• DocumentCode
    2635682
  • Title

    Visual analytic roadblocks for novice investigators

  • Author

    Kwon, Bum Chul ; Fisher, Brian ; Yi, Ji Soo

  • Author_Institution
    Purdue Univ., West Lafayette, IN, USA
  • fYear
    2011
  • fDate
    23-28 Oct. 2011
  • Firstpage
    3
  • Lastpage
    11
  • Abstract
    We have observed increasing interest in visual analytics tools and their applications in investigative analysis. Despite the growing interest and substantial studies regarding the topic, understanding the major roadblocks of using such tools from novice users´ perspectives is still limited. Therefore, we attempted to identify such “visual analytic roadblocks” for novice users in an investigative analysis scenario. To achieve this goal, we reviewed the existing models, theories, and frameworks that could explain the cognitive processes of human-visualization interaction in investigative analysis. Then, we conducted a qualitative experiment with six novice participants, using a slightly modified version of pair analytics, and analyzed the results through the open-coding method. As a result, we came up with four visual analytic roadblocks and explained these roadblocks using existing cognitive models and theories. We also provided design suggestions to overcome these roadblocks.
  • Keywords
    data analysis; data visualisation; human-visualization interaction cognitive process; investigative analysis scenario; novice investigators; open-coding method; pair analytics; visual analytic roadblocks; Analytical models; Calendars; Cognition; Context; Humans; Visual analytics; Visual analytics; cognitive model; framework; investigative analysis; qualitative experiment; roadblock;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology (VAST), 2011 IEEE Conference on
  • Conference_Location
    Providence, RI
  • Print_ISBN
    978-1-4673-0015-5
  • Type

    conf

  • DOI
    10.1109/VAST.2011.6102435
  • Filename
    6102435