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A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

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An exploratory study combining Virtual Reality and Semantic Web for life science research using Graph2VR.

Alexander J Kellmann, Sander van den Hoek¹, Max Postema¹

¹Department of Genetics, Genomics Coordination Center, University Medical Center Groningen, Antonius Deusinglaan 1, Groningen, Groningen 9713 AV, The Netherlands.

Database : the Journal of Biological Databases and Curation

|May 20, 2025

Summary

This summary is machine-generated.

Virtual reality (VR) enhances exploration of large Linked Data graphs for researchers. Graph2VR shows potential in life sciences for data visualization and enrichment, with recommendations for future development.

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Area of Science:

Bioinformatics
Data Science
Virtual Reality Applications

Background:

Linked Data graphs and SPARQL queries are complex for researchers to navigate.
Virtual Reality (VR) offers immersive environments for data exploration.

Purpose of the Study:

Evaluate Graph2VR, a VR prototype, for navigating Linked Data graphs in life sciences.
Assess Graph2VR's utility in realistic use cases involving cohort studies, genomic data, and ontology enrichment.

Main Methods:

Applied Graph2VR to visualize metadata from EUCAN Connect cohort studies.
Utilized Graph2VR for genomic data from rare disease patients (Variant Interpretation Pipeline to RDF).
Employed Graph2VR to enrich the Dutch Anatomical Therapeutic Chemical code Ontology with Drugbank IDs.

Main Results:

Graph2VR demonstrated potential for data exploration and enrichment across diverse life science datasets.
Identified limitations of Graph2VR in handling very large knowledge graphs.
Showcased VR's capability for navigating extensive three-dimensional knowledge graphs.

Conclusions:

VR environments like Graph2VR hold significant promise for navigating large-scale knowledge graphs.
Recommendations are provided for optimizing data preparation and VR tooling for enhanced usability.