.1007/978-0-387-92920-0_31}, author = {Rumpf, Martin and Wirth, Benedikt}, editor = {Otmar Scherzer} } @proceedings {328, title = {VisBricks: Multiform Visualization of Large, Inhomogeneous Data}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {17(12)}, year = {2011}, pages = {2291--2300}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {A. Lex and H.-J. Schulz and M. Streit and C. Partl and D. Schmalstieg} } @proceedings {230, title = {Visual analysis of large graphs: State-of-the-art and future research challenges}, journal = {Wiley-Blackwell Computer Graphics Forum, Online first}, year = {2011}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/cgf11-star.pdf}, author = {T. von Landesberger and A. Kuijper and T. Schreck and J. Kohlhammer and J. vanWijk and J.-D. Fekete and D. Fellner} } @proceedings {232, title = {Visual Analytics for Stochastic Simulation in Cell Biology}, journal = {Proceedings of the International Conference on Knowledge Management and Knowledge Technologies (iKNOW{\textquoteright}11)}, year = {2011}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {H.-J. Schulz and A. Uhrmacher and H. Schumann} } @proceedings {298, title = {Visual Analytics of Terrorist Activities Related to Epidemics}, journal = {Proc. IEEE Conference on Visual Analytics Science and Technology (VAST Challenge 2011 - Grand Challenge Award)}, year = {2011}, keywords = {[Project Phase 2] Visual analysis of movement and event data in spatiotemporal context}, url = {http://bib.dbvis.de/uploadedFiles/330.pdf}, author = {E. Bertini and J. Buchm{\"u}ller and F. Fischer and S. Huber and T. Lindemeier and F. Maa{\ss} and Mansmann, F. and T. Ramm and M. Regenscheit and C. Rohrdantz and C. Scheible and T. Schreck and S. Sellien and F. Stoffel and M. Tautzenberger and M. Zieker and D.A. Keim} } @proceedings {228, title = {Visual Feature Space Analysis - Methods and Applications}, journal = {LWA KDML Workshop 2011}, year = {2011}, address = {Magdeburg}, keywords = {[Project Phase 1] Visual feature space analysis}, author = {T. Schreck} } @article {213, title = {Visual Mobility Analysis using T-Warehouse}, journal = {International Journal of Data Warehousing and Mining}, volume = {v.7 (1)}, year = {2011}, pages = {1-23}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = {http://www.igi-global.com/Bookstore/Article.aspx?TitleId=49638}, author = {A. Raffaeta and L. Leonardi and G. Marketos and G. Andrienko and N. Andrienko and E. Frentzos and N. Giatrakos and S. Orlando and N. Pelekis and A. Roncato and C. Silvestri} } @book {233, title = {Visualization of Time-Oriented Data}, year = {2011}, publisher = {Springer Verlag}, organization = {Springer Verlag}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, isbn = {978-0-85729-078-6}, url = {http://www.springer.com/computer/hci/book/978-0-85729-078-6}, author = {W. Aigner and S. Miksch and H. Schumann and C. Tominski} } @proceedings {197, title = {Visualizing Dynamic Quantitative Data In Hierarchies}, journal = {Proceedings of International Conference on Visualization Theory and Applications}, year = {2011}, pages = {177--186}, publisher = {Springer}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Burch2011a.pdf}, author = {M. Burch and D. Weiskopf} } @proceedings {147, title = {Fault Forest Visualization}, journal = {SOFTVIS{\textquoteright}10}, year = {2010}, month = {10/2010}, address = {Salt Lake City, Utah, USA}, keywords = {[Project Phase 1] Visualization of and interaction with complex graphs on large scale and high resolution displays models metaphors and interaction paradigms}, author = {S. B{\"o}ttger and H. Barthel and A. Ebert} } @proceedings {144, title = {Event-based analysis of people{\textquoteright}s activities and behavior using Flickr and Panoramio geotagged photo collections}, journal = {IV 2010. 14th International Conference on Information Visualization}, year = {2010}, month = {07/2010}, address = {London, UK}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and M. Krstjaic and D.A. Keim and N. Andrienko and G. Andrienko} } @proceedings {143, title = {Extracting Events from Spatial Time Series}, journal = {IV 2010. 14th International Conference on Information Visualization}, year = {2010}, month = {07/2010}, address = {London, UK }, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko and M. Mladenov and M. Mock and C. P{\"o}litz} } @article {169, title = {Local Similarity Measures for ROI-based Registration of DCE-MRI of the Breast}, journal = {Proc. of Medical Image Understanding and Analysis (MIUA)}, year = {2010}, month = {07/2010}, pages = {159-163}, keywords = {[Project Phase 1] Efficient Visual Analysis of Dynamic Medical Image Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Schaefer_2010_MIUA.pdf}, author = {S. Sch{\"a}fer and C. M. Hentschke and K. D. T{\"o}nnies} } @proceedings {113, title = {Smart Query Definition for Content-Based Search in Large Sets of Graphs}, journal = {International Symposium on Visual Analytics Science and Technology (EuroVAST)}, year = {2010}, month = {06/2010}, address = {Bordeaux, France}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/GraphSearch.pdf}, author = {T. von Landesberger and S. Bremm and J. Bernard and T. Schreck} } @article {170, title = {Detection of Motion Distorted Areas in Perfusion MRI of the Breast}, journal = {Bildverarbeitung f{\"u}r die Medizin (BVM2010)}, year = {2010}, month = {03/2010}, pages = {172-176}, keywords = {[Project Phase 1] Efficient Visual Analysis of Dynamic Medical Image Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Schaefer_2010_BVM.pdf}, author = {S. Sch{\"a}fer and K. D. T{\"o}nnies} } @proceedings {159, title = {IR, NLP, and Visualization}, journal = {Advances in Information Retrieval, 32nd European Conference on IR Research, ECIR 2010}, year = {2010}, month = {03/2010}, pages = {11}, publisher = {Springer}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, issn = {978-3-642-12274-3}, author = {H. Sch{\"u}tze and C. Gurrin and Y. He and G. Kazai and U. Kruschwitz and S. Little and T. Roelleke and S. M. Ruger and K. van Rijsbergen} } @proceedings {161, title = {3D Object Localization via Stereo Vision using an Omnidirectional and a Perspective Camera}, journal = {2nd. Workshop on Omnidirectional Robot Vision, a workshop of the 2010 IEEE International Conference on Robotics and Automation (ICRA2010)}, year = {2010}, pages = {7--12}, publisher = {IEEE Press}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, issn = {978-88-95872-02-5}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Kaeppeler2010.pdf}, author = {U. Kaeppeler and M. H{\"o}ferlin and P. Levi} } @proceedings {130, title = {Bonsai: Growing Interesting Small Trees}, journal = {Proceedings of the 10th IEEE International Conference on Data Mining (ICDM{\textquoteright}2010), Sydney, Australia}, year = {2010}, keywords = {[Project Phase 1] New techniques for the interactive navigation visualization and analysis of heterogeneous biological networks}, url = {http://visualanalytics.de/sites/default/files/upload/publications/bonsai.pdf}, author = {S. Seufert and S. Bedathur and J. Mestre and G. Weikum} } @article {127, title = {Computational Polypharmacology with Text Mining and Ontologies}, journal = {Current Pharmaceutical Biotechnology}, year = {2010}, keywords = {[Project Phase 1] Zoomable Cell}, author = {C. Plake and M. Schroeder} } @conference {BoBeRu10, title = {Convex Relaxation for Grain Segmentation at Atomic Scale}, booktitle = {Vision, Modeling and Visualization}, year = {2010}, pages = {179{\textendash}186}, publisher = {Eurographics Association}, organization = {Eurographics Association}, keywords = {[Project Phase 1] Variational Methods for Model-based Interactive Analysis of Flows}, doi = {10.2312/PE/VMV/VMV10/179-186}, author = {Boerdgen, Markus and Berkels, Benjamin and Rumpf, Martin and Cremers, Daniel}, editor = {Dieter Fellner} } @proceedings {124, title = {Discontinuities in Continuous Scatterplots}, journal = {IEEE Transactions on Visualization and Computer Graphics (Proceedings IEEE Visualization)}, year = {2010}, keywords = {[Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Lehmann_2010_VIS.pdf}, author = {D. J. Lehmann and H. Theisel} } @proceedings {140, title = {Discovering Bits of Place Histories from People{\textquoteright}s Activity Traces}, journal = {VAST 2010}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko and M. Mladenov and M. Mock and C. P{\"o}litz} } @article {137, title = {Discovering Landmark Preferences and Movement Patterns from Photo Postings Transaction}, journal = {GIS}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {P. Jankowski and N. Andrienko and G. Andrienko and S. Kisilevich} } @proceedings {115, title = {Discrete Scale Axis Representations for 3D Geometry}, journal = {Proceedings of the 37th International Conference and Exhibition on Computer Graphics and Interactive Techniques (SIGGRAPH)}, year = {2010}, keywords = {[Project Phase 1] Visually guided exploration of point cloud data in Euclidean space}, url = {http://visualanalytics.de/sites/default/files/upload/publications/discrete_scale_axis_siggraph_2010.pdf}, author = {B. Miklos and J. Giesen and M. Pauly} } @article {128, title = {Examination of Apoptosis Signaling in Pancreatic Cancer by Computational Signal Transduction Analysis}, journal = {PLoS One}, year = {2010}, keywords = {[Project Phase 1] Zoomable Cell}, author = {F. Rueckert and G. Dawelbait and C. Winter and A. Hartmann and M. Schroeder and H. K. Schackert and B. Sipos and G. Kloeppel and H. Kalthoff and H.-D. Saeger and C. Pilarsky and R. Gruetzmann} } @proceedings {131, title = {Fast and Accurate Estimation of Shortest Paths in Large Graphs}, journal = {Proceedings of the 19th ACM International Conference on Information and Knowledge Management (CIKM{\textquoteright}2010), Toronto, Canada.}, year = {2010}, keywords = {[Project Phase 1] New techniques for the interactive navigation visualization and analysis of heterogeneous biological networks}, url = {http://visualanalytics.de/sites/default/files/upload/publications/cikm579i-gubichev.pdf}, author = {A. Gubichev and S. Bedathur and S. Seufert and G. Weikum} } @proceedings {145, title = {Finding arbitrary shaped clusters with related extents in space and time}, journal = {EuroVAST 2010, International Symposium on Visual Analytics Science and Technology}, year = {2010}, pages = {pp.19-25}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, issn = {978-3-905673-74-6}, author = {C. P{\"o}litz and G. Andrienko and N. Andrienko} } @proceedings {238, title = {Flexible Experimentation in the Modeling and Simulation Framework JAMES II - Implications for Computational Systems Biology}, journal = {Briefings in Bioinformatics}, volume = {11}, year = {2010}, pages = {290-300}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {R. Ewald and J. Himmelspach and M. Jeschke and S. Leye and A. Uhrmacher} } @article {134, title = {A Framework for Using Self-Organizing Maps to Analyze Spatio-Temporal Patterns, Exemplified by Analysis of Mobile Phone Usage}, journal = {Journal of Location Based Services}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space, [Project Phase 1] Visual feature space analysis}, author = {G. Andrienko and N. Andrienko and P. Bak and S. Bremm and D.A. Keim and T. von Landesberger and C. P{\"o}litz and T. Schreck} } @inbook {155, title = {From static textual display of patents to graphical interactions}, booktitle = {Current Challenges in Patent Information Retrieval}, year = {2010}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, author = {S. Koch and H. Bosch} } @article {136, title = {A General Framework for Using Aggregation in Visual Exploration of Movement Data}, journal = {The Cartographic Journal}, year = {2010}, pages = {pp. 22-40}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko} } @proceedings {146, title = {A Generalisation-based Approach to Anonymising Movement Data}, journal = {Geospatial Thinking, AGILE 2010}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, issn = {978-989-20-1953-6}, author = {G. Andrienko and N. Andrienko and F. Giannotti and A. Monerale and D. Pedreschi and S. Rinzivillo}, editor = {M. Painho and M. Y. Santos and H. Pundt} } @proceedings {156, title = {Generating a Visual Overview of Large Diachronic Document Collections based on the Detection of Topic Change}, journal = {Proc. IVAPP 2010: International Conference on Information Visualization Theory and Applications}, year = {2010}, keywords = {[Project Phase 1] Topology-based Visual Analysis of Information Spaces}, url = {http://visualanalytics.de/sites/default/files/upload/publications/teresniak-ivapp2010.pdf}, author = {Holz, F. and Teresniak, S. and Heyer, G. and Scheuermann, G.} } @article {92, title = {Genome-wide expression profiling and functional network analysis upon neuroectodermal conversion of human mesenchymal stem cells suggest HIF-1 and miR-124a as important regulators.}, journal = {To appear in Experimental Cell Research}, year = {2010}, keywords = {[Project Phase 1] Zoomable Cell}, author = {M. Maisel and H. Habisch and L. Royer and A. Herr and J. Milosevic and S. Liebau and R. Brenner and J. Schwarz and M. Schroeder and A. Storch} } @proceedings {173, title = {GEO-SPADE: A generic google-earth based framework for analysis and exploration of spatiotemporal data.}, journal = {12th International Conference on Enterprise Information Systems}, year = {2010}, pages = {13-20}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and D.A. Keim and L. Rokach} } @proceedings {122, title = {Improving the Visual Analysis of High-dimensional Datasets Using Quality Measures}, journal = {Proc. of the IEEE Symposium on Visual Analytics Science and Technology (IEEE VAST)}, year = {2010}, keywords = {[Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/AlbuquerqueVAST2010.pdf}, author = {G. Albuquerque and M. Eisemann and D. J. Lehmann and H. Theisel and M. Magnor} } @proceedings {163, title = {Information-Based Adaptive Fast-Forward for Visual Surveillance}, journal = {Multimedia Tools and Applications}, year = {2010}, publisher = {Springer Netherlands}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, doi = {10.1007/s11042-010-0606-z}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2010c.pdf}, author = {B. H{\"o}ferlin and M. H{\"o}ferlin and D. Weiskopf and G. Heidemann} } @proceedings {167, title = {Interactive Motion Segmentation}, journal = {Interactive Flow Analysis}, year = {2010}, keywords = {[Project Phase 1] Variational Methods for Model-based Interactive Analysis of Flows}, url = {http://visualanalytics.de/sites/default/files/upload/publications/MotionSegmentation.pdf}, author = {C. Nieuwenhuis and B. Berkels and M. Rumpf and D. Cremers} } @proceedings {149, title = {Iterative Integration of Visual Insights during Scalable Patent Search and Analysis}, journal = {IEEE Transactions on Visualization and Computer Graphics}, year = {2010}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/TVCG10.pdf}, author = {S. Koch and H. Bosch and M. Giereth and T. Ertl} } @article {129, title = {A knowledge-based search engine to navigate the information thicket of nanotoxicology}, journal = {Regulatory Toxicology and Pharmacology}, year = {2010}, keywords = {[Project Phase 1] Zoomable Cell}, author = {U. Sauer and C. Kneuer and J. Tentschert and T. W{\"a}chter and M. Schroeder and A. Luch and M. Liebsch and B. Grune and M. E. Goetz} } @article {179, title = {Mashing up for the Masses. Towards a User Oriented Visual Exploration of Interesting Touristic Places Using Collections of Geotagged Photos.}, journal = {International Journal On Advances in Intelligent Systems (submitted)}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and C. Rohrdantz and D.A. Keim} } @proceedings {119, title = {MeMotif: Structural fragment clustering reveals novel structural and functional motifs in alpha-helical transmembrane proteins.}, journal = {Nucleic Acids Research}, year = {2010}, pages = {D181--D189}, edition = {38(Database issue)}, keywords = {[Project Phase 1] Zoomable Cell}, author = {A. Marsico and K. Scheubert and A. Henschel and C. Winter and R. Winnenburg and A. Tuukkanen and B. Vassilev and M. Schroeder} } @article {138, title = {Movement Data Anonymity through Generalization}, journal = {Transactions on Data Privacy}, year = {2010}, pages = {pp. 91-121}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = {http://visualanalytics.de/sites/default/files/upload/publications/tdpa045a10.pdf}, author = {A. Monreale and G. Andrienko and N. Andrienko and F. Giannotti and D. Pedreschi and S. Rinzivillo and S. Wrobel} } @proceedings {172, title = {A novel approach to mining travel sequences using collections of geo-tagged photos. }, journal = {Proceedings of the 13th AGILE International Conference on Geographic Information Science}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and D.A. Keim and L. Rokach} } @proceedings {174, title = {P-DBSCAN: A density based clustering algorithm for exploration and analysis of attractive areas using collections of geo-tagged photos}, journal = {1st International Conference on Computing for Geospatial Research \& Application}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and Mansmann, F. and D.A. Keim} } @proceedings {65, title = {Parahistogramme innerhalb eines dreidimensionalen Interaktionsraumes}, journal = {Bildverarbeitung f{\"u}r die Medizin}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics for Large and heterogeneous Life Science data with emphasis on expression data}, author = {A. Pritzkau and D. Bartz} } @proceedings {141, title = {Poster: Dynamic Time Transformation for Interpreting Clusters of Trajectories with Space-Time Cube}, journal = {VAST 2010}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko} } @proceedings {150, title = {Preliminary Study into Query Translation for Patent Retrieval}, journal = {PaIR}, year = {2010}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/pair10.pdf}, author = {C. Jochim and S. Koch and C. Lioma and H. Sch{\"u}tze and T. Ertl} } @proceedings {142, title = {Sammon{\textquoteright}s Projection for Clustering Complex Geographical Objects}, journal = {GIScience 2010}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko} } @proceedings {160, title = {Selection of an Optimal Set of Discriminative and Robust Local Features with Application to Traffic Sign Recognition}, journal = {WSCG 2010, 18th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision}, year = {2010}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2010b.pdf}, author = {B. H{\"o}ferlin and G. Heidemann} } @proceedings {117, title = {Semi-automated ontology generation within OBO-Edit.}, journal = {Bioinformatics}, year = {2010}, pages = {i88--i96}, edition = {26(12)}, keywords = {[Project Phase 1] Zoomable Cell}, author = {T. W{\"a}chter and M. Schroeder} } @proceedings {187, title = {A Semi-Automatic Image Morphing Technique for Biological Images}, journal = {EG Workshop VCBM 2010 (Poster)}, year = {2010}, keywords = {[Project Phase 1] Zoomable Cell}, author = {M. Spehr and A. Viergutz and S. Gumhold} } @inbook {389, title = {Space and Time}, booktitle = {Mastering the Information Age -- Solving Problems with Visual Analytics}, year = {2010}, publisher = {Eurographics Association}, organization = {Eurographics Association}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, issn = {978-3-905673-77-7}, author = {G. Andrienko and N. Andrienko and U. Demar and D. Dransch and J. Dykes and S. Fabrikant and M. Jern} } @article {133, title = {Space, Time, and Visual Analytics}, journal = {International Journal Geographical Information Science}, year = {2010}, pages = {pp. 1577-1600}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko and U. Demar and D. Dransch and J. Dykes and S. Fabrikant and M. Jern and M.-J. Kraak and H. Schumann and C. Tominski} } @proceedings {112, title = {Space-in-Time and Time-in-Space Self-Organizing Maps for Exploring Spatiotemporal Patterns}, journal = {EuroVis 2010}, year = {2010}, pages = {913-922}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space, [Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/eurovis10.pdf}, author = {G. Andrienko and N. Andrienko and S. Bremm and T. Schreck and T. von Landesberger and D.A. Keim and P. Bak} } @article {45, title = {Spatial Generalization and Aggregation of Massive Movement Data}, journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {N. Andrienko and G. Andrienko} } @inbook {176, title = {Spatio-temporal clustering (Book chapter)}, year = {2010}, publisher = {Springer}, organization = {Springer}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich}, editor = {L. Rokach and O. Maimon} } @proceedings {116, title = {Structural fragment clustering reveals novel structural and functional motifs in alpha-helical transmembrane proteins.}, journal = {BMC Bioinformatics}, year = {2010}, edition = {11(204)}, keywords = {[Project Phase 1] Zoomable Cell}, author = {A. Marsico and A. Henschel and C. Winter and A. Tuukkanen and B. Vassilev and K. Scheubert and M. Schroeder} } @article {125, title = {Structural Modeling of histone methyltransferase complex Set1C from Saccharomyces cerevisiae using constraint-based docking}, journal = {Proteomics}, year = {2010}, keywords = {[Project Phase 1] Zoomable Cell}, author = {A. Tuukkanen and A. Henschel and B. Huang and A. F. Stewart and M. Schroeder} } @article {166, title = {Techniques for precision-based visual analysis of projected data}, journal = {Information Visualization}, volume = {9}, year = {2010}, pages = {181-193(13)}, abstract = {The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection techniques such as Principal Component Analysis, Multi-dimensional Scaling and Self-Organizing Map can be used to map high-dimensional data to 2D display space. However, projections typically incur a loss in information. Often, uncertainty exists regarding the precision of the projection as compared with its original data characteristics. While the output quality of these projection techniques can be discussed in terms of aggregate numeric error values, visualization is often helpful for better understanding the projection results. We address the visual assessment of projection precision by an approach integrating an appropriately designed projection precision measure directly into the projection visualization. To this end, a flexible projection precision measure is defined that allows the user to balance the degree of locality at which the measure is evaluated. S everal visual mappings are designed for integrating the precision measure into the projection visualization at various levels of abstraction. The techniques are implemented in an interactive system, including methods supporting the user in finding appropriate settings of relevant parameters. We demonstrate the usefulness of the approach for visual analysis of classified and unclassified high-dimensional data sets. We show how our interactive precision quality visualization system helps to examine the preservation of original data properties in projected space.}, keywords = {[Project Phase 1] Visual feature space analysis}, doi = {doi:10.1057/ivs.2010.2}, url = {http://visualanalytics.de/sites/default/files/upload/publications/ivs2010.pdf}, author = {T. von Landesberger and T. Schreck and S. Bremm} } @conference {Precision-Based, title = {Techniques for Precision-Based Visual Analysis of Projected Data.}, booktitle = {IS\&T/SPIE Conference on Visualization and Data Analysis (VDA 2010)}, year = {2010}, abstract = {The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection techniques such as PCA, MDS, and SOM can be used to map high-dimensional data to 2D display space. However, projections typically incur a loss in information. Therefore, uncertainty usually exists when evaluating the precision of the projection against the original high-dimensional data characteristics. While the output quality of these techniques can be discussed in terms of algorithmic assessment, visualization is often helpful for better understanding the results. In this paper, we address the assessment of projection precision by an approach integrating an appropriately designed projection precision measure directly into the projection visualization. To this end, a exible projection precision measure is de ned that allows the user to balance the degree of locality at which the measure is evalu- ated. Several visual mappings are designed for integrating the precision measure into the projection visualization at various levels of abstraction. The techniques are implemented in a fully interactive system which is practically applied on several data sets. We demonstrate the usefulness of the approach for visual analysis of classi ed and clustered high-dimensional data sets. We thereby show how our novel interactive precision quality visualization system helps to examine preservation of closeness of the data in original space into the low-dimensional space.}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/TechniquesforPrecision.pdf}, author = {T. Schreck and T. von Landesberger and S. Bremm} } @article {175, title = {Towards acquisition of semantics of places and events by multi-perspective analysis of geotagged photo collections}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and D.A. Keim and N. Andrienko and G. Andrienko} } @proceedings {157, title = {Towards Automatic Detection and Tracking of Topic Change}, journal = {Proc. CICLing 2010, Ia?i: Conference on Intelligent Text Processing and Computational Linguistics, LNCS 6008}, year = {2010}, publisher = {Springer LNCS}, keywords = {[Project Phase 1] Topology-based Visual Analysis of Information Spaces}, url = {http://visualanalytics.de/sites/default/files/upload/publications/holz-teresniak-cicling2010.pdf}, author = {Holz, F. and Teresniak, S.}, editor = {A. Gelbukh} } @proceedings {158, title = {Two-stage Framework for a Topology-Based Projection and Visualization of Classified Document Collections}, journal = {IEEE Conference on Visual Analytics Science and Technology (IEEE VAST)}, year = {2010}, publisher = {IEEE Computer Society}, keywords = {[Project Phase 1] Topology-based Visual Analysis of Information Spaces}, url = {http://visualanalytics.de/sites/default/files/upload/publications/oesterling-vast2010.pdf}, author = {Oesterling, P. and Scheuermann, G. and Teresniak, S. and Heyer, G. and S. Koch and T. Ertl and G. H. Weber} } @article {164, title = {Uncertainty-Aware Video Visual Analytics of Tracked Moving Objects}, journal = {Journal of Spatial Information Science (JOSIS)}, year = {2010}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, doi = {10.5311/JOSIS.2010.2.1}, url = {http://www.visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2010d.pdf}, author = {M. H{\"o}ferlin and B. H{\"o}ferlin and D. Weiskopf and G. Heidemann} } @proceedings {162, title = {Video Visualization for Snooker Skill Training}, journal = {Computer Graphics Forum}, year = {2010}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, doi = {http://dx.doi.org/10.1111/j.1467-8659.2009.01670.x}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2010.pdf}, author = {M. H{\"o}ferlin and E. Grundy and R. Borgo and D. Weiskopf and M. Chen and I.W. Griffiths and W. Griffiths} } @conference {OHJ*:2009, title = {Visual Analysis of High Dimensional Point Clouds Using Topological Landscapes}, booktitle = {IEEE Pacific Visualization 2010 Proceedings}, year = {2010}, note = {submitted
}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, keywords = {[Project Phase 1] Topology-based Visual Analysis of Information Spaces}, author = {Oesterling, P. and Heine, C. and H. J{\"a}nicke and Scheuermann, G.} } @proceedings {114, title = {Visual Analysis of Large Graphs}, journal = {Eurographics}, year = {2010}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/egstar10.pdf}, author = {T. von Landesberger and A. Kuijper and T. Schreck and J. Kohlhammer and J. vanWijk and J.-D. Fekete and D. Fellner} } @article {182, title = {A visual analytics approach to diagnosis of breast DCE-MRI data}, journal = {Computer and Graphics}, year = {2010}, pages = {602-611}, keywords = {[Project Phase 1] Efficient Visual Analysis of Dynamic Medical Image Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/A Visual Analytics Approach to Diagnosis of Breast DCE-MRI Data.pdf}, author = {S. Gla{\ss}er and U. Preim and K. D. T{\"o}nnies and B. Preim} } @mastersthesis {Oeltze2010, title = {Visual Exploration and Analysis of Perfusion Data}, volume = {PhD}, year = {2010}, school = {Otto-von-Guericke University Magdeburg}, address = {Magdeburg, Germany}, keywords = {[Project Phase 2] Visual Analytics in Public Health}, author = {Steffen Oeltze} } @article {139, title = {Visual Mobility Analysis using T-Warehouse}, journal = {International Journal of Data Warehousing and Mining}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {A. Raffaeta and L. Leonardi and G. Marketos and G. Andrienko and N. Andrienko and E. Frentzos and N. Giatrakos and S. Orlando and N. Pelekis and A. Roncato and C. Silvestri} } @proceedings {123, title = {Visualisierung und Analyse multi-dimensionaler Datens{\"a}tze}, journal = {Informatik Spektrum}, year = {2010}, keywords = {[Project Phase 1] Coordination Project, [Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, author = {D. J. Lehmann and G. Albuquerque and M. Eisemann and A. Tatu and D.A. Keim and H. Schumann and M. Magnor and H. Theisel} } @article {185, title = {Visuelle Analyse medizinischer Daten}, journal = {Informatik Spektrum}, year = {2010}, pages = {569-579}, keywords = {[Project Phase 1] Efficient Visual Analysis of Dynamic Medical Image Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Visuelle Analyse medizinischer Daten.pdf}, author = {B. Preim and S. Oeltze and K. D. T{\"o}nnies} } @proceedings {165, title = {Visuelle Bewegungsanalyse in Video- und Geodaten}, journal = {Informatik Spektrum}, volume = {33}, year = {2010}, pages = {580--588}, publisher = {Springer Berlin / Heidelberg}, address = {Universit{\"a}t Stuttgart, Stuttgart, Deutschland}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, doi = {10.1007/s00287-010-0490-y}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Weiskopf2010.pdf}, author = {D. Weiskopf and G. Andrienko and N. Andrienko and P. Bak} } @proceedings {153, title = {Visuelle Textanalyse}, journal = {Informatik Spektrum}, year = {2010}, keywords = {[Project Phase 1] Coordination Project, [Project Phase 1] Scalable Visual Patent Analysis, [Project Phase 1] Topology-based Visual Analysis of Information Spaces}, author = {C. Rohrdantz and S. Koch and C. Jochim and Heyer, G. and Scheuermann, G. and T. Ertl and H. Sch{\"u}tze and D.A. Keim} } @proceedings {88, title = {Where Would You Go on Your Next Vacation? - A Framework for Visual Exploration of Attractive Places}, journal = {GeoProcessing 2010}, year = {2010}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and Mansmann, F. and P. Bak and D.A. Keim and A. Tchaikin} } @article {126, title = {Whole blood genome-wide expression profiling and network analysis suggest MELAS master regulators}, journal = {Neurological Research}, year = {2010}, author = {S. Mende and L. Royer and A. Herr and J. Schmiedel and M. Deschauer and T. Klopstock and V. S. Kostic and M. Schroeder and H. Reichmann and A. Storch} } @proceedings {118, title = {Xenopus meiotic microtubule-associated protein interaction network.}, journal = {PLoS One}, year = {2010}, pages = {e9248}, edition = {5(2)}, keywords = {[Project Phase 1] Zoomable Cell}, author = {V. Gache and P. Waridel and C. Winter and A. Juhem and M. Schroeder and A. Shevchenko and A. V. Popov} } @proceedings {177, title = {{\textquotedblleft}Beautiful picture of an ugly place{\textquotedblright}. Exploring photo collections using opinion and sentiment analysis of user comments}, journal = {Computational Linguistics \& Applications (CLA 10)}, year = {2010}, pages = {419-428}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {S. Kisilevich and C. Rohrdantz and D.A. Keim} } @conference {HHT:2009, title = {Change of Topics over Time and Tracking Topics by Their Change of Meaning}, booktitle = {KDIR {\textquoteright}09: Proc. of Int. Conf. on Knowledge Discovery and Information Retrieval}, year = {2009}, month = {October}, keywords = {[Project Phase 1] Topology-based Visual Analysis of Information Spaces}, author = {Heyer, G. and Holz, F. and Teresniak, S.} } @conference {Glasser_2009_VMV, title = {A Visual Analytics Approach to Diagnosis of Breast DCE-MRI Data}, booktitle = {{Proc. on Vision, Modeling, and Visualization (VMV)}}, year = {2009}, month = {November}, pages = {351{\textendash}362}, address = {Braunschweig}, abstract = {Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast has become an important image modality for early breast cancer detection. In comparison to conventional X-ray mammography it exhibits a higher sensitivity, but only moderate specificity. To improve the specificity, and therefore the distinction of benign and malignant changes, the lesion\’s heterogeneity and the lesion enhancement kinetics have to be evaluated. We present a visual analytics approach for breast tumors in DCE-MRI data that divides a tumor in different regions with different perfusion characteristics by employing a region merging method. The resulting region-based representation allows for evaluation of the tumor\’s heterogeneity and the region-wise qualitative and quantitative evaluation of the enhancement kinetics. The analyses are combined with a glyph-based representation for a fast overview of the whole lesion. We tested our approach with seven well-chosen lesions and compared them to their histopathologic reports.
}, keywords = {[Project Phase 1] Efficient Visual Analysis of Dynamic Medical Image Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/VMV2009_Glasser.pdf}, author = {S. Gla{\ss}er and S. Sch{\"a}fer and S. Oeltze and U. Preim and K. D. T{\"o}nnies and B. Preim} } @article {THS*:2009, title = {Visualisierung von Bedeutungsverschiebungen in gro}, journal = {Datenbank-Spektrum}, volume = {31}, year = {2009}, note = {submitted}, month = {12}, keywords = {[Project Phase 1] Topology-based Visual Analysis of Information Spaces}, author = {Teresniak, S. and Heyer, G. and Scheuermann, G. and Holz, F.} } @conference {36, title = {Demo-Paper: Analysis of community-contributed space- and time-referenced data (by example of Panoramio photos)}, booktitle = {ACM-GIS Conference}, year = {2009}, month = {11/2009}, abstract = {Space- and time-referenced data published on the Web by general people can be viewed in a dual way: as independent spatiotemporal events and as trajectories of people in the geographical space. These two views suppose different approaches to the analysis, which can yield different kinds of valuable knowledge about places and about people. We present several analysis methods corresponding to these two views. The methods are suited to the large amounts of the data.}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = {http://visualanalytics.de/sites/default/files/upload/publications/acmgis09.pdf}, author = {G. Andrienko and N. Andrienko and P. Bak and S. Kisilevich and D.A. Keim} } @conference {48, title = {Movement Data Anonymity through Generalization}, booktitle = {Proceedings of 2nd SIGSPATIAL ACM GIS 2009 International Workshop on Security and Privacy in GIS and LBS}, year = {2009}, month = {11/2009}, address = {Seattle, WA, USA}, abstract = {In recent years, spatio-temporal and moving objects databases have gained considerable interest, due to the di usion of mobile devices (e.g., mobile phones, RFID devices and GPS devices) and of new applications, where the discovery of consumable, concise, and applicable knowledge is the key step. Clearly, in these applications privacy is a concern, since models extracted from this kind of data can reveal the behavior of group of individuals, thus compromising their privacy. Movement data present a new challenge for the privacy-preserving data mining community because of their spatial and temporal characteristics. In this position paper we briey present an approach for the generalization of movement data that can be adopted for obtaining k-anonymity in spatio-temporal datasets; specifically, it can be used to realize a framework for publishing of spatio-temporal data while preserving privacy. We ran a preliminary set of experiments on a real-world trajectory dataset, demonstrating that this method of generalization of trajectories preserves the clustering analysis results.}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = { http://visualanalytics.de/sites/default/files/upload/publications/springl09.pdf}, author = {N. Andrienko and G. Andrienko and F. Giannotti and A. Monreale and D. Pedreschi} } @proceedings {43, title = {Video Visual Analytics of Tracked Moving Objects}, journal = {Proceedings of 3rd Workshop on Behaviour Monitoring and Interpretation}, volume = {541}, year = {2009}, month = {11/2009}, pages = {59--64}, publisher = {CEUR Workshop Proceedings}, address = {Ghent University, Belgium}, abstract = {Exploring video data by simply watching does not scale for large databases. Especially, this problem becomes obvious in the field of video surveillance. Motivated by a mini challenge of the contest of the IEEE Symposium on Visual Analytics Science and Technology 2009 (Detecting the encounter of persons in a provided video stream utilizing the techniques of visual analytics), we propose an approach for fast identification of relevant objects based on the properties of their trajectories. We present a novel visual and interactive filter process for fast video exploration that yields good results even with challenging video data. The video material includes changing illumination and was captured with low temporal resolution by a camera panning between different views.
}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2009b.pdf}, author = {M. H{\"o}ferlin and B. H{\"o}ferlin and D. Weiskopf} } @article {59, title = {Visualization of Omics Data for Systems Biology}, journal = {Nature Methods}, year = {2009}, month = {10/2009}, keywords = {[Project Phase 1] New techniques for the interactive navigation visualization and analysis of heterogeneous biological networks}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Gehlenborg.pdf}, author = {N. Gehlenborg and N. S. Baliga and A. Goesmann and M. A. Hibbs. and H. Kitano and O. Kohlbacher and H. Neuweger and R. Schneider and D. Tenenbaum and A. Gavin} } @conference {52, title = {Interactive spatio-temporal cluster analysis of VAST challenge 2008 datasets Integrating Automated Analysis with Interactive Exploration}, booktitle = {Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery}, year = {2009}, month = {07/2009}, address = {Paris, France}, abstract = {We describe a visual analytics method supporting the analysis of two different types of spatio-temporal data, point events and trajectories of moving agents. The method combines clustering with interactive visual displays, in particular, map and space-time cube. We demonstrate the use of the method by applying it to two datasets from the VAST Challenge 2008: evacuation traces (trajectories of people movement) and landings and interdictions of migrant boats (point events).}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = {http://visualanalytics.de/sites/default/files/upload/publications/vakd09.pdf}, author = {N. Andrienko and G. Andrienko} } @conference {54, title = {A Visual Analytics Toolkit for Cluster-Based Classification of Mobility Data Advances in Spatial and Temporal Databases}, booktitle = {Proceedings 11th SSTD}, year = {2009}, month = {07/2009}, publisher = {Springer Berlin / Heidelberg}, organization = {Springer Berlin / Heidelberg}, address = {Aalborg}, abstract = {In this paper we propose a demo of a Visual Analytics Toolkit to cope with the complexity of analysing a large dataset of moving objects, in a step wise manner.We allow the user to sample a small subset of objects, that can be handled in main memory, and to perform the analysis on this small group by means of a density based clustering algorithm. The GUI is designed in order to exploit and facilitate the human interaction during this phase of the analysis, to select interesting clusters among the candidates. The selected groups are used to build a classifier that can be used to label other objects from the original dataset. The classifier can then be used to efficiently associate all objects in the database to clusters. The tool has been tested using a large set of GPS tracked cars.}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, isbn = {978-3-642-02981-3}, url = {http://visualanalytics.de/sites/default/files/upload/publications/springer09.pdf}, author = {N. Andrienko and G. Andrienko and S. Rinzivillo and M. Nanni and D. Pedreschi} } @conference {53, title = {Visual Analytics for Geographic Analysis, Exemplified by Different Types of Movement Data Information Fusion and Geographic Information Systems}, booktitle = {Proceedings of the Fourth International Workshop, 17-20 May 2009}, year = {2009}, month = {05/2009}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, address = {Sankt Petersburg}, abstract = {Visual analytics is introduced in the sense of a new research discipline defined as the science of analytical reasoning facilitated by interactive visual interfaces. Visual analytics combines automated analysis techniques with interactive visualizations so as to extend the perceptual and cognitive abilities of humans and enable them to extract useful information and derive knowledge from large and complex data, and to solve complex problems. Inparticular, data and problems involving geospatial components are inherently complex and therefore call for visual analytics approaches. The problems of analyzing data about movement of various discrete objects in geographical space are discussed in detail. The paper considers three types of movement data: data describing movements of a single entity during a long time period, data about simultaneous movements of multiple unrelated entities, and data about simultaneous movements of multiple related entities. The pertinent analysistasks significantly differ for these types of data. For each type of data, the visual analytics techniques and tools lately developed by the authors are briefly described.}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, isbn = {978-3-642-00303-5 (Print) 978-3-642-00304-2 (Online)}, author = {N. Andrienko and G. Andrienko} } @conference {50, title = {Analysis of community-contributed space- and time-referenced data (example of flickr and panoramio photos)}, booktitle = {IEEE Visual Analytics Science and Technology (VAST 2009)}, year = {2009}, abstract = {Space- and time-referenced data published on the Web by general people can be viewed in a dual way: as independent spatiotemporal events and as trajectories of people in the geographical space. These two views suppose different approaches to the analysis, which can yield different kinds of valuable knowledge about places and about people. We define possible types of analysis tasks related to the two views of the data and present several analysis methods appropriate for these tasks. The methods are suited to large amounts of the data.}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = {http://visualanalytics.de/sites/default/files/upload/publications/vast09a.pdf}, author = {N. Andrienko and G. Andrienko and P. Bak and S. Kisilevich and D.A. Keim} } @conference {34, title = {Analysis of community-contributed space- and time-referenced data by example of Panoramio photos}, booktitle = {Vision, Modeling, and Visualization Workshop (VMV)}, year = {2009}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {G. Andrienko and N. Andrienko and P. Bak and S. Kisilevich and D.A. Keim} } @inbook {60, title = {Bioinformatics for Proteomics}, booktitle = {Bioinformatics for Omics data}, year = {2009}, publisher = {Humana Press}, organization = {Humana Press}, chapter = {2}, keywords = {[Project Phase 1] New techniques for the interactive navigation visualization and analysis of heterogeneous biological networks}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Bielow.pdf}, author = {C. Bielow and C. Gr{\"o}pl and O. Kohlbacher and K. Reinert} } @conference {51, title = {Building Visual Summaries of Clusters of Trajectories}, booktitle = {IEEE Information Visualization (InfoVis 2009)}, year = {2009}, abstract = {A big problem in analysis of movement data (trajectories of moving agents) is how to visualize clusters of trajectories so as to have an overview of all clusters and to be able to compare different clusters. Clusters of trajectories are not disjoint in space but intersect and overlap. Hence, they need to be shown separately in multiple small displays. Such displays can be legible only if the clusters are presented in a schematized form. We suggest a method for building schematic representations of clusters of trajectories. The method transforms trajectories into aggregate flows between areas. The areas are automatically defined on the basis of the spatial distribution of the characteristic points from the trajectories. We use numeric measures of the abstraction quality and techniques for controlling the quality.}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = {http://visualanalytics.de/sites/default/files/upload/publications/infovis09.pdf}, author = {N. Andrienko and G. Andrienko} } @proceedings {84, title = {Combining automated analysis and visualization techniques for effective exploration of high-dimensional data}, journal = {IEEE Visual Analytics Science and Technology (VAST 2009)}, year = {2009}, abstract = {Visual exploration of multivariate data typically requires projection onto lower-dimensional representations. The number of possible representations grows rapidly with the number of dimensions, and manual exploration quickly becomes ineffective or even unfeasible. This paper proposes automatic analysis methods to extract potentially relevant visual structures from a set of candidate visualizations. Based on features, the visualizations are ranked in accordance with a specified user task. The user is provided with a manageable number of potentially useful candidate visualizations, which can be used as a starting point for interactive data analysis. This can effectively ease the task of finding truly useful visualizations and potentially speed up the data exploration task. In this paper, we present ranking measures for class-based as well as non class-based Scatterplots and Parallel Coordinates visualizations. The proposed analysis methods are evaluated on different datasets.
}, keywords = {[Project Phase 1] Coordination Project, [Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Tatu09VAST.pdf}, author = {A. Tatu and G. Albuquerque and M. Eisemann and J. Schneidewind and H. Theisel and M. Magnor and D.A. Keim} } @article {38, title = {Density Equalizing Distortion of Large Geographic Point Sets}, journal = {Cartographic and Geographic Information Science}, volume = {36}, year = {2009}, chapter = {237}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {P. Bak and M. Schaefer and A. Stoffel and D.A. Keim and I. Omer} } @article {VESA, title = {Ein flexibles System f{\"u}r die explorative visuelle Sequenz-Analyse}, journal = {Datenbank Spektrum}, year = {2009}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Einflexibles.pdf}, author = {S. Bremm and S. Maier and T. von Landesberger and T. Schreck} } @proceedings {100, title = {Go3R - Semantic Internet Search Engine for Alternative Methods to Animal Testing}, journal = {ALTEX}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {U. Sauer and T. W{\"a}chter and B. Grune and A. Doms and M. R. Alvers and H. Spielmann and M. Schroeder} } @proceedings {96, title = {GoGene: gene annotation on the fast lane}, journal = {Nucleic Acid Research}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {C. Plake and L. Royer and R. Winnenburg and J. Hakenberg and M. Schroeder} } @article {102, title = {GoPubMed: Exploring PubMed with Ontological Background Knowledge}, journal = {Bioinformatics for Systems Biology. Humana Press}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {H. Dietze and D. Alexopolou and M. R. Alvers and L. Barrio-Alvers and B. Andreopoulos and A. Doms and J. Hakenberg and J. M{\"o}nnich and C. Plake and A. Reischuck and L. Royer and T. W{\"a}chter and M. Zschunke and M. Schroeder} } @proceedings {97, title = {GoWeb: A semantic search engine for the life science web}, journal = {BMC Bioinformatics}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {H. Dietze and M. Schroeder} } @proceedings {101, title = {Identifying hot cancer and novel novel cell-cycle genes from literature}, journal = {Proceedings of the German Conference on Bioinformatics. Gesellschaft f{\"u}r Informatik}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {L. Royer and C. Plake and M. Schroeder} } @article {148, title = {Illustrative visualization: interrogating triangulated surfaces}, journal = {Computing}, year = {2009}, pages = {131-150}, keywords = {[Project Phase 1] Visualization of and interaction with complex graphs on large scale and high resolution displays models metaphors and interaction paradigms}, author = {R. J. Moorhead II and Y. Guan and H. Hagen and S. B{\"o}ttger and N. Kotava and C. Wagner} } @proceedings {64, title = {Innovative Filtering Techniques and Customized Analytics Tools}, journal = {IEEE Symposium on Visual Analytics Science and Technology}, year = {2009}, abstract = {The VAST 2009 Challenge consisted of three heterogeneous synthetic data sets organized into separate mini-challenges with minimal correspondence information. The challenge task was the identification of a suspected data theft from cyber and real-world traces. The grand challenge required integrating the findings from the mini challenges into a plausible, consistent scenario. A mixture of linked, customized tools based on queryable models and rapid prototyping as well as generic analysis tools (developed in-house) helped us correctly solve all of the mini challenges. A collaborative analytic process was employed to reconstruct the scenario and to propose the correct steps for the reliable identification of the criminal organization based on activity traces of its members.}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Bosch2009.pdf}, author = {H. Bosch and J. Heinrich and B. H{\"o}ferlin and M. H{\"o}ferlin and S. Koch and C. M{\"u}ller and G. Reina and M. W{\"o}rner} } @article {47, title = {Interactive Cluster Analysis of Diverse Types of Spatiotemporal Data}, journal = {ACM SIGKDD Explorations}, year = {2009}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {N. Andrienko and G. Andrienko} } @proceedings {87, title = {Interactive Visual Clustering of Large Collections of Trajectories}, journal = {IEEE Visual Analytics Science and Technology}, year = {2009}, abstract = {One of the most common operations in exploration and analysis of various kinds of data is clustering, i.e. discovery and interpretation of groups of objects having similar properties and/or behaviors. In clustering, objects are often treated as points in multi-dimensional space of properties. However, structurally complex objects, such as trajectories of moving entities and other kinds of spatiotemporal data, cannot be adequately represented in this manner. Such data require sophisticated and computationally intensive clustering algorithms, which are very hard to scale effectively to large datasets not fitting in the computer main memory. We propose an approach to extracting meaningful clusters from large databases by combining clustering and classification, which are driven by a human analyst through an interactive visual interface.}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, url = {http://visualanalytics.de/sites/default/files/upload/publications/vast09.pdf}, author = {G. Andrienko and N. Andrienko and S. Rinzivillo and M. Nanni and D. Pedreschi and F. Giannotti} } @proceedings {80, title = {Iterative Integration of Visual Insights during Patent Search and Analysis}, journal = {IEEE Symposium on Visual Analytics Science and Technology}, year = {2009}, abstract = {Patents are an important economic factor in today{\textquoteright}s globalized markets. Therefore, the analysis of patent information has become an inevitable task for a variety of interest groups. The retrieval of relevant patent information is an integral part of almost every patent analysis scenario. Unfortunately, the complexity of patent material inhibits a straightforward retrieval of all relevant patent documents and leads to iterative, time-consuming approaches in practice. With {\textquoteleft}PatViz{\textquoteright}, a new system for interactive analysis of patent information has been developed to leverage iterative query refinement. PatViz supports users in building complex queries visually and in exploring patent result sets interactively. Thereby, the visual query module introduces an abstraction layer that provides uniform access to different retrieval systems and relieves users of the burden to learn different complex query languages. By establishing an integrated environment it allows for interactive reintegration of insights gained from visual result set exploration into the visual query representation. We expect that the approach we have taken is also suitable to improve iterative query refinement in other Visual Analytics systems.}, keywords = {[Project Phase 1] Scalable Visual Patent Analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/koch.pdf}, author = {S. Koch and H. Bosch and M. Giereth and T. Ertl} } @conference {82, title = {Micro-Macro Views for Visual Trajectory Cluster Analysis}, booktitle = {Eurographics/IEEE Symposium on Visualization (EuroVis)}, year = {2009}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/eurovis09posterabstract.pdf}, author = {J. Bernard and T. von Landesberger and S. Bremm and T. Schreck} } @proceedings {99, title = {Mutation tagging with gene identifiers applied to membrane protein stability prediction}, journal = {BMC Bioinformatics}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {R. Winnenburg and C. Plake and M. Schroeder} } @proceedings {91, title = {Network compression as a quality measure for protein interaction networks}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {L. Royer and A. F. Stewart and M. Schroeder} } @proceedings {58, title = {A novel algorithm for detecting differentially regulated paths based on Gene Set Enrichment Analysis}, journal = {Bioinformatics}, year = {2009}, abstract = {Motivation: Deregulated signaling cascades are known to play a crucial role in many pathogenic processes, among them are tumor initiation and progression. In the recent past, modern experimental techniques that allow for measuring the amount of mRNA transcripts of almost all known human genes in a tissue or even in a single cell have opened new avenues for studying the activity of the signaling cascades and for understanding the information flow in the networks. Results: We present a novel dynamic programming algorithm for detecting deregulated signaling cascades. The so-called FiDePa (Finding Deregulated Paths) algorithm interprets differences in the expression profiles of tumor and normal tissues. It relies on the wellknown gene set enrichment analysis (GSEA) and efficiently detects all paths in a given regulatory or signaling network that are significantly enriched with differentially expressed genes or proteins. Since our algorithm allows for comparing a single tumor expression profile with the control group, it facilitates the detection of specific regulatory features of a tumor that may help to optimize tumor therapy. To demonstrate the capabilities of our algorithm, we analyzed a glioma expression dataset with respect to a directed graph that combined the regulatory networks of the KEGG and TRANSPATH database. The resulting glioma consensus network that encompasses all detected deregulated paths contained many genes and pathways that are known to be key players in glioma or cancer-related pathogenic processes. Moreover, we were able to correlate clinically relevant features like necrosis or metastasis with the detected paths. Availability: C++ source code is freely available, BiNA can be downloaded from http://www.bnplusplus.org/. Contact: ack@bioinf.uni-sb.de Supplementary information: Supplementary data are available at Bioinformatics online.}, keywords = {[Project Phase 1] New techniques for the interactive navigation visualization and analysis of heterogeneous biological networks}, url = {http://visualanalytics.de/sites/default/files/upload/publications/FiDePa.pdf}, author = {A. Keller and C. Backes and A. Gerasch and M. Kaufmann and O. Kohlbacher and H. Lenhof} } @proceedings {57, title = {On open problems in biological network visualization}, journal = {Proceedings of the International Symposium on Graph Drawing}, year = {2009}, abstract = {Much of the data created and analyzed by the so-called life sciences (i.e. biochemistry, botany, cell biology, genetics, molecular biology, and biology) can be interpreted and represented by graphs. Many general as well as special purpose graph drawing tools and libraries for the layout and drawing of graphs are available, but they are either not adequate for handling large graphs or do not adhere to the general drawing conventions and recognized layouts of biological networks. In this paper we describe some representative use cases that are required for presenting, exploring, curating, and comparing graphs in bioinformatics.}, keywords = {[Project Phase 1] New techniques for the interactive navigation visualization and analysis of heterogeneous biological networks}, url = {http://visualanalytics.de/sites/default/files/upload/publications/BiologyProblems.pdf}, author = {M. Albrecht and A. Kerren and K. Klein and O. Kohlbacher and P. Mutzel and W. Paul and F. Schreiber and M. Wybrow} } @proceedings {63, title = {Perzeptuell motivierte illustrative Darstellungsstile f{\"u}r komplexe Modelle}, journal = {Proc. of Mensch \& Computer Workshop}, year = {2009}, abstract = {Illustrationen werden erfolgreich in den Ingenieurwissenschaften, den Naturwissenschaften und der Medizin zur abstrahierten Darstellung von Objekten und Situationen verwendet. Typischerweise sind diese Illustrationen Zeichnungen, bei denen der Illustrator k{\"u}nstlerische Techniken zur Betonung relevanter Aspekte der Objekte einsetzt. Im Gegensatz dazu erzeugen Visualisierungen eine direkte, nicht abstrahierte visuelle Darstellung von Simulationen, gescannten Objekten oder modellierten Daten. Durch die inh{\"a}rente Komplexit{\"a}t dieser Datens{\"a}tze stellt sich die Interpretation dieser Daten jedoch oft als schwierig dar. Die illustrative Visualisierung hingegen versucht beide Ans{\"a}tze zur einer abstrahierten Darstellung eines Datensatzes zu verbinden, in der die wesentlichen Charakteristika betont werden. Dieser Ansatz bekommt eine besondere Bedeutung bei sehr komplexen Modellen, die u.U. aus vielen einzelnen Objekten bestehen, wie z.B. einzelne Bauteile einer Maschine, oder segmentierten Organen aus einem CT- oder MRT-Datensatz eines Menschen. W{\"a}hrend im Allgemeinen die illustrative Visualisierung einer bessere Betonung ausgew{\"a}hlter und relevanter Informationen als die traditionelle Visualisierung erreicht, so stellen viele nah beieinander gelegene Objekte eine Herausforderung dar, da sie klar von einander getrennt werden m{\"u}ssen.}, keywords = {[Project Phase 1] Visual Analytics for Large and heterogeneous Life Science data with emphasis on expression data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/salah2009-mcOP.pdf}, author = {S. Salah and D. Cunningham and D. Bartz} } @proceedings {85, title = {Quality-Based Visualization Matrices}, journal = {Vision Modeling Visualization Workshop (VMV 2009)}, year = {2009}, abstract = {Parallel coordinates and scatterplot matrices are widely used to visualize multi-dimensional data sets. But these visualization techniques are insufficient when the number of dimensions grows. To solve this problem, different approaches to preselect the best views or dimensions have been proposed in the last years. However, there are still several shortcomings to these methods. In this paper we present three new methods to explore multivariate data sets: a parallel coordinates matrix, in analogy to the well-known scatterplot matrix, a classbased scatterplot matrix that aims at finding good projections for each class pair, and an importance aware algorithm to sort the dimensions of scatterplot and parallel coordinates matrices.}, keywords = {[Project Phase 1] Exhaustive visual search for information in multi-dimensional data sets}, url = {http://visualanalytics.de/sites/default/files/upload/publications/vmv2009_albuquerque.pdf}, author = {G. Albuquerque and M. Eisemann and D. J. Lehmann and H. Theisel and M. Magnor} } @article {37, title = {Spatiotemporal Analysis of Sensor Logs Using Growth-Ring Maps}, journal = {IEEE Transactions on Computer Graphics and Visualization}, volume = {15}, year = {2009}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, author = {P. Bak and Mansmann, F. and Jantzko, H. and D.A. Keim} } @proceedings {95, title = {SuperCYP: a comprehensive database on Cytochrome P450 enzymes including a tool for analysis of CYP-drug interactions}, journal = {Nucleic Acids Research}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {S. Preissner and K. Kroll and M. Dunkel and C. Senger and G. Goldsobel and D. Kuzman and S. Guenther and R. Winnenburg and M. Schroeder and R. Preissner} } @conference {graphmotivsvmv2009, title = {A System for Interactive Visual Analysis of Large Graphs Using Motifs in Graph Editing and Aggregation}, booktitle = {Vision Modeling Visualization Workshop (VMV 2009) (accepted)}, year = {2009}, abstract = {Network analysis is an important task in a wide variety of application domains including analysis of social, financial, or transportation networks, to name a few. The appropriate visualization of graphs may reveal useful insight into relationships between network entities and subnetworks. However, often further algorithmic analysis of network structures is needed. In this paper, we propose a system for effective visual analysis of graphs which supports multiple analytic tasks. Our system enhances any graph layout algorithm by an analysis stage which detects predefined or arbitrarily specified subgraph structures (motifs). These motifs in turn are used to filter or aggregate the given network, which is particularly useful for search and analysis of interesting structures in large graphs. Our approach is fully interactive and can be iteratively refined, supporting analysis of graph structures at multiple levels of abstraction. Furthermore, our system supports the analysis of data- or user-driven graph dynamics by showing the implications of graph changes on the identified subgraph structures. The interactive facilities may be flexibly combined for gaining deep insight into the network structures for a wide range of analysis tasks. While we focus on directed, weighted graphs, the proposed tools can be easily extended to undirected and unweighted graphs. The usefulness of our approach is demonstrated by application on a phone call data set.
}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/MotifPaper2009.pdf}, author = {T. von Landesberger and M. G{\"o}rner and R. Rehner and T. Schreck} } @conference {56, title = {Towards Reliable Traffic Sign Recognition}, booktitle = {Proceedings of IEEE Intelligent Vehicles Symposium {\textquoteright}09}, year = {2009}, abstract = {The demand for reliable traffic sign recognition (TSR) increases with the development of safety driven advanced driver assistance systems (ADAS). Emerging technologies like brake-by-wire or steer-by-wire pave the way for collision avoidance and threat identification systems. Obviously, decision making in such critical situations requires high reliability of the information base. Especially for comfort systems, we need to take into account that the user tends to trust the information provided by the ADAS. In this paper, we present a robust system architecture for the reliable recognition of circular traffic signs. Our system employs complementing approaches for the different stages of current TSR systems. This introduces the application of local SIFT features for content-based traffic sign detection along with widely applied shape-based approaches. We further add a technique called contracting curve density (CCD) to refine the localization of the detected traffic sign candidates and therefore increase the performance of the subsequent classification module. Finally, the recognition stage based on SIFT and SURF descriptions of the candidates executed by a neural net provides a robust classification of structured image content like traffic signs. By applying these steps we compensate the weaknesses of the utilized approaches, and thus, improve the system{\textquoteright}s performance.}, keywords = {[Project Phase 1] Scalable Visual Analytics of Video Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Hoeferlin2009.pdf}, author = {B. H{\"o}ferlin and K. Zimmermann} } @proceedings {94, title = {Triangle network motifs predict complexes by complementing high-error interactomes with structural information}, journal = {BMC Bioinformatics}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {B. Andreopoulos and C. Winter and D. Labudde and M. Schroeder} } @proceedings {74, title = {An unconstrained multiphase thresholding approach for image segmentation}, journal = {Second International Conference on Scale Space Methods and Variational Methods in Computer Vision}, volume = {5567}, year = {2009}, pages = {26-37}, abstract = {In this paper we provide a method to nd global minimizers of certain non-convex 2-phase image segmentation problems. This is achieved by formulating a convex minimization problem whose minimizers are also minimizers of the initial non-convex segmentation problem, similar to the approach proposed by Nikolova, Esedoglu and Chan. The key di erence to the latter model is that the new model does not involve any constraint in the convex formulation that needs to be respected when minimizing the convex functional, neither explicitly nor by an arti cial penalty term. This approach is related to recent results by Chambolle. Eliminating the constraint considerably simpli es the computational dif- culties, and even a straightforward gradient descent scheme leads to a reliable computation of the global minimizer. Furthermore, the model is extended to multiphase segmentation along the lines of Vese and Chan. Numerical results of the model applied to the classical piecewise constant Mumford-Shah functional for two, four and eight phase segmentation are shown.}, keywords = {[Project Phase 1] Variational Methods for Model-based Interactive Analysis of Flows}, url = {http://visualanalytics.de/sites/default/files/upload/publications/paper.pdf}, author = {B. Berkels} } @conference {55, title = {Uncovering Interaction Patterns in Mobile Outdoor Gaming}, booktitle = {2009 International Conference on Advanced Geographic Information Systems \& Web Services}, year = {2009}, abstract = {Significant advances in recreation planning have been achieved thanks to the mobile technology and the ubiquitous computation. Today it is possible to know the real time position of a group of individuals participating in an outdoor game, and to obtain a large amount of data about their movements. However, most analyses have focused onindividual movements based on trajectories. In this paper we present a novel form of conceptualising and analysing human movement, based on a metaphor we have called "movement as interaction" which conceives movement as a result of interaction between individuals, collectives and the environment. The implementation of the proposed approach has enabled us to uncover interaction patterns in a group of children participating in an outdoor game based on mobile technology. The first results demonstrate the feasibility of our approach to detect game interactions.}, keywords = {[Project Phase 1] Visual Analytics methods to support the spatiotemporal analysis of movements in a physical space in particular in a geographical space}, isbn = {978-0-7695-3527-2}, author = {D. Orellana and M. Wachowicz and N. Andrienko and G. Andrienko} } @proceedings {98, title = {A User-Centered Evaluation Framework for the Sealife Semantic Web Browsers}, journal = {BMC Bioinformatics}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {H. Oliver and G. Diallo and E. de Quincey and P. Kostkova and G. Jawaheer and D. Alexopolou and B. Habermann and R. Stevens and S. Jupp and K. Khelif and M. Schroeder and G. Madle} } @booklet {90, title = {VAST Challenge Awards at VisWeek 2009 / Atlantic City}, year = {2009}, author = {P. Bak and C. Rohrdantz and S. Leifert and C. Granacher and S. Koch and S. Butscher and P. Jungk and D.A. Keim and H. Bosch and J. Heinrich and B. H{\"o}ferlin and M. H{\"o}ferlin and S. Koch and C. M{\"u}ller and G. Reina and M. W{\"o}rner} } @proceedings {83, title = {Visual Analysis of Graphs with Multiple Connected Components}, journal = {IEEE Symposium on Visual Analytics Science and Technology (VAST 2009)}, year = {2009}, keywords = {[Project Phase 1] Visual feature space analysis}, author = {T. von Landesberger and M. G{\"o}rner and T. Schreck} } @proceedings {183, title = {Visual Analysis of Cerebral Perfusion Data -- Four Interactive Approaches and a Comparison}, journal = {Proc. of the 6th International Symposium on Image and Signal Processing and Analysis (ISPA)}, year = {2009}, pages = {588-595}, keywords = {[Project Phase 1] Efficient Visual Analysis of Dynamic Medical Image Data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Visual Analysis of Cerebral Perfusion Data -- Four Interactive Approaches and a Comparison.pdf}, author = {S. Oeltze and H. Hauser and J. Rorvik and A. Lundervold and B. Preim} } @mastersthesis {457, title = {Visual Analysis of Information Spaces using Topological Landscapes}, year = {2009}, keywords = {[Project Phase 2] Topology-based Visual Analysis of Information Spaces}, author = {Oesterling, P.} } @proceedings {62, title = {A Visual Analytics Approach for Gene Expression Data}, journal = {IEEE Symposium on Visual Analytics Science and Technology}, year = {2009}, abstract = {We present a new application, SpRay, designed for the visual exploration of gene expression data. It is based on an extension and adaption of parallel coordinates to support the visual exploration of large and high-dimensional datasets. In particular, we investigate the visual analysis of gene expression data as generated by microarray experiments; We combine refined visual exploration with statistical methods to a visual analytics approach that proved to be particularly successful in this application domain. We will demonstrate the usefulness on several multidimensional gene expression datasets from different bioinformatics applications.}, keywords = {[Project Phase 1] Visual Analytics for Large and heterogeneous Life Science data with emphasis on expression data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/dietzsch2009-vast.pdf}, author = {J. Dietzsch and J. Heinrich and K. Nieselt and D. Bartz} } @proceedings {81, title = {Visual Analytics of Time Dependent 2D Point Clouds}, journal = {EG Computer Graphics International (CGI)}, year = {2009}, address = {Victoria, Canada}, abstract = {Two dimensional point data can be considered one of the most basic, yet one of the most ubiquitous data types arising in a wide variety of applications. The basic scatter plot approach is widely used and highly effective for data sets of small to moderate size. However, it shows scalability problems for data sets of increasing size, of multiple classes and of time-dependency. In this short paper, we therefore present an improved visual analysis of such point clouds. The basic idea is to monitor certain statistical properties of the data for each point and for each class as a function of time. The output of the statistic analysis is used for identification of interesting data views decreasing information overload. The data is interactively visualized using various techniques. In this paper, we specify the problem, detail our approach, and present application results based on a real world data set.}, keywords = {[Project Phase 1] Visual feature space analysis}, url = {http://visualanalytics.de/sites/default/files/upload/publications/cgi09.pdf}, author = {T. von Landesberger and S. Bremm and P. Rezaei and T. Schreck} } @proceedings {235, title = {Visual Support for the Understanding of Simulation Processes}, journal = {Proceedings of the IEEE Pacific Visualization Symposium (PacificVis{\textquoteright}09)}, year = {2009}, address = {Beijing, China}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, url = {http://visualanalytics.de/sites/default/files/upload/publications/Unger_PacificVis09.pdf}, author = {A. Unger and H. Schumann} } @proceedings {61, title = {Visuelle Analytik f{\"u}r Genexpressionsdaten}, journal = {Datenbank-Spektrum }, year = {2009}, abstract = {Microarrays oder DNA-Chips sind eine der erfolgreichsten Technologien zur Genexpressionsanalyse, die in den letzten Jahren Einzug in die Molekularbiologie und Medizin gehalten haben. Bei der Datenauswertung im Rahmen der Microarray-Analyse besteht aber nach wie vor ein gro{\ss}er Bedarf an sowohl benutzerfreundlicher, als auch leistungsf{\"a}higer Software, die den schnelllebigen Technologiespr{\"u}ngen und wachsenden Datenumf{\"a}ngen Rechnung tr{\"a}gt. Bei der Analyse von Microarray-Daten spielen dabei die automatische Auswertung und die visuelle Exploration eine wichtige Rolle. Mit SpRay wurde ein Werkzeug geschaffen, das f{\"u}r die Exploration und Analyse derartiger Daten ausgelegt ist. Zentrale Visualisierung ist eine Adaption und Erweiterung der parallelen Koordinaten und der Heatmap. SpRay bietet eine visuelle Analyse sowohl von Original- als auch automatisch abgeleiteten (statistischen) Daten in einem gemeinsamen Visual-Analytics-Datenraum. Anhand einiger Anwendungsbeispiele aus verschiedenen Microarray-Studien wird die Zweckm{\"a}{\ss}igkeit von SpRay demonstriert.}, keywords = {[Project Phase 1] Visual Analytics for Large and heterogeneous Life Science data with emphasis on expression data}, url = {http://visualanalytics.de/sites/default/files/upload/publications/nieselt2009-dbspektrum.pdf}, author = {K. Nieselt and J. Dietzsch and J. Heinrich and A. Pritzkau and M. Mosisch and D. Bartz} } @proceedings {93, title = {Whole blood genome-wide expression profiling of A3243G MELAS patients reveals alternative disease-modifying gene clusters}, year = {2009}, keywords = {[Project Phase 1] Zoomable Cell}, author = {S. Mende and A. Herr and J. Schmiedel and M. Deschauer and T. Klopstock and V. S. Kostic and L. Royer and M. Schroeder and H. Reichmann and A. Storch} } @proceedings {236, title = {An Algorithm Selection Approach for Simulation Systems}, journal = {Proc. ACM/IEEE/SCS Workshop on Principles of Advanced and Distributed Simulation PADS{\textquoteright}08}, year = {2008}, publisher = {IEEE Computer Society}, address = {Rome, Italy}, keywords = {[Project Phase 2] Developing new visual analysis methods to be integrated into simulation processes focusing on the exploration of cell biological systems in space and time}, author = {R. Ewald and J. Himmelspach and A. Uhrmacher} } @article {19099609, title = {GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments}, journal = {BMC Bioinformatics}, volume = {9}, number = {1}, year = {2008}, pages = {552}, abstract = {BACKGROUND:High-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline.RESULTS:Here, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms.CONCLUSION:Our gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.
}, keywords = {[Project Phase 1] New techniques for the interactive navigation visualization and analysis of heterogeneous biological networks}, issn = {1471-2105}, doi = {10.1186/1471-2105-9-552}, url = {http://visualanalytics.de/sites/default/files/upload/publications/GeneTrailExpress.pdf}, author = {A. Keller and C. Backes and M. Al-Awadhi and A. Gerasch and J. Kuntzer and O. Kohlbacher and M. Kaufmann and H. Lenhof} }