An insight-based methodology for evaluating bioinformatics visualizations

By Purvi Saraiya, Chris North, Karen Duca. IEEE Transactions on Visualization and Computer Graphics, 2005

425 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b450dedf0079b80c490e57fd9a20464351e5cbf3

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Citations in the corpus

A Nested Model for Visualization Design and Validation (2009, background): “Although this form of validation is usually qualitative, some influential work towards quantifying insight has been done [37].”
Interpreting informational cues: An explorative study on information use among prospective homebuyers (2009, positive): “Instead of controlled experiments that measure time to completion to benchmark tasks, interest has grown in insight-based evaluation ( Saraiya, North and Duca, 2005 ) and longitudinal case studies with domain experts doing their own work over days and weeks.”
A Framework for Considering Comprehensibility in Modeling (2016, neutral): “For example, insight quantiﬁcation approaches 30,31 could measure how well a model supports hypothesis formulation (building theory).”
Evaluating Information Visualizations (2008, methodology): “” While it is possible to ask participants what they have learned about a dataset after use of an information visualization tool, it strongly depends on the participants’ motivation, their previous knowledge about the domain, and their interest in the dataset [55, 63].”
Casual Information Visualization: Depictions of Data in Everyday Life (2007, methodology): “Saraiya et. al. address this question to some degree with their introduction of " Insight-based evaluation " which is a technique for understanding the number, type, and importance of the insights that a tool can bring [31].”
Visualization of omics data for systems biology (2010, methodology): “Visual analytics methods have begun to be applied to studying the connection between visualization and analytical reasoning in systems biolog”
Mastering the Information Age - Solving Problems with Visual Analytics (2010, background): “Saraiya Gaining insight is about discovery and is often unexpected et al.[95] define insight “as an individual observation about the data by the participant, a unit of discovery”.”
Collaborative visualization: Definition, challenges, and research agenda (2011, neutral): “However, measuring group insight (or even individual insight as pointed out previously 77 ) is difﬁcult.”
Design Study Methodology: Reflections from the Trenches and the Stacks (2012, methodology): “Finally, many proposed evaluation methods address the specific needs of validating the usefulness of visualization tools such as the multidimensional in-depth long-term case study approach [80], the insight-based method [68, 69], and grounded evaluation [33].”
The Effects of Interactive Latency on Exploratory Visual Analysis (2014, methodology): “Initially, we tried to extract pieces of knowledge (“insight”), following the insight-based methodology [37].”