Masoodian, M., Luz, S., & Kavenga, D. (2016). Nu-view: A visualization system for collaborative Co-located analysis of geospatial disease data. In Proceedings of the ACSW ‘16 Australasian Computer Science Week Multiconference, 2-5 February, Canberra, Australia. New York, USA: ACM. http://doi.org/10.1145/2843043.2843374
Permanent Research Commons link: http://hdl.handle.net/10289/10196
In general, many factors contribute to the spread of diseases among populations over large geographical areas. In practice, analysis of these factors typically requires expertise of multidisciplinary teams. In this paper, we present a visualization system which aims to support the visual analytics process involving multidisciplinary teams of analysts in colocated collaborative settings. The current prototype system allows coupled and decoupled modes of interaction, using a combination of personal visualizations on private small displays and group visualizations on a shared large display. We have conducted preliminary fieldwork and a review study of this prototype with a group of medical experts who have provided feedback on the current system and suggestions for other usage scenarios, as well as further improvements. We found that our target user group have a generally positive attitude towards the use of a shared display with support for the suggested interaction modes, even though these modes are substantially different from the way their groups currently conduct synchronous collaboration, and that additional support for sharing image and textual data over the geospatial data layer may be required.
© 2016 ACM. This is an author’s accepted revision of the work published in Proceedings of ACSW ‘16 the Australasian Computer Science Week Multiconference. http://dx.doi.org/10.1145/10.1145/2843043.2843374