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Solving Problems with Visual Analytics
Author(s) -
Jörn Kohlhammer,
Daniel A. Keim,
Margit Pohl,
Giuseppe Santucci,
Gennady Andrienko
Publication year - 2011
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2011.12.035
Subject(s) - visual analytics , computer science , analytics , cultural analytics , data science , variety (cybernetics) , thematic analysis , data analysis , session (web analytics) , software analytics , semantic analytics , human–computer interaction , perception , interactive visual analysis , visualization , world wide web , artificial intelligence , qualitative research , data mining , software , psychology , social science , software system , data web , sociology , web service , software construction , programming language , neuroscience
Visual analytics is an emerging research discipline aiming at making the best possible use of huge information loads in a wide variety of applications by appropriately combining the strengths of intelligent automatic data analysis with the visual perception and analysis capabilities of the human user. The major goal of visual analytics is the integration of these disciplines into visual analytics to acquire well-established and agreed upon concepts and theories, combining scientific breakthroughs in a single discipline to have a potential impact on visual analytics and vice versa. In a session at FET11, the leaders of the thematic working groups of the recently finalised FET Open coordination action VisMaster CA presented the scientific challenges that were identified in the visual analytics research roadmap, and the connection between the various disciplines and the broader vision of visual analytics. This article contains excerpts from this research roadmap to motivate further research in this direction within FET

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