Data navigation and visualisation: navigating coordinated multiple views of data
  The field of coordinated and multiple views (CMVs) has been for over a decade, a promising technique for enhancing data visualization, yet that promise remains unfulfilled. Current CMVs lack a platform for flexible execution of certain kinds of open-ended tasks consequently users’ are unable to achieve novel objectives. Navigation of data, though an important aspect of interactive visualization, has not generated the level of attention it should from the human computer interaction community. A number of frameworks for and categorization of navigation techniques exist, but further detailed studies are required to highlight the range of benefits improved navigation can achieve in the use of interactive tools such as CMVs.
This thesis investigates the extent of support offered by CMVs to people navigating information spaces, in order to discover data, visualize these data and retrieve adequate information to achieve their goals. It also seeks to understand the basic principle of CMVs and how to apply its procedure to achieve successful navigation.
Three empirical studies structured around the user’s goal as they navigate CMVs are presented here. The objective of the studies is to propose a simple, but strong, design procedure to support future development of CMVs. The approach involved a comparative analysis of qualitative and quantitative experiments comprising of categorised navigation tasks carried out, initially on existing CMVs and subsequently on CMVs which had been redesigned applying the proposed design procedure. The findings show that adequate information can be retrieved, with successful navigation and effective visualization achieved more easily and in less time, where metadata is provided alongside the relevant data within the CMVs to facilitate navigation. This dissertation thus proposes and evaluates a novel design procedure to aid development of more navigable CMVs.

  • Dates:

    2010 to 2015

  • Qualification:

    Doctorate (PhD)

Project Team