Inventing Discovery Tools: Combining Information Visualization with Data Mining
Author(s) -
Ben Shneiderman
Publication year - 2001
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
DOI - 10.1007/3-540-45650-3_4
Subject(s) - computer science , visualization , exploratory data analysis , data science , data exploration , information visualization , exploratory analysis , data mining , data visualization , knowledge extraction , visual analytics , information retrieval
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. I claim that a combined approach could lead to novel discovery tools that preserve user control, enable more effective exploration, and promote responsibility.
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