Survey of Surveys (SoS) ‐ Mapping The Landscape of Survey Papers in Information Visualization

Information visualization as a field is growing rapidly in popularity since the first information visualization conference in 1995. However, as a consequence of its growth, it is increasingly difficult to follow the growing body of literature within the field. Survey papers and literature reviews ar...

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Veröffentlicht in:Computer graphics forum Jg. 36; H. 3; S. 589 - 617
Hauptverfasser: McNabb, Liam, Laramee, Robert S.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Blackwell Publishing Ltd 01.06.2017
Schlagworte:
[Human‐centered computing]: Visualization—Information visualization
Analytics
Categories and Subject Descriptors (according to ACM CCS)
Classification
Clusters
Critical mass
Literature reviews
Mapping
Product development
Readers
Researchers
Scientific papers
Scientific visualization
Surveying
Visualization
ISSN:0167-7055, 1467-8659
Online-Zugang:Volltext
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Zusammenfassung:Information visualization as a field is growing rapidly in popularity since the first information visualization conference in 1995. However, as a consequence of its growth, it is increasingly difficult to follow the growing body of literature within the field. Survey papers and literature reviews are valuable tools for managing the great volume of previously published research papers, and the quantity of survey papers in visualization has reached a critical mass. To this end, this survey paper takes a quantum step forward by surveying and classifying literature survey papers in order to help researchers understand the current landscape of Information Visualization. It is, to our knowledge, the first survey of survey papers (SoS) in Information Visualization. This paper classifies survey papers into natural topic clusters which enables readers to find relevant literature and develops the first classification of classifications. The paper also enables researchers to identify both mature and less developed research directions as well as identify future directions. It is a valuable resource for both newcomers and experienced researchers in and outside the field of Information Visualization and Visual Analytics.
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.13212