Nu-view: A Visualization System for Collaborative Co-located Analysis of Geospatial Disease Data

Masood Masoodian, Saturnino Luz, David Kavenga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 co-located 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.
Original languageEnglish
Title of host publicationProceedings of the Australasian Computer Science Week Multiconference
Place of PublicationNew York, NY, USA
PublisherACM Association for Computing Machinery
Pages48:1-48:10
ISBN (Print)978-1-4503-4042-7
DOIs
Publication statusPublished - 25 Jan 2016

Publication series

NameACSW '16
PublisherACM

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