Research Commons
      • Browse 
        • Communities & Collections
        • Titles
        • Authors
        • By Issue Date
        • Subjects
        • Types
        • Series
      • Help 
        • About
        • Collection Policy
        • OA Mandate Guidelines
        • Guidelines FAQ
        • Contact Us
      • My Account 
        • Sign In
        • Register
      View Item 
      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computing and Mathematical Sciences Papers
      • View Item
      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computing and Mathematical Sciences Papers
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Nu-view: A visualization system for collaborative Co-located analysis of geospatial disease data

      Masoodian, Masood; Luz, Saturnino; Kavenga, David
      Thumbnail
      Files
      auic16.pdf
      Accepted version, 11.25Mb
      DOI
       10.1145/2843043.2843374
      Find in your library  
      Citation
      Export citation
      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: https://hdl.handle.net/10289/10196
      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 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.
      Date
      2016
      Type
      Conference Contribution
      Publisher
      ACM
      Rights
      © 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
      Collections
      • Computing and Mathematical Sciences Papers [1455]
      Show full item record  

      Usage

      Downloads, last 12 months
      117
       
       
       

      Usage Statistics

      For this itemFor all of Research Commons

      The University of Waikato - Te Whare Wānanga o WaikatoFeedback and RequestsCopyright and Legal Statement