Who, Where, When and with Whom? Evaluation of Group Meeting Visualizations
Visualizing time-dependent and location-based data is a challenging problem but highly relevant for areas like intelligence analysis, traffic control, or social network analysis. In this context, we address the problem of visualizing meetings between persons, groups of persons, vehicles, or other entities. However, the temporal dimension inherent in such data makes traditional map representations less well suited for this kind of problem as they easily become cluttered. To overcome this issue we developed a modified map representation and three alternative representations (two matrix-based visualizations and one based on Gantt charts). An empirical evaluation comparing these four visualizations and assessing correctness, recognition rates of groups, and subjective preference indicates that the alternative visualizations perform significantly better than the map-based representation when meetings need to be identified. In addition, we identify specific strengths and weaknesses of the investigated visualizations and propose design considerations.
KeywordsInformation visualization Map Matrix Gantt charts
The research leading to these results in the VALCRI project has received funding from the European Union 7th Framework Programme (FP7/2007-2013) under grant agreement no FP7-IP- 608142, to Middlesex University and Partners. Simone Kriglstein was supported by CVAST (funded by the Austrian Federal Ministry of Science, Research, and Economy in the exceptional Laura Bassi Centres of Excellence initiative, project nr: 822746).
- 3.Andrienko, G., Andrienko, N., Mladenov, M., Mock, M., Pölitz, C.: Discovering bits of place histories from people’s activity traces. In: Proceedings of the VAST 2010, pp. 59–66. IEEE (2010)Google Scholar
- 4.Boba Santos, R.: Crime Analysis With Crime Mapping, 3rd edn. SAGE Publications, Thousand Oaks (2013)Google Scholar
- 6.Ghoniem, M., Fekete, J.D., Castagliola, P.: A comparison of the readability of graphs using node-link and matrix-based representations. In: Proceedings of the INFOVIS 2004, pp. 17–24. IEEE (2004)Google Scholar
- 11.Kjellin, A., Pettersson, L.W., Seipel, S., Lind, M.: Evaluating 2D and 3D visualizations of spatiotemporal information. ACM Trans. Appl. Percept. 7(3), 19:1–19:23 (2008)Google Scholar
- 12.Kraak, M.J.: The space-time cube revisited from a geovisualization perspective. In: Proceedings of the ICC 2003. The International Cartographic (2003)Google Scholar
- 15.Li, N., Chen, G.: Analysis of a location-based social network. In: Proceedings of the CSE 2004, pp. 263–270. IEEE (2009)Google Scholar
- 16.Luz, S., Masoodian, M.: Comparing static gantt and mosaic charts for visualization of task schedules. In: Proceedings of the IV 2011, pp. 182–187. IEEE (2011)Google Scholar
- 17.MacEachren, A.M.: How Maps Work - Representation, Visualization, and Design. Guilford Press, New York (2004)Google Scholar
- 18.Orellana, D., Wachowicz, M., Andrienko, N., Andrienko, G.: Uncovering interaction patterns in mobile outdoor gaming. In: Proceedings of the GEOWS 2009, pp. 177–182. IEEE (2009)Google Scholar
- 19.Schreier, M.: Qualitative Content Analysis in Practice. SAGE Publications, Thousand Oaks (2012)Google Scholar
- 20.Shen, Z., Ma, K.L.: Path visualization for adjacency matrices. In: Proceedings of the EUROVIS 2007, pp. 83–90. Eurographics Association (2007)Google Scholar
- 21.Ware, C.: Information Visualization: Perception for Design. Morgan Kaufmann Publishers Inc., Burlington (2004)Google Scholar