We investigated the impacts of three sorting techniques on various cognitive tasks performed on a tabular representation. The tasks under study were a multi-attribute object selection task and selected low-level analytic tasks. Three sorting techniques, including sorting by a column (Typical Sort: TS), sorting by all columns simultaneously (SimulSort: SS), and sorting by all columns with faithful vertical locations (ParallelTable: PT), were compared with a static table without the sorting feature (Baseline: B). An incentivized controlled laboratory study with 80 participants and a preliminary eye-tracker study were conducted to better understand the strengths and weaknesses of the four different approaches. We found that SimulSort and ParallelTable significantly improved the performance of multi-attribute object selection. ParallelTable, however, suffers from an occlusion problem, so it is not an appropriate support for some low-level analytic tasks. We used the findings to propose appropriate sorting techniques for specific tasks performed on a table.
Visualized Decision Making, tabular visualization, SimulSort, ParallelTable, sorting
Date of this Version
NOTICE: this is the author’s version of a work that was accepted for publication in International Journal of Human Computer Interaction . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Human-Computer Interactions, [Volume 29, Issue 6, July 17, 2012 ]