CHI 2014: Studying Visualization

Structuring the Space by Nathalie Henry Riche

  • people often refer to information visualizations as maps; many visualizations use spatial metaphors; picked up on contour lines from topographical maps for data
  • mental model: spatial structure + landmarks; do they help or hinder readability and understanding?
  • user study: hinder ability to find common neighbors? help perform comparison of similar graphs? help revisit nodes? 3 conditions – no structure, grid, contour lines
  • findings: no changes in readability shown, contour lines better than grids for comparison but no difference between grids and control, ensure data sets have salient features like clusters, contour better than grid or control for revisitation even though people thought the grid helped

Highlighting Interventions and User Differences by Giuseppe Carenini

  • investigate user-adaptive visualizations; what to adapt to? when to adapt? how to adapt?
  • evaluate 4 types of highlighting interventions: bold, connected arrows, de-emphasis, reference lines
  • highlighting can layer in relevant information in a complex visualization
  • user study: 62 participants, bar graphs, tasks – retrieve value + compute derived value; look at impact of user characteristics; varied timing of intervention
  • findings: deemphasis is best but bold and arrow worked too, dynamic timing erased edge of deemphasis, more complex task also took deemphasis to parity with bold and arrow, all interventions rated useful, visual working memory related to perceived usefulness of reference line

Evaluating a Tool for Improving Chart and Graph Accessibility by Gita Lindgaard

  • how do blind people form a mental representation of a graph?
  • descriptions must be consistent, order of descriptions follow order of questions, star from oldest data, need to interrogate the graph, vocabulary – x/y axis + up/down
  • iGraph: extracts semantics from excel charts and generates natural language output plus supports interaction commands
  • usability study 1: complex graphs took longer, blind people used twice as many commands as sighted and found it easier to use, all used more command than necessary, skipmwasmconfusing, didn't use where am I command
  • usability study 2 (improved system): graph complexity had no effect, blind users used many more commands still (double check understanding), blind users navigated left more often, sighted start over more often
  • field study: system could handle most of the questions the user had about user's chosen graphs; order of information: title, type, then other info; presentation of graphs were often missing a great deal of critical metadata about the graphs
  • test expert to novice vocabulary usage: iGraph vocabulary mentioned by all participants

Understand Users' Comprehension and Preferences for Composing Information Visualizations by Huahai Yang

  • develop a system to automatically compose a visualization from multiple charts and pick best representation; choice depends on insight you are looking for, eg side by side bar good at extrema identification, lines good at correlation comparison
  • study: describe composite visualizations to discover vocabulary and concepts; mechanical Turk led to 1,500 useful descriptions, then coded them; 4 basic insights – read value, extrema identification, characterize distribution, correlation; all can be used for comparison as well; prioritize insights for different types of charts; value comparison, extrema, and correlation swamp other insights (Zipf function)
  • most preferred: crossed-bar (side by side) except for correlation comparison which prefers crossed-line
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