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About 10,000 papers for “Visual analytics”

Visual analytics

Keim, Daniel A., Kohlhammer, Jörn, Mansmann, Florian et al. · Fraunhofer-Publica (Fraunhofer-Gesellschaft) · 2010

S.7-18

Cited by 0

Visual Analytics

Pak Chung Wong, J. Joshua Thomas · IEEE Computer Graphics and Applications · 2004

The information revolution is upon us, and it is guaran-teed to change our lives and the way we conduct our daily business. The fact that we have to deal with not just the size but also the variety and complexity of this in-formation makes it a real challenge to survive the revolu-tion. Enter Visual Analytics, a contemporary and proven approach to combine the art of human intuition and the science of mathematical deduction to directly perceive patterns and derive knowledge and insight from them.

Cited by 214

Visual Analytics

Rauhöft, Greg · Fraunhofer-Publica (Fraunhofer-Gesellschaft) · 2019

21 Folien

Cited by 0

Visual analytics

Suresh K. Bhavnani, Jeremy L. Warner, Sandra S. Hatch · Elsevier eBooks · 2023

Cited by 0

Visual Analytics

Brian Fisher, Joseph Kielman, W. Bradford Paley et al. · 2014

Cited by 0

Visual Analytics

Fisher, Brian, Kielman, Joseph, Paley, W. Bradley et al. · eScholarship (California Digital Library) · 2009

Cited by 0Open access

Visual Analytics

Fisher, Brian, Kielman, Joseph, Paley, W. Bradley et al. · eScholarship (California Digital Library) · 2009

Cited by 0Open access

Visual Analytics

Tuscher, Michaela, Bögl, Markus · reposiTUm (TU Wien) · 2025

Cited by 0Open access

Visual analytics

Natalia Andrienko, Gennady Andrienko · 2017

Visual analytics aims to combine the strengths of human and computer data processing. Visualization, whereby humans and computers cooperate through graphics, is the means through which this is achieved. Sophisticated synergies are required for analyzing spatio-temporal data and solving spatio-temporal problems. It is necessary to take into account the specifics of the geographic space, time, and spatio-temporal phenomena and processes.

Cited by 0

Visual Analytics

Gennady Andrienko, Natalia Andrienko, Daniel Keim et al. · 2014

Copyright & reuse City University London has developed City Research Online so that its users may access the research outputs of City University London's staff. Copyright © and Moral Rights for this paper are retained by the individual author(s) and / or other copyright holders. All material in City Research Online is checked for eligibility for copyright before being made available in the live archive. URLs from City Research Online may be freely distributed and linked to from other web pages. Versions of research The version in City Research Online may differ from the final published version. Users are advised to check the Permanent City Research Online URL above for the status of the paper. Enquiries If you have any enquiries about any aspect of City Research Online, or if you wish to make contact with the author(s) of this paper, please email the team at publications@city.ac.uk.Challenging Problems of Geospatial

Cited by 0

Visual analytics

Keim, Daniel A., Andrienko, Gennady, Fekete, J.-D. et al. · Fraunhofer-Publica (Fraunhofer-Gesellschaft) · 2008

S.154-175

Cited by 0

Visual Analytics

Daniel A. Keim, Florian Mansmann, Andreas Stoffel et al. · Encyclopedia of Database Systems · 2009

Cited by 35

Visual analytics

Keim, Daniel A., Kohlhammer, Jörn, Mansmann, Florian et al. · Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) · 2010

Visual analytics is not easy to define, due to its multi-disciplinary nature involving multiple processes and the wide variety of application areas. An early definition was "the science of analytical reasoning facilitated by interactive human-machine interfaces". However, based on current practice, a more specific definition would be: "Visual analytics combines automated Visual analytics combines automated analysis with interactive visualisations analysis techniques with interactive visualisations for an effctive understanding, reasoning and decision making on the basis of very large and complex datasets". So, in terms of the goal of visual analytics, we can elaborate on this definition to state that visual analytics is the creation of tools and techniques to enable people to: - Synthesise information and derive insight from massive, dynamic, ambiguous, and often conflicting data. - Detect the expected and discover the unexpected. - Provide timely, defensible, and understandable assessments. - Communicate these assessment effectively for action

Cited by 0

Visual Analytics

Keim, Daniel A., Mansmann, Florian, Stoffel, Andreas et al. · KOPS (University of Konstanz) · 2008

Cited by 0Open access