Graph Analytics-Lessons Learned and Challenges Ahead

TitleGraph Analytics-Lessons Learned and Challenges Ahead
Publication TypeMagazine Articles
Year of Publication2011
AuthorsWong P C, Chen C, Gorg C, Shneiderman B, Stasko J, Thomas J
MagazineIEEE Computer Graphics and Applications
Issue Number5
Pagination18 - 29
Date Published2011///
ISBN Number0272-1716
Keywordscitation analysis, citespace, Computer Graphics, document analysis, graphics and multimedia, greengrid, jigsaw system, modeling, power grid analysis, semantic substrates, simulation, social networks, text analysis, Visualization

Graph analytics is one of the most influential and important R&D topics in the visual analytics community. Researchers with diverse backgrounds from information visualization, human-computer interaction, computer graphics, graph drawing, and data mining have pursued graph analytics from scientific, technical, and social approaches. These studies have addressed both distinct and common challenges. Past successes and mistakes can provide valuable lessons for revising the research agenda. In this article, six researchers from four academic and research institutes identify graph analytics' fundamental challenges and present both insightful lessons learned from their experience and good practices in graph analytics research. The goal is to critically assess those lessons and shed light on how they can stimulate research and draw attention to grand challenges for graph analytics. The article also establishes principles that could lead to measurable standards and criteria for research.