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Human Data Interaction

Virtual Reality Based Human Data Interaction

Big Data Analytics has become a major decision support factor in industry and government organisations. With the ever increasing abundance of digital data, questions arise such as

  • How can we effectively detect relevant patterns and multivariate correlation in the data?
  • How can we extract the most meaningful information from these patterns?, and
  • How can this information be effectively communicated to a range of end users?

Limited control and display modalities of modern computing devices usually do not easily facilitate exploration of the multi-dimensionality, heterogeneity, and spatial complexity of large-scale data sets.

In this PhD project, we aim to explore the feasibility of using VR systems for effective human data interaction (HDI). The aim of the project is to develop and experimentally validate VR based HDI systems designed to maximise information communication and user experience when interactively exploring complex data sets. Some of the research questions that we aim to answer include

  • What VR system design aspects are most critical for effective exploration on complex data sets?
  • How can multidimensionality and heterogeneity of large data sets be effectively captured with VR based control and display modalities?
  • What kind of HDI tasks can be performed with VR based systems and how does this compare to conventional systems?
  • What are suitable measures to quantify the success of VR based HDI?

We focus specifically on a forestry domain application in which large point cloud data is used for estimation of forest characteristics.


Elisabeth Adelia Widjojo (Lead), PhD Candidate at School of Engineering and ICT, University of Tasmania
Dr. Winyu Chinthammit, School of Engineering and ICT, University of Tasmania
Dr. Ulrich Engelke, Decision Sciences, CSIRO Data61
Dr. Jon Osborne, School of Land and Food, University of Tasmania


2016 – 2019