Developing Qualitative Metrics for Visual Analytic Environments
From BELIV 2010
Presentation
Notes
- focus on qualitative metrics on utility than usability
- interested analytic process, use of vis in this process, quality of results of process
- VAST developed data sets with ground truths, know you are right
- review of all the reviews submitted for mini challenges (42)
- asked three questions, focused on second
- material ok
- (focus) what reviewers think are important
- selecting 2 types of reviewers: prof analysts (hard), vis experts
- reviewers given video submission, screen shots, text descriptions
- reviewers comment on clarity, clear the better scores obtained, not clear, only 5% get a score higher than 5
- comments analytical, vis
- why select a particular vis; intuitive to analysis
- comment on vis: complexity, too complex, can't see answer, find line between complexity of vis and putting enough for people to what's happening
- people don't like having to mouse
- careful about showing relationships
- comparison is very important
q and a
- how many reviewers
- comments available to next year's contestants
- comments may be too prescriptive, only put comments there that have been made multiple times (no frequency statistics)
- some comments may not be right, but it's a starting point
- have to be careful as to how to phrase it, shouldn't be applied without thinking about it
- video quality, infovis/vast high correlation between acceptance and availability of video; in challenge--explanation is more correlated than with videos
- metrics of the contest in the future that reviewers will use
- different data--different comments this year
- accessibility--not explicitly stated: guidelines or metrics given; not catered to color-blind / blind people;
