Name
Abstract | ||
|---|---|---|
Time is a universal and essential aspect of data in any investigative analysis. It helps analysts establish causality, build storylines from evidence, and reject infeasible hypotheses. For this reason, many investigative analysis tools provide visual representations designed for making sense of temporal data. However, the field of visual analytics still needs more evidence explaining how temporal visualization actually aids the analysis process, as well as design recommendations for how to build these visualizations. To fill this gap, we conducted an insight-based qualitative study to investigate the influence of temporal visualization on investigative analysis. We found that visualizing temporal information helped participants externalize chains of events. Another contribution of our work is the lightweight evaluation approach used to collect, visualize, and analyze insight. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TVCG.2012.89 | IEEE Trans. Vis. Comput. Graph. |
Keywords | Field | DocType |
data visualisation,recycling,data visualization,data analysis,visual analytics | Data science,Analysis tools,Causality,Data visualization,Computer science,Visualization,Visual analytics,Temporal database,Document handling,Qualitative research | Journal |
Volume | Issue | ISSN |
18 | 11 | 1077-2626 |
Citations | PageRank | References |
8 | 0.44 | 21 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bum chul Kwon | 1 | 278 | 16.46 |
| Waqas Javed | 2 | 334 | 11.68 |
| Sohaib Ghani | 3 | 88 | 4.12 |
| Niklas Elmqvist | 4 | 2065 | 98.35 |
| Ji Soo Yi | 5 | 860 | 41.47 |
| David S. Ebert | 6 | 2056 | 232.34 |