Visual Analytics - Revision history

Paolofdr at 15:36, 19 June 2013

2013-06-19T15:36:49Z

@@ Line 29: / Line 29: @@
 * J.J. Thomas and K.A. Cook (Eds.), [http://nvac.pnl.gov/agenda.stm Illuminating the Path: The Research and Development Agenda for Visual Analytics]. IEEE Press, 2005.
 * Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis and Florian Mansmann (Eds.), [http://www.vismaster.eu/book/ Mastering the Information Age – Solving Problems with Visual Analytics], Eurographics Association, 2010.
-You saved me a lot of hsasle just now.
+=== Papers ===

86.96.226.20: /* Papers */

2012-11-23T07:43:42Z

Papers

← Older revision		Revision as of 07:43, 23 November 2012
Line 29:		Line 29:
	* J.J. Thomas and K.A. Cook (Eds.), [http://nvac.pnl.gov/agenda.stm Illuminating the Path: The Research and Development Agenda for Visual Analytics]. IEEE Press, 2005.		* J.J. Thomas and K.A. Cook (Eds.), [http://nvac.pnl.gov/agenda.stm Illuminating the Path: The Research and Development Agenda for Visual Analytics]. IEEE Press, 2005.
	* Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis and Florian Mansmann (Eds.), [http://www.vismaster.eu/book/ Mastering the Information Age – Solving Problems with Visual Analytics], Eurographics Association, 2010.		* Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis and Florian Mansmann (Eds.), [http://www.vismaster.eu/book/ Mastering the Information Age – Solving Problems with Visual Analytics], Eurographics Association, 2010.
	~~=== Papers ===~~		You saved me a lot of hsasle just now.
	* J.J. Thomas and K.A. Cook, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1573625 "A Visual Analytics Agenda,"] ''IEEE Computer Graphics & Applications'', vol. 26, pp. 10-13, 2006.
	* Pak Chung Wong and J. Thomas, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1333623 "Visual Analytics,"] ''IEEE Computer Graphics & Applications'', vol. 24, pp. 20-21, 2004.
	* Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melancon. 2008. [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual Analytics: Definition, Process, and Challenges."] In Information Visualization, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). Lecture Notes In Computer Science, Vol. 4950. Springer-Verlag, Berlin, Heidelberg 154-175
	* J. Thomas, [http://portal.acm.org/citation.cfm?id=1292429 "Visual analytics: a ~~grand challenge in science: turning information overload into the opportunity~~ of ~~the decade,"] ''Journal of Computing Sciences in Colleges'', vol. 23, pp. 5-6, 2007.~~

	Hi BobI don't think anybody (who knew of them in the first place) will have foetgtorn standards bodies like W3C or OASIS. Indeed for those of who work with XML, the W3C is of course the central source of most of the key specifications.Surely though quality is not an automatic facet of any particular body's work, but varies according to many factors: the people, the time, the politics, etc. So while W3C has given us some great technologies (XML 1.0, XSLT, MathML, and SVG to name but four) it has also given us some stinkers (e.g. XML Schema, the whole WS-* stack, and XML 1.1).I think it's interesting that often the blame for stinkiness can be traced squarely back to vendor influence. To take one tiny example: why did the W3C decide to count the (previously forbidden) NEL character as a line feed in XML 1.1, other than for reasons of compatibility with legacy IBM systems which (practically alone of their competitors) made use of this character? This was one of the disastrous moves that made such XML 1.1 instances incompatible with the entire installed base of XML 1.0 processors.XML 1.0 (which I think of as a clean, well-written spec) has attracted over 200 errata in its lifetime. At around 40 pages that's 5 errors per page. Do you think certain recent high-profile ISO/IEC standards are significantly more faulty than that?When you mention procurement, I take it you mean the procurement by nations. The major factor here is surely that nations lean towards international standards because they are international, not necessarily because of perceptions of superior quality. Being international means that they (the nations) ultimately can control the standardisation process. Vendor-driven consortiums perform a different function and are valued at a lesser worth accordingly: it's not technical, it's political.And if laws are to be re-visited and standards bodies judged, who is going to be doing the re-visiting and the judging? Ultimately it is a precept of international standardisation that the sovereign nations order their own affairs and yes sometimes this means vendors get upset. Ultimately we (the users) need the nations as they are the only entities powerful enough to bring today's huge corporations to heel. - Alex.

86.96.226.20: /* References */

2012-11-23T07:18:40Z

References

← Older revision		Revision as of 07:18, 23 November 2012
Line 35:		Line 35:
	* J. Thomas, [http://portal.acm.org/citation.cfm?id=1292429 "Visual analytics: a grand challenge in science: turning information overload into the opportunity of the decade,"] ''Journal of Computing Sciences in Colleges'', vol. 23, pp. 5-6, 2007.		* J. Thomas, [http://portal.acm.org/citation.cfm?id=1292429 "Visual analytics: a grand challenge in science: turning information overload into the opportunity of the decade,"] ''Journal of Computing Sciences in Colleges'', vol. 23, pp. 5-6, 2007.

	~~== References ==~~		Hi BobI don't think anybody (who knew of them in the first place) will have foetgtorn standards bodies like W3C or OASIS. Indeed for those of who work with XML, the W3C is of course the central source of most of the key specifications.Surely though quality is not an automatic facet of any particular body's work, but varies according to many factors: the people, the time, the politics, etc. So while W3C has given us some great technologies (XML 1.0, XSLT, MathML, and SVG to name but four) it has also given us some stinkers (e.g. XML Schema, the whole WS-* stack, and XML 1.1).I think it's interesting that often the blame for stinkiness can be traced squarely back to vendor influence. To take one tiny example: why did the W3C decide to count the (previously forbidden) NEL character as a line feed in XML 1.1, other than for reasons of compatibility with legacy IBM systems which (practically alone of their competitors) made use of this character? This was one of the disastrous moves that made such XML 1.1 instances incompatible with the entire installed base of XML 1.0 processors.XML 1.0 (which I think of as a clean, well-written spec) has attracted over 200 errata in its lifetime. At around 40 pages that's 5 errors per page. Do you think certain recent high-profile ISO/IEC standards are significantly more faulty than that?When you mention procurement, I take it you mean the procurement by nations. The major factor here is surely that nations lean towards international standards because they are international, not necessarily because of perceptions of superior quality. Being international means that they (the nations) ultimately can control the standardisation process. Vendor-driven consortiums perform a different function and are valued at a lesser worth accordingly: it's not technical, it's political.And if laws are to be re-visited and standards bodies judged, who is going to be doing the re-visiting and the judging? Ultimately it is a precept of international standardisation that the sovereign nations order their own affairs and yes sometimes this means vendors get upset. Ultimately we (the users) need the nations as they are the only entities powerful enough to bring today's huge corporations to heel. - Alex.
	*[Cook et al., ~~2007] Cook~~, ~~Kris; Earnshaw, Rae; Stasko, John, Guest Editors' Introduction~~: ~~Discovering~~ the ~~Unexpected~~, ~~''Computer Graphics and Applications''~~, ~~27(5):15-19, IEEE~~, ~~Sept~~.~~-Oct. 2007.~~
	*[Keim et al., ~~2006] Keim~~, D.A.~~; Mansmann~~, F. ~~and Schneidewind, J~~. ~~and Ziegler, H~~.~~, Challenges~~ in ~~Visual Data Analysis~~, ~~Proceedings~~ of ~~Information Visualization~~ (~~IV 2006~~)~~, IEEE, p~~. ~~9-16, 2006~~.
	*[Thomas and Cook, 2005] J.J. ~~Thomas and K~~.A. ~~Cook~~, ~~eds~~., ~~[http://nvac~~.~~pnl~~.~~gov/agenda.stm Illuminating the Path~~: ~~The Research and Development Agenda for Visual Analytics]~~, ~~IEEE CS Press, 2005~~.
	*[Thomas and ~~Cook~~, ~~2006] James J. Thomas~~ and ~~Kristin A~~. ~~Cook., ''IEEE Computer Graphics and Applications'', 26~~(1)~~:10~~-~~13, January/February, 2006~~.



	~~[[Category: Glossary]]~~

77.37.209.235: Undo revision 126609 by 86.96.226.18 (Talk)

2012-06-12T00:02:12Z

Undo revision 126609 by 86.96.226.18 (Talk)

← Older revision		Revision as of 00:02, 12 June 2012
Line 1:		Line 1:
	~~Great atricle~~, ~~thank you again~~ for ~~writing~~.		{{Definition\|'''Visual analytics''' is the science of analytical reasoning facilitated by interactive visual interfaces. [Thomas and Cook, 2005]}}

			{{Quotation\|People use visual analytics tools and techniques to synthesize 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; and communicate assessment effectively for action.
			<br>Visual analytics is a multidisciplinary field that includes the following focus areas:<br>
			*analytical reasoning techniques that let users obtain deep insights that directly support assessment, planning, and decision making;
			*visual representations and interaction techniques that exploit the human eye’s broad bandwidth pathway into the mind to let users see, explore, and understand large amounts of information simultaneously;
			*data representations and transformations that convert all types of conflicting and dynamic data in ways that support visualization and analysis; and
			*techniques to support production, presentation, and dissemination of analytical results to communicate information in the appropriate context to a variety of audiences.
			\|[Thomas and Cook, 2005, 2006]}}

			[[Image:Keim06visual-analytics-disciplines.png\|right\|thumb\|300px\|Visual analytics as a highly interdisciplinary field of research.<br>[Keim et al., 2006]]]
			{{Quotation\|'''Visual analytics''' is more than just visualization and can rather be seen as an integrated approach combining [[visualization]], [[human factors]] and [[data analysis]]. ... With respect to the field of [[visualization]], visual analytics integrates methodology from information analytics, geospatial analytics, and scientific analytics. Especially human factors (e.g., interaction, cognition, perception, collaboration, presentation, and dissemination) play a key role in the communication between human and computer, as well as in the decisionmaking process.\|[Keim et al., 2006]}}

			{{Quotation\|Visual analytics is the formation of abstract visual metaphors in combination with a human information discourse (usually some form of interaction) that enables detection of the expected and discovery of the unexpected within massive, dynamically changing information spaces. It is an outgrowth of the fields of scientific and information visualization but includes technologies from many other fields, including knowledge management, statistical analysis, cognitive science, decision science, and others.<br><br>This marriage of computation, visual representation, and interactive thinking supports intensive analysis. The goal is not only to permit users to detect expected events, such as might be predicted by models, but also to help users discover the unexpected—the surprising anomalies, changes, patterns, and relationships that are then examined and assessed to develop new insight.\|[Cook et al., 2007]}}

			== Related Links ==
			*[http://vadl.cc.gatech.edu/ Visual Analytics Digital Library]
			*[http://www.cs.umd.edu/hcil/semvast/ SEMVAST] Scientific Evaluation Methods for Visual Analytics Science and Technology - Resource on Visual Analytics Evaluation

			== Visual Analytics @ YouTube ==
			*[http://www.youtube.com/watch?v=5i3xbitEVfs March 15, 2010 — VisMaster - Mastering the Information Age] What is Visual Analytics and why is it important for Europe to fund Research in this new domain?
			*[http://www.youtube.com/watch?v=2CMw4i9DiaM December 16, 2008 — Jigsaw] Using visualization and visual analytics to help investigative analysis and sensemaking.
			*[http://www.youtube.com/watch?v=cVL2Y6nfGiM November 03, 2008 — Mikael Jern on Visual Analytics] Visual Analytics Center, OECD Explorer
			*[http://www.youtube.com/watch?v=5uGRGqCFryg July 10, 2007 — Why Visual Analytics? - A conversation] A series of interviews to some of most known people in Visual Analytics, the science of reasoning through visualization
			*[http://www.youtube.com/watch?v=m_TQZwYL7MY December 12, 2006 — Visual Analytics Show segment from "BusinessNOW" on Maryland Public Television]

			== Basic Literature ==
			=== Books ===
			* J.J. Thomas and K.A. Cook (Eds.), [http://nvac.pnl.gov/agenda.stm Illuminating the Path: The Research and Development Agenda for Visual Analytics]. IEEE Press, 2005.
			* Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis and Florian Mansmann (Eds.), [http://www.vismaster.eu/book/ Mastering the Information Age – Solving Problems with Visual Analytics], Eurographics Association, 2010.
			=== Papers ===
			* J.J. Thomas and K.A. Cook, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1573625 "A Visual Analytics Agenda,"] ''IEEE Computer Graphics & Applications'', vol. 26, pp. 10-13, 2006.
			* Pak Chung Wong and J. Thomas, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1333623 "Visual Analytics,"] ''IEEE Computer Graphics & Applications'', vol. 24, pp. 20-21, 2004.
			* Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melancon. 2008. [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual Analytics: Definition, Process, and Challenges."] In Information Visualization, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). Lecture Notes In Computer Science, Vol. 4950. Springer-Verlag, Berlin, Heidelberg 154-175
			* J. Thomas, [http://portal.acm.org/citation.cfm?id=1292429 "Visual analytics: a grand challenge in science: turning information overload into the opportunity of the decade,"] ''Journal of Computing Sciences in Colleges'', vol. 23, pp. 5-6, 2007.

			== References ==
			*[Cook et al., 2007] Cook, Kris; Earnshaw, Rae; Stasko, John, Guest Editors' Introduction: Discovering the Unexpected, ''Computer Graphics and Applications'', 27(5):15-19, IEEE, Sept.-Oct. 2007.
			*[Keim et al., 2006] Keim, D.A.; Mansmann, F. and Schneidewind, J. and Ziegler, H., Challenges in Visual Data Analysis, Proceedings of Information Visualization (IV 2006), IEEE, p. 9-16, 2006.
			*[Thomas and Cook, 2005] J.J. Thomas and K.A. Cook, eds., [http://nvac.pnl.gov/agenda.stm Illuminating the Path: The Research and Development Agenda for Visual Analytics], IEEE CS Press, 2005.
			*[Thomas and Cook, 2006] James J. Thomas and Kristin A. Cook., ''IEEE Computer Graphics and Applications'', 26(1):10-13, January/February, 2006.



			[[Category: Glossary]]

86.96.226.18: LmndCHUTrir

2012-05-31T16:30:00Z

LmndCHUTrir

← Older revision		Revision as of 16:30, 31 May 2012
Line 1:		Line 1:
	~~{{Definition\|'''Visual analytics''' is the science of analytical reasoning facilitated by interactive visual interfaces. [Thomas and Cook, 2005]}}~~		Great atricle, thank you again for writing.

	{{Quotation\|People use visual analytics tools and techniques to synthesize 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; and communicate assessment effectively for action.
	~~<br>Visual analytics is a multidisciplinary field that includes the following focus areas:<br>~~
	*analytical reasoning techniques that let users obtain deep insights that directly support assessment, planning, and decision making;
	*visual representations and interaction techniques that exploit the human eye’s broad bandwidth pathway into the mind to let users see, explore, and understand large amounts of information simultaneously;
	*data representations and transformations that convert all types of conflicting and dynamic data in ways that support visualization and analysis; and
	*techniques to support production, presentation, and dissemination of analytical results to communicate information in the appropriate context to a variety of audiences.
	~~\|[Thomas and Cook, 2005, 2006]}}~~

	~~[[Image:Keim06visual-analytics-disciplines.png\|right\|thumb\|300px\|Visual analytics as a highly interdisciplinary field of research.<br>[Keim et al., 2006]]]~~
	{{Quotation\|'''Visual analytics''' is more than just visualization and can rather be seen as an integrated approach combining [[visualization]], [[human factors]] and [[data analysis]]. ... With respect to the field of [[visualization]], visual analytics integrates methodology from information analytics, geospatial analytics, and scientific analytics. Especially human factors (e.g., interaction, cognition, perception, collaboration, presentation, and dissemination) play a key role in the communication between human and computer, as well as in the decisionmaking process.\|[Keim et al., 2006]}}

	{{Quotation\|Visual analytics is the formation of abstract visual metaphors in combination with a human information discourse (usually some form of interaction) that enables detection of the expected and discovery of the unexpected within massive, dynamically changing information spaces. It is an outgrowth of the fields of scientific and information visualization but includes technologies from many other fields, including knowledge management, statistical analysis, cognitive science, decision science, and others.<br><br>This marriage of computation, visual representation, and interactive thinking supports intensive analysis. The goal is not only to permit users to detect expected events, such as might be predicted by models, but also to help users discover the unexpected—the surprising anomalies, changes, patterns, and relationships that are then examined and assessed to develop new insight.\|[Cook et al., 2007]}}

	~~== Related Links ==~~
	*[http://vadl.cc.gatech.edu/ Visual Analytics Digital Library]
	*[http://www.cs.umd.edu/hcil/semvast/ SEMVAST] Scientific Evaluation Methods for Visual Analytics Science and Technology - Resource on Visual Analytics Evaluation

	~~== Visual Analytics @ YouTube ==~~
	*[http://www.youtube.com/watch?v=5i3xbitEVfs March 15, 2010 — VisMaster - Mastering the Information Age] What is Visual Analytics and why is it important for Europe to fund Research in this new domain?
	*[http://www.youtube.com/watch?v=2CMw4i9DiaM December 16, 2008 — Jigsaw] Using visualization and visual analytics to help investigative analysis and sensemaking.
	*[http://www.youtube.com/watch?v=cVL2Y6nfGiM November 03, 2008 — Mikael Jern on Visual Analytics] Visual Analytics Center, OECD Explorer
	*[http://www.youtube.com/watch?v=5uGRGqCFryg July 10, 2007 — Why Visual Analytics? - A conversation] A series of interviews to some of most known people in Visual Analytics, the science of reasoning through visualization
	*[http://www.youtube.com/watch?v=m_TQZwYL7MY December 12, 2006 — Visual Analytics Show segment from "BusinessNOW" on Maryland Public Television]

	~~== Basic Literature ==~~
	~~=== Books ===~~
	* J.J. Thomas and K.A. Cook (Eds.), [http://nvac.pnl.gov/agenda.stm Illuminating the Path: The Research and Development Agenda for Visual Analytics]. IEEE Press, 2005.
	* Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis and Florian Mansmann (Eds.), [http://www.vismaster.eu/book/ Mastering the Information Age – Solving Problems with Visual Analytics], Eurographics Association, 2010.
	~~=== Papers ===~~
	* J.J. Thomas and K.A. Cook, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1573625 "A Visual Analytics Agenda,"] ''IEEE Computer Graphics & Applications'', vol. 26, ~~pp. 10-13, 2006.~~
	* Pak Chung Wong and J. Thomas, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1333623 "Visual Analytics,"] ''IEEE Computer Graphics & Applications'', vol. 24, pp. 20-21, 2004.
	* Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melancon. 2008. [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual Analytics: Definition, Process, and Challenges."] In Information Visualization, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). Lecture Notes In Computer Science, Vol. 4950. Springer-Verlag, Berlin, Heidelberg 154-175
	* J. Thomas, [http://portal.acm.org/citation.cfm?id=1292429 "Visual analytics: a grand challenge in science: turning information overload into the opportunity of the decade,"] ''Journal of Computing Sciences in Colleges'', vol. 23, pp. 5-6, 2007.

	~~== References ==~~
	*[Cook et al., 2007] Cook, Kris; Earnshaw, Rae; Stasko, John, Guest Editors' Introduction: Discovering the Unexpected, ''Computer Graphics and Applications'', 27(5):15-19, IEEE, Sept.-Oct. 2007.
	*[Keim et al., 2006] Keim, D.A.; Mansmann, F. and Schneidewind, J. and Ziegler, H., Challenges in Visual Data Analysis, Proceedings of Information Visualization (IV 2006), IEEE, p. 9-16, 2006.
	*[Thomas and Cook, 2005] J.J. Thomas and K.A. Cook, eds., [http://nvac.pnl.gov/agenda.stm Illuminating the Path: The Research and Development Agenda for ~~Visual Analytics], IEEE CS Press, 2005.~~
	*[Thomas and Cook, 2006] James J. Thomas and Kristin A. Cook., ''IEEE Computer Graphics and Applications'', 26(1):10-13, January/February, 2006.



	~~[[Category: Glossary]]~~

Paolofdr: - spam

2011-08-19T11:16:54Z

- spam

← Older revision		Revision as of 11:16, 19 August 2011
Line 1:		Line 1:
	{{Definition\|'''Visual analytics''' is the science of analytical reasoning facilitated by interactive visual interfaces. [Thomas and Cook, 2005]}}		{{Definition\|'''Visual analytics''' is the science of analytical reasoning facilitated by interactive visual interfaces. [Thomas and Cook, 2005]}}

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	{{Quotation\|People use visual analytics tools and techniques to synthesize 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; and communicate assessment effectively for action.		{{Quotation\|People use visual analytics tools and techniques to synthesize 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; and communicate assessment effectively for action.

119.155.9.18 at 07:20, 15 August 2011

2011-08-15T07:20:25Z

← Older revision		Revision as of 07:20, 15 August 2011
Line 1:		Line 1:
	{{Definition\|'''Visual analytics''' is the science of analytical reasoning facilitated by interactive visual interfaces. [Thomas and Cook, 2005]}}		{{Definition\|'''Visual analytics''' is the science of analytical reasoning facilitated by interactive visual interfaces. [Thomas and Cook, 2005]}}

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	{{Quotation\|People use visual analytics tools and techniques to synthesize 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; and communicate assessment effectively for action.		{{Quotation\|People use visual analytics tools and techniques to synthesize 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; and communicate assessment effectively for action.

Iwolf: papers /* Papers */

2011-04-06T16:38:00Z

papers Papers

← Older revision		Revision as of 16:38, 6 April 2011
Line 30:		Line 30:
	* Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis and Florian Mansmann (Eds.), [http://www.vismaster.eu/book/ Mastering the Information Age – Solving Problems with Visual Analytics], Eurographics Association, 2010.		* Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis and Florian Mansmann (Eds.), [http://www.vismaster.eu/book/ Mastering the Information Age – Solving Problems with Visual Analytics], Eurographics Association, 2010.
	=== Papers ===		=== Papers ===
	* J.J. Thomas and K.A. Cook, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1573625 "A Visual Analytics Agenda,"] IEEE Computer Graphics & Applications, vol. 26, pp. 10-13, 2006.		* J.J. Thomas and K.A. Cook, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1573625 "A Visual Analytics Agenda,"] ''IEEE Computer Graphics & Applications'', vol. 26, pp. 10-13, 2006.
	* Pak Chung Wong and J. Thomas, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1333623 "Visual Analytics,"] Computer Graphics ~~and~~ Applications~~, IEEE~~, vol. 24, pp. 20-21, 2004.		* Pak Chung Wong and J. Thomas, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1333623 "Visual Analytics,"] ''IEEE Computer Graphics & Applications'', vol. 24, pp. 20-21, 2004.
	* D. Keim, G. Andrienko, J.-D. Fekete, C. Görg, J. Kohlhammer, and G. Melançon, [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual analytics: Definition, process, and challenges,"] 2008, pp. 154-175.
	* Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melancon. 2008. [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual Analytics: Definition, Process, and Challenges."] In Information Visualization, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). Lecture Notes In Computer Science, Vol. 4950. Springer-Verlag, Berlin, Heidelberg 154-175		* Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melancon. 2008. [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual Analytics: Definition, Process, and Challenges."] In Information Visualization, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). Lecture Notes In Computer Science, Vol. 4950. Springer-Verlag, Berlin, Heidelberg 154-175
	* J. Thomas, [http://portal.acm.org/citation.cfm?id=1292429 "Visual analytics: a grand challenge in science: turning information overload into the opportunity of the decade,"] ~~J. Comput. Small Coll~~, vol. 23, pp. 5-6, 2007.		* J. Thomas, [http://portal.acm.org/citation.cfm?id=1292429 "Visual analytics: a grand challenge in science: turning information overload into the opportunity of the decade,"] ''Journal of Computing Sciences in Colleges'', vol. 23, pp. 5-6, 2007.

	== References ==		== References ==

Iwolf: added paper /* Basic Literature */

2011-04-06T16:35:53Z

added paper Basic Literature

← Older revision		Revision as of 16:35, 6 April 2011
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	* D. Keim, G. Andrienko, J.-D. Fekete, C. Görg, J. Kohlhammer, and G. Melançon, [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual analytics: Definition, process, and challenges,"] 2008, pp. 154-175.		* D. Keim, G. Andrienko, J.-D. Fekete, C. Görg, J. Kohlhammer, and G. Melançon, [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual analytics: Definition, process, and challenges,"] 2008, pp. 154-175.
	* Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melancon. 2008. [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual Analytics: Definition, Process, and Challenges."] In Information Visualization, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). Lecture Notes In Computer Science, Vol. 4950. Springer-Verlag, Berlin, Heidelberg 154-175		* Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melancon. 2008. [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual Analytics: Definition, Process, and Challenges."] In Information Visualization, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). Lecture Notes In Computer Science, Vol. 4950. Springer-Verlag, Berlin, Heidelberg 154-175
			* J. Thomas, [http://portal.acm.org/citation.cfm?id=1292429 "Visual analytics: a grand challenge in science: turning information overload into the opportunity of the decade,"] J. Comput. Small Coll, vol. 23, pp. 5-6, 2007.

	== References ==		== References ==

Iwolf: added papers /* Basic Literature */

2011-04-06T16:33:33Z

added papers Basic Literature

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	* J.J. Thomas and K.A. Cook (Eds.), [http://nvac.pnl.gov/agenda.stm Illuminating the Path: The Research and Development Agenda for Visual Analytics]. IEEE Press, 2005.		* J.J. Thomas and K.A. Cook (Eds.), [http://nvac.pnl.gov/agenda.stm Illuminating the Path: The Research and Development Agenda for Visual Analytics]. IEEE Press, 2005.
	* Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis and Florian Mansmann (Eds.), [http://www.vismaster.eu/book/ Mastering the Information Age – Solving Problems with Visual Analytics], Eurographics Association, 2010.		* Daniel Keim, Jörn Kohlhammer, Geoffrey Ellis and Florian Mansmann (Eds.), [http://www.vismaster.eu/book/ Mastering the Information Age – Solving Problems with Visual Analytics], Eurographics Association, 2010.
			=== Papers ===
			* J.J. Thomas and K.A. Cook, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1573625 "A Visual Analytics Agenda,"] IEEE Computer Graphics & Applications, vol. 26, pp. 10-13, 2006.
			* Pak Chung Wong and J. Thomas, [http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1333623 "Visual Analytics,"] Computer Graphics and Applications, IEEE, vol. 24, pp. 20-21, 2004.
			* D. Keim, G. Andrienko, J.-D. Fekete, C. Görg, J. Kohlhammer, and G. Melançon, [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual analytics: Definition, process, and challenges,"] 2008, pp. 154-175.
			* Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melancon. 2008. [http://infovis.uni-konstanz.de/papers/2007/Dagstuhl2007VisualAnalyticsfinal.pdf "Visual Analytics: Definition, Process, and Challenges."] In Information Visualization, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). Lecture Notes In Computer Science, Vol. 4950. Springer-Verlag, Berlin, Heidelberg 154-175

	== References ==		== References ==