2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualisations in Virtual Reality

Stefan P. Feyer, Bruno Pinaud, Stephen G. Kobourov, Nicolas Brich, Michael Krone, Andreas Kerren, Michael Behrisch, Falk Schreiber, Karsten Klein

Research output: Working paperPreprintAcademic

Abstract

Relational information between different types of entities is often modelled by a multilayer network (MLN) – a network
with subnetworks represented by layers. The layers of an MLN can be arranged in different ways in a visual representation, however,
the impact of the arrangement on the readability of the network is an open question. Therefore, we studied this impact for several
commonly occurring tasks related to MLN analysis. Additionally, layer arrangements with a dimensionality beyond 2D, which are
common in this scenario, motivate the use of stereoscopic displays. We ran a human subject study utilising a Virtual Reality headset to
evaluate 2D, 2.5D, and 3D layer arrangements. The study employs six analysis tasks that cover the spectrum of an MLN task taxonomy,
from path finding and pattern identification to comparisons between and across layers. We found no clear overall winner. However, we
explore the task-to-arrangement space and derive empirical-based recommendations on the effective use of 2D, 2.5D, and 3D layer
arrangements for MLNs.
Original languageEnglish
Number of pages11
DOIs
Publication statusPublished - 2023

Bibliographical note

CoRR and Accepted Full Paper IEEE VIS 2023

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