License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.10471.2
URN: urn:nbn:de:0030-drops-29393
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2011/2939/
Go to the corresponding Portal

Keim, Daniel A. ; Wrobel, Stefan

10471 Executive Summary -- Scalable Visual Analytics

pdf-format:
10471.SWM.Other.2939.pdf (0.5 MB)

Abstract

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.

BibTeX - Entry

@InProceedings{keim_et_al:DagSemProc.10471.2,
  author =	{Keim, Daniel A. and Wrobel, Stefan},
  title =	{{10471 Executive Summary – Scalable Visual Analytics}},
  booktitle =	{Scalable Visual Analytics},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2011},
  volume =	{10471},
  editor =	{Daniel A. Keim and Stefan Wrobel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2011/2939},
  URN =		{urn:nbn:de:0030-drops-29393},
  doi =		{10.4230/DagSemProc.10471.2},
  annote =	{Keywords: Visual Analytics, Visualization, Data Analysis, Discovery Science, Information Visualization}
}

Keywords: Visual Analytics, Visualization, Data Analysis, Discovery Science, Information Visualization
Collection: 10471 - Scalable Visual Analytics
Issue Date: 2011
Date of publication: 01.02.2011

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI