Literature DB >> 17073373

An insight-based longitudinal study of visual analytics.

Purvi Saraiya1, Chris North, Vy Lam, Karen A Duca.   

Abstract

Visualization tools are typically evaluated in controlled studies that observe the short-term usage of these tools by participants on preselected data sets and benchmark tasks. Though such studies provide useful suggestions, they miss the long-term usage of the tools. A longitudinal study of a bioinformatics data set analysis is reported here. The main focus of this work is to capture the entire analysis process that an analyst goes through from a raw data set to the insights sought from the data. The study provides interesting observations about the use of visual representations and interaction mechanisms provided by the tools, and also about the process of insight generation in general. This deepens our understanding of visual analytics, guides visualization developers in creating more effective visualization tools in terms of user requirements, and guides evaluators in designing future studies that are more representative of insights sought by users from their data sets.

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Year:  2006        PMID: 17073373     DOI: 10.1109/TVCG.2006.85

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  5 in total

1.  Facilitating the analysis of immunological data with visual analytic techniques.

Authors:  David C Shih; Kevin C Ho; Kyle M Melnick; Ronald A Rensink; Tobias R Kollmann; Edgardo S Fortuno
Journal:  J Vis Exp       Date:  2011-01-02       Impact factor: 1.355

Review 2.  The case for visual analytics of arsenic concentrations in foods.

Authors:  Matilda O Johnson; Hari H P Cohly; Raphael D Isokpehi; Omotayo R Awofolu
Journal:  Int J Environ Res Public Health       Date:  2010-04-28       Impact factor: 3.390

3.  Scientists' sense making when hypothesizing about disease mechanisms from expression data and their needs for visualization support.

Authors:  Barbara Mirel; Carsten Görg
Journal:  BMC Bioinformatics       Date:  2014-04-26       Impact factor: 3.169

4.  Health timeline: an insight-based study of a timeline visualization of clinical data.

Authors:  Andres Ledesma; Niranjan Bidargaddi; Jörg Strobel; Geoffrey Schrader; Hannu Nieminen; Ilkka Korhonen; Miikka Ermes
Journal:  BMC Med Inform Decis Mak       Date:  2019-08-22       Impact factor: 2.796

5.  Biomedical discovery acceleration, with applications to craniofacial development.

Authors:  Sonia M Leach; Hannah Tipney; Weiguo Feng; William A Baumgartner; Priyanka Kasliwal; Ronald P Schuyler; Trevor Williams; Richard A Spritz; Lawrence Hunter
Journal:  PLoS Comput Biol       Date:  2009-03-27       Impact factor: 4.475

  5 in total

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