Proceedings: GI 2017

Supporting Team-First Visual Analytics through Group Activity Representations

Sriram Karthik Badam (University of Maryland, College Park, MD, USA), Zehua Zeng (University of Maryland, College Park, MD, USA), Emily Wall (Georgia Institute of Technology, Atlanta, GA, USA), Alex Endert (Georgia Institute of Technology, Atlanta, GA, USA), Niklas Elmqvist (University of Maryland, College Park, MD, USA)

Proceedings of Graphics Interface 2017: Edmonton, Alberta, 16-19 May 2017, 208 - 213

DOI 10.20380/GI2017.26

  • Bibtex

    @inproceedings{Badam:2017:10.20380/GI2017.26,
    author = {Badam, Sriram and Zeng, Zehua and Wall, Emily and Endert, Alex and Elmqvist, Niklas},
    title = {Supporting Team-First Visual Analytics through Group Activity Representations},
    booktitle = {Proceedings of Graphics Interface 2017},
    series = {GI 2017},
    year = {2017},
    issn = {0713-5424},
    isbn = {978-0-9947868-2-1},
    location = {Edmonton, Alberta},
    pages = {208 -- 213},
    numpages = {6},
    doi = {10.20380/GI2017.26},
    publisher = {Canadian Human-Computer Communications Society / Soci{\'e}t{\'e} canadienne du dialogue humain-machine},
    }

Abstract

Collaborative visual analytics (CVA) involves sensemaking activities within teams of analysts based on coordination of work across team members, awareness of team activity, and communication of hypotheses, observations, and insights. We introduce a new type of CVA tools based on the notion of “team-first” visual analytics, where supporting the analytical process and needs of the entire team is the primary focus of the graphical user interface before that of the individual analysts. To this end, we present the design space and guidelines for team-first tools in terms of conveying analyst presence, focus, and activity within the interface. We then introduce InsightsDrive, a CVA tool for multidimensional data, that contains team-first features into the interface through group activity visualizations. This includes (1) in-situ representations that show the focus regions of all users integrated in the data visualizations themselves using color-coded selection shadows, as well as (2) ex-situ representations showing the data coverage of each analyst using multidimensional visual representations. We conducted two user studies, one with individual analysts to identify the affordances of different visual representations to inform data coverage, and the other to evaluate the performance of our team-first design with exsitu and in-situ awareness for visual analytic tasks. Our results give an understanding of the performance of our team-first features and unravel their advantages for team coordination.