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Dagstuhl Seminar 10471

Scalable Visual Analytics

( Nov 21 – Nov 26, 2010 )

(Click in the middle of the image to enlarge)

Permalink
Please use the following short url to reference this page: https://www.dagstuhl.de/10471

Organizers

Contact


Schedule

Memorandum

We are very sad to learn that James J. Thomas passed suddenly away on August, 6th, 2010.
Web-Page of the NVAC in his memory:
nvac.pnl.gov/


Summary

The goal of the seminar was to bring together the participants of the DFG strategic research initiative SPP 1335 "Scalable Visual Analytics: Interactive Visual Analysis Systems for Complex Information Spaces" and international members of the visual analytics community. Topics addressed include the analysis of bio-molecular data, spatio-temporal data, document analysis, and streaming data.

The different scenarios had in common that approaches which work either on a purely analytical or on a purely visual level do not help due to the dynamics and complexity of the underlying processes or due to intelligent opponents. During the seminar, the participants did not only present each other the status of their own work but also discussed more general issues that are common to all projects. This includes the evaluation of visual analytics approaches, building up suitable infrastructures to improve dissemination and re-usability of the results, or aspects of cognitive science that are critical for effective user-centric analysis processes. Furthermore, special interest groups were formed to encourage and foster joint projects and collaborations.

The Scalable Visual Analytics seminar was a fertile meeting in which researchers from diverse backgrounds met. It included industry and academia, senior and junior researchers, multi-national representation, and people coming from several disciplines. The diversity resulted in interesting and useful discussions, which will help to shape the future of the versatile research area of Visual Analytics.

The seminar included multiple presentations and discussions which helped to exchange domain knowledge and steer future research activities. Besides, several working groups during the seminar not only identified future research directions in the field of scalable visual analytics but also initiated new joint projects. In total, plans for three position papers, two overview papers to outreach to other communities, and three EU FET Open Projects were drafted. Furthermore, three workshops as satellites of conferences that cover specific application areas were planned to further disseminate the work and provide a platform for ongoing discussions and activities.

This seminar clearly illustrated the diversity, relevance, and fertility of the topics within the field of Visual Analytics. The intensity of the participants' involvement is a clear indication that the interactions fostered by the seminar will generate significant follow-up research, and eventually lead to practical use of Visual Analytics as well. All participants of the seminar were encouraged to reference Dagstuhl in future activities that were conceived during the seminar; in particular, the papers if accepted will contain acknowledgments of their inception during the Dagstuhl seminar.


Participants
  • Georgia Albuquerque (TU Braunschweig, DE)
  • Gennady Andrienko (Fraunhofer IAIS - St. Augustin, DE) [dblp]
  • Natalia V. Andrienko (Fraunhofer IAIS - St. Augustin, DE) [dblp]
  • Loretta Auvil (University of Illinois at Urbana Champaign, US) [dblp]
  • Peter Bak (IBM - Haifa, IL)
  • Benjamin Berkels (Universität Bonn, DE) [dblp]
  • Enrico Bertini (Universität Konstanz, DE) [dblp]
  • Susanne Boll (Universität Oldenburg, DE) [dblp]
  • Sven Böttger (TU Kaiserslautern, DE)
  • Sebastian Bremm (TU Darmstadt, DE)
  • Achim Ebert (TU Kaiserslautern, DE) [dblp]
  • Thomas Ertl (Universität Stuttgart, DE) [dblp]
  • Jean-Daniel Fekete (University of Paris South XI, FR) [dblp]
  • Brian D. Fisher (Simon Fraser University - Surrey, CA) [dblp]
  • Andreas Gerasch (Universität Tübingen, DE)
  • Joachim Giesen (Universität Jena, DE) [dblp]
  • Carsten Görg (University of Colorado - Aurora, US) [dblp]
  • Hans Hagen (TU Kaiserslautern, DE) [dblp]
  • Gunther Heidemann (Universität Stuttgart, DE)
  • Gerhard Heyer (Universität Leipzig, DE) [dblp]
  • Markus Höferlin (Universität Stuttgart, DE)
  • Halldor Janetzko (Universität Konstanz, DE) [dblp]
  • Charles Jochim (Universität Stuttgart, DE)
  • Michael Kaufmann (Universität Tübingen, DE) [dblp]
  • Daniel A. Keim (Universität Konstanz, DE) [dblp]
  • Andreas Kerren (Linnaeus University - Växjö, SE) [dblp]
  • Steffen Koch (Universität Stuttgart, DE) [dblp]
  • Oliver Kohlbacher (Universität Tübingen, DE) [dblp]
  • Jörn Kohlhammer (Fraunhofer Institut - Darmstadt, DE) [dblp]
  • Dirk J. Lehmann (Universität Magdeburg, DE)
  • Hans-Peter Lenhof (Universität des Saarlandes, DE) [dblp]
  • Peter Liggesmeyer (TU Kaiserslautern, DE) [dblp]
  • Marcus A. Magnor (TU Braunschweig, DE) [dblp]
  • Florian Mansmann (Universität Konstanz, DE)
  • Richard May (Pacific Northwest National Lab. - Richland, US)
  • Arturas Mazeika (MPI für Informatik - Saarbrücken, DE)
  • Silvia Miksch (TU Wien, AT) [dblp]
  • Heinrich Müller (TU Dortmund, DE)
  • Kay Katja Nieselt (Universität Tübingen, DE) [dblp]
  • Daniela Oelke (Universität Konstanz, DE) [dblp]
  • Axel Platz (Siemens AG - München, DE)
  • Margit Pohl (TU Wien, AT) [dblp]
  • Bernhard Preim (Universität Magdeburg, DE) [dblp]
  • Waqar Saleem (Universität Jena, DE)
  • Gerik Scheuermann (Universität Leipzig, DE) [dblp]
  • Tobias Schreck (Universität Konstanz, DE) [dblp]
  • Michael Schroeder (TU Dresden, DE)
  • Heidrun Schumann (Universität Rostock, DE) [dblp]
  • Hinrich Schütze (Universität Stuttgart, DE) [dblp]
  • Marcel Spehr (TU Dresden, DE)
  • David Spretke (Universität Konstanz, DE)
  • Holger Theisel (Universität Magdeburg, DE) [dblp]
  • Klaus-Dietz Tönnies (Universität Magdeburg, DE)
  • Daniel Weiskopf (Universität Stuttgart, DE) [dblp]
  • Stefan Wrobel (Fraunhofer IAIS - St. Augustin, DE) [dblp]

Classification
  • artificial intelligence / robotics
  • computer graphics / computer vision
  • data bases / information retrieval
  • data structures / algorithms / complexity
  • society / HCI

Keywords
  • Visual Analytics
  • Visualization
  • Data Analysis
  • Discovery Science
  • Information Visualization