Literature DB >> 17968068

Toward a deeper understanding of the role of interaction in information visualization.

Ji Soo Yi1, Youn Ah Kang, John Stasko, Julie Jacko.   

Abstract

Even though interaction is an important part of information visualization (Infovis), it has garnered a relatively low level of attention from the Infovis community. A few frameworks and taxonomies of Infovis interaction techniques exist, but they typically focus on low-level operations and do not address the variety of benefits interaction provides. After conducting an extensive review of Infovis systems and their interactive capabilities, we propose seven general categories of interaction techniques widely used in Infovis: 1) Select, 2) Explore, 3) Reconfigure, 4) Encode, 5) Abstract/Elaborate, 6) Filter, and 7) Connect. These categories are organized around a user's intent while interacting with a system rather than the low-level interaction techniques provided by a system. The categories can act as a framework to help discuss and evaluate interaction techniques and hopefully lay an initial foundation toward a deeper understanding and a science of interaction.

Year:  2007        PMID: 17968068     DOI: 10.1109/TVCG.2007.70515

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


  16 in total

1.  Leveraging domain knowledge to facilitate visual exploration of large population datasets.

Authors:  William Hsu; Alex A T Bui
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

Review 2.  Unlocking proteomic heterogeneity in complex diseases through visual analytics.

Authors:  Suresh K Bhavnani; Bryant Dang; Gowtham Bellala; Rohit Divekar; Shyam Visweswaran; Allan R Brasier; Alex Kurosky
Journal:  Proteomics       Date:  2015-04       Impact factor: 3.984

3.  A cognitive task analysis of a visual analytic workflow: Exploring molecular interaction networks in systems biology.

Authors:  Barbara Mirel; Felix Eichinger; Benjamin J Keller; Matthias Kretzler
Journal:  J Biomed Discov Collab       Date:  2011-03-21

4.  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

5.  Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions.

Authors:  Sugeerth Murugesan; Kristofer Bouchard; Edward Chang; Max Dougherty; Bernd Hamann; Gunther H Weber
Journal:  BMC Bioinformatics       Date:  2017-06-06       Impact factor: 3.169

6.  Development of an interactive web-based tool to conduct and interrogate meta-analysis of diagnostic test accuracy studies: MetaDTA.

Authors:  Suzanne C Freeman; Clareece R Kerby; Amit Patel; Nicola J Cooper; Terry Quinn; Alex J Sutton
Journal:  BMC Med Res Methodol       Date:  2019-04-18       Impact factor: 4.615

7.  Beyond information access: Support for complex cognitive activities in public health informatics tools.

Authors:  Kamran Sedig; Paul Parsons; Mark Dittmer; Oluwakemi Ola
Journal:  Online J Public Health Inform       Date:  2012-12-19

8.  VANLO--interactive visual exploration of aligned biological networks.

Authors:  Steffen Brasch; Lars Linsen; Georg Fuellen
Journal:  BMC Bioinformatics       Date:  2009-10-12       Impact factor: 3.169

9.  Novel Analysis Software for Detecting and Classifying Ca2+ Transient Abnormalities in Stem Cell-Derived Cardiomyocytes.

Authors:  Kirsi Penttinen; Harri Siirtola; Jorge Àvalos-Salguero; Tiina Vainio; Martti Juhola; Katriina Aalto-Setälä
Journal:  PLoS One       Date:  2015-08-26       Impact factor: 3.240

10.  Epiviz: interactive visual analytics for functional genomics data.

Authors:  Florin Chelaru; Llewellyn Smith; Naomi Goldstein; Héctor Corrada Bravo
Journal:  Nat Methods       Date:  2014-08-03       Impact factor: 28.547

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