Inventing discovery tools: combining information visualization with data mining††Keynote for Discovery Science 2001 Conference, November 25–28, 2001, Washington, DC.

2003 ◽  
pp. 378-385
Author(s):  
Ben Shneiderman
Keyword(s):  
Data Mining ◽  
Information Visualization ◽  
Washington Dc ◽  
Discovery Science ◽  
Combining Information

scholarly journals Inventing Discovery Tools: Combining Information Visualization with Data Mining

2002 ◽  
Vol 1 (1) ◽  
pp. 5-12 ◽  
Author(s):  
Ben Shneiderman
Keyword(s):  
Data Mining ◽  
Information Visualization ◽  
Research Information ◽  
Data Mining Algorithms ◽  
Exploratory Data ◽  
Visualization Tools ◽  
Statistical Algorithms ◽  
Mining Algorithms ◽  
Combining Information ◽  
Insight Into

The growing use of information visualization tools and data mining algorithms stems from two separate lines of research. Information visualization researchers believe in the importance of giving users an overview and insight into the data distributions, while data mining researchers believe that statistical algorithms and machine learning can be relied on to find the interesting patterns. This paper discusses two issues that influence design of discovery tools: statistical algorithms vs visual data presentation, and hypothesis testing vs exploratory data analysis. The paper claims that a combined approach could lead to novel discovery tools that preserve user control, enable more effective exploration, and promote responsibility.

Aesthetic Expectations for Information Visualization

2010 ◽  
Vol 1 (1) ◽  
pp. 19-39 ◽  
Author(s):  
Anna Ursyn
Keyword(s):  
New Media ◽  
Information Visualization ◽  
Data Sets ◽  
Art World ◽  
New Media Art ◽  
Computer Scientists ◽  
Computer Based ◽  
Level Of Training ◽  
Visualization Techniques ◽  
Combining Information

This article explores the landscape of creative endeavors in the new media art and reflects on aesthetics of information visualization. When using computer based information visualization to show data interactively in many dimensions, the user can navigate across big data sets, find patterns, relationships, and structures that would be invisible if presented numerically. The authors also explore ways of combining information visualization techniques with the principles of creative design, enhancing artistic influences on the technical implementations, and raising the level of training in design. Finally, the authors offer suggestions for creating knowledge visualizations with the use of art and graphics to strengthen the readiness of computer scientists to fulfill aesthetic expectations and gain recognition from art world specialists for factual solutions done in visualization projects and new forms of art.

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