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{{Quotation|Insight: The capacity to discern the true nature of a situation; The act or outcome of grasping the inward or hidden nature of things or of perceiving in an intuitive manner.|[Merriam-Webster]}} | {{Quotation|Insight: The capacity to discern the true nature of a situation; The act or outcome of grasping the inward or hidden nature of things or of perceiving in an intuitive manner.|[Merriam-Webster]}} | ||
{{Quotation|The Gestalt psychologists also introduced the idea that restructuring is associated with [[insight]]--sudden realization of the problem's solution.|[Goldstein, 2005]}} | |||
Important characteristics of insight in [[Information Visualization]] as defined by [[North, Chris|Chris North]]: | |||
{{Quotation|'''Complex.''' Insight is complex, involving all or large amounts of the given data in a synergistic way, not simply individual data values.<br>'''Deep.''' Insight builds up over time, accumulating and building on itself to create depth. Insight often generates further questions and, hence, further insight.<br>'''Qualitative.''' Insight is not exact, can be uncertain and subjective, and can have multiple levels of resolusion.<br>'''Unexpected.''' Insight is often unpredictable, serendipitous, and creative.<br>'''Relevant.''' Insight is deeply embedded in the data domain, connecting the data to existing domain knowledge and giving it relevant meaning. It goes beyond dry data analysis, to relevant domain impact.|[North, 2006]}} | |||
see [[Knowledge Discovery]] for an explanation of the relationship between [[Data]], [[Information]], [[Insight]], [[Model]], [[Pattern]], [[Hypothesis]], [[Knowledge]] and [[Knowledge Crystallization]]. | |||
== References == | == References == | ||
[Saraiya et al., 2005] Purvi Saraiya, Chris North, and Karen Duca, An Insight-Based Methodology for | *[Goldstein, 2005] Goldstein, Bruce. Cognitive Psychology, Thomson Wadsworth, 2005. | ||
Evaluating Bioinformatics Visualizations, ''IEEE Transactions on Visualization and Computer Graphics'', 11(4):443-456, July/August 2005. | *[North, 2006] Chris North, Toward Measuring Visualization Insight. ''IEEE Computer Graphics and Applications''', 26(3):6-9, 2006. | ||
*[Saraiya et al., 2005] Purvi Saraiya, Chris North, and Karen Duca, An Insight-Based Methodology for Evaluating Bioinformatics Visualizations, ''IEEE Transactions on Visualization and Computer Graphics'', 11(4):443-456, July/August 2005. | |||
[[Category: Glossary]] | [[Category: Glossary]] | ||
Latest revision as of 10:47, 21 August 2009
We define an insight as an individual observation about the data by the participant, a unit of discovery.
[Saraiya et al., 2005]
[Saraiya et al., 2005]
Insight: The capacity to discern the true nature of a situation; The act or outcome of grasping the inward or hidden nature of things or of perceiving in an intuitive manner.
[Merriam-Webster]
The Gestalt psychologists also introduced the idea that restructuring is associated with insight--sudden realization of the problem's solution.
[Goldstein, 2005]
Important characteristics of insight in Information Visualization as defined by Chris North:
Complex. Insight is complex, involving all or large amounts of the given data in a synergistic way, not simply individual data values.
Deep. Insight builds up over time, accumulating and building on itself to create depth. Insight often generates further questions and, hence, further insight.
Qualitative. Insight is not exact, can be uncertain and subjective, and can have multiple levels of resolusion.
Unexpected. Insight is often unpredictable, serendipitous, and creative.
Relevant. Insight is deeply embedded in the data domain, connecting the data to existing domain knowledge and giving it relevant meaning. It goes beyond dry data analysis, to relevant domain impact.
Deep. Insight builds up over time, accumulating and building on itself to create depth. Insight often generates further questions and, hence, further insight.
Qualitative. Insight is not exact, can be uncertain and subjective, and can have multiple levels of resolusion.
Unexpected. Insight is often unpredictable, serendipitous, and creative.
Relevant. Insight is deeply embedded in the data domain, connecting the data to existing domain knowledge and giving it relevant meaning. It goes beyond dry data analysis, to relevant domain impact.
[North, 2006]
see Knowledge Discovery for an explanation of the relationship between Data, Information, Insight, Model, Pattern, Hypothesis, Knowledge and Knowledge Crystallization.
References
- [Goldstein, 2005] Goldstein, Bruce. Cognitive Psychology, Thomson Wadsworth, 2005.
- [North, 2006] Chris North, Toward Measuring Visualization Insight. IEEE Computer Graphics and Applications', 26(3):6-9, 2006.
- [Saraiya et al., 2005] Purvi Saraiya, Chris North, and Karen Duca, An Insight-Based Methodology for Evaluating Bioinformatics Visualizations, IEEE Transactions on Visualization and Computer Graphics, 11(4):443-456, July/August 2005.