TY - BOOK
T1 - Visualisation and Exploration of Personal Data in Virtual Reality
AU - Millais, Patrick
N1 - Supervised by Simon Jones
PY - 2017/6/11
Y1 - 2017/6/11
N2 - Recent research in the personal informatics feld has focused on correlating aspects of self-tracked data, supporting users to arrive at meaningful insights when reecting on aggregated datasets. To date, no research has been completed on how users could explorepersonal data using virtual reality, and the opportunities this presents for users' understanding of multidimensional datasets.In this study we evaluate the open-ended exploration of multidimensional datasets using two separate visualisations. Be The Data immerses users in a three-dimensional scatterplot, allowing them to interpret a dataset from new perspectives. The second visualisation,Parallel Planes, enables a multi-faceted dataset to be chained together, supporting users in perceiving a holistic overview of interrelated dimensions.Through an insight-based evaluation methodology, we find that users conducted depth based explorations of the Parallel Planes visualisation, arriving at valuable and signicant insights through hypothesising about the data. We also find that there was no overall task workload difference between traditional visualisation paradigms and virtual reality. We conclude by outlining future research directions, and making recommendations for future evaluation approaches for data visualisation in VR.
AB - Recent research in the personal informatics feld has focused on correlating aspects of self-tracked data, supporting users to arrive at meaningful insights when reecting on aggregated datasets. To date, no research has been completed on how users could explorepersonal data using virtual reality, and the opportunities this presents for users' understanding of multidimensional datasets.In this study we evaluate the open-ended exploration of multidimensional datasets using two separate visualisations. Be The Data immerses users in a three-dimensional scatterplot, allowing them to interpret a dataset from new perspectives. The second visualisation,Parallel Planes, enables a multi-faceted dataset to be chained together, supporting users in perceiving a holistic overview of interrelated dimensions.Through an insight-based evaluation methodology, we find that users conducted depth based explorations of the Parallel Planes visualisation, arriving at valuable and signicant insights through hypothesising about the data. We also find that there was no overall task workload difference between traditional visualisation paradigms and virtual reality. We conclude by outlining future research directions, and making recommendations for future evaluation approaches for data visualisation in VR.
KW - Computer performance
KW - cache utilization
KW - TLB
M3 - Other report
T3 - Department of Computer Science Technical Report Series
BT - Visualisation and Exploration of Personal Data in Virtual Reality
PB - Department of Computer Science, University of Bath
CY - Bath, U. K.
ER -