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Scalable Set Visualizations (Dagstuhl Seminar 17332)

Authors: Yifan Hu, Luana Micallef, Martin Nöllenburg, and Peter Rodgers

Published in: Dagstuhl Reports, Volume 7, Issue 8 (2018)


Abstract
This report documents the program and outcomes of Dagstuhl Seminar 17332 "Scalable Set Visualizations", which took place August 14--18, 2017. The interdisciplinary seminar brought together 26 researchers from different areas in computer science and beyond such as information visualization, human-computer interaction, graph drawing, algorithms, machine learning, geography, and life sciences. During the seminar we had five invited overview talks on different aspects of set visualizations as well as a few ad-hoc presentations of ongoing work. The abstracts of these talks are contained in this report. Furthermore, we formed five working groups, each of them discussing intensively about a selected open research problem that was proposed by the seminar participants in an open problem session. The second part of this report contains summaries of the groups' findings.

Cite as

Yifan Hu, Luana Micallef, Martin Nöllenburg, and Peter Rodgers. Scalable Set Visualizations (Dagstuhl Seminar 17332). In Dagstuhl Reports, Volume 7, Issue 8, pp. 1-22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@Article{hu_et_al:DagRep.7.8.1,
  author =	{Hu, Yifan and Micallef, Luana and N\"{o}llenburg, Martin and Rodgers, Peter},
  title =	{{Scalable Set Visualizations (Dagstuhl Seminar 17332)}},
  pages =	{1--22},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2018},
  volume =	{7},
  number =	{8},
  editor =	{Hu, Yifan and Micallef, Luana and N\"{o}llenburg, Martin and Rodgers, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.7.8.1},
  URN =		{urn:nbn:de:0030-drops-84274},
  doi =		{10.4230/DagRep.7.8.1},
  annote =	{Keywords: algorithms, information visualization, scalability, set visualization, visual analytics}
}
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