=Paper=
{{Paper
|id=Vol-3415/paper-35
|storemode=property
|title=Visualisation and Exploration of Linked Data Using Virtual Reality - a preview of
                                       Graph2VR
|pdfUrl=https://ceur-ws.org/Vol-3415/paper-35.pdf
|volume=Vol-3415
|dblpUrl=https://dblp.org/rec/conf/swat4ls/KellmannPKSWES23
}}
==Visualisation and Exploration of Linked Data Using Virtual Reality - a preview of
                                       Graph2VR==
<pdf width="1500px">https://ceur-ws.org/Vol-3415/paper-35.pdf</pdf>
<pre>
Visualisation and Exploration of Linked Data Using
Virtual Reality - a preview of Graph2VR
Alexander Kellmann1,2,∗ , Max Postema1,2 , Joris de Keijser1,2 , Pjotr Svetachov1 ,
Becca Wilson3 , Esther van Enckevort1,2 and Morris A. Swertz1,2
1
  University of Groningen, Groningen, The Netherlands
2
  University Medical Center Groningen, Groningen, The Netherlands
3
  University of Liverpool, Liverpool, United Kingdom


                                         Abstract
                                         We have reviewed existing solutions and created a prototype, Graph2VR, to work with graphs in Virtual
                                         Reality based on SPARQL queries, with the aim to help scientific applications such as cohort data
                                         harmonisation or rare disease human phenotype ontology navigation.

                                         Keywords
                                         Linked Data Visualisation, RDF Visualisation, Virtual Reality, Graph exploration, SPARQL, DotNetRDF




1. Introduction
Linked Data is a best practice method to share and reuse data, in particular complex knowledge
graphs. Visual processing of information and structures in large graphs comes naturally to
people, and so development of tools for the visualisation of Linked Data has become a field
of research interest in recent years. Graph2VR is an explorative study on how visualization
of Linked Data in Virtual Reality as 3D graphs might change/improve the way the user can
interact with semantic data graphs.


2. Results
We have surveyed existing semantic web and VR visualisation tools. We have implemented
a working prototype that enables semantic graph navigation. And we did a survey where 34
human test subjects used the prototype to explore semantic data graphs using VR. Figure 1
shows a screenshot of Graph2VR after a SPARQL query was executed. The natural virtual
environment offers another dimension and therefore more space to visualize graphs.



The 14th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences, 2023, Feb
13–16, 2023, Basel, CH
∗
    Corresponding author.
Envelope-Open a.j.kellmann@umcg.nl (A. Kellmann)
Orcid 0000-0001-6108-5552 (A. Kellmann); 0000-0003-2294-593X (B. Wilson); 0000-0002-2440-3993 (E. v. Enckevort);
0000-0002-0979-3401 (M. A. Swertz)
                                       © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
    CEUR
    Workshop
    Proceedings
                  http://ceur-ws.org
                  ISSN 1613-0073
                                       CEUR Workshop Proceedings (CEUR-WS.org)
Figure 1: Screenshot of Graph2VR.


3. Future works
Graph2VR is currently undergoing final evaluation and user testing in order to quantify the
usability of the software, awaiting write-up of the results in a full research paper. At publication,
the Graph2VR prototype software will be made open source.


Acknowledgments

T h i s work was s u p p o r t e d by EUCAN− c o n n e c t , a f e d e r a t e d FAIR
      p l a t f o r m e n a b l i n g l a r g e − s c a l e a n a l y s i s o f high − v a l u e c o h o r t
      d a t a c o n n e c t i n g Europe and Canada i n p e r s o n a l i s e d h e a l t h .
      T h i s p r o j e c t r e c e i v e d f u n d i n g from t h e European Union ’ s
      H o r i z o n 2 0 2 0 r e s e a r c h and i n n o v a t i o n programme u n d e r g r a n t
      a g r e e m e n t No 8 2 4 9 8 9 .

</pre>