Understanding large network datasets through embodied interaction in virtual reality

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• dc.contributor.author Betella, Alberto
• dc.contributor.author Martínez Bueno, Enrique
• dc.contributor.author Kongsantad, Wipawee
• dc.contributor.author Zucca, Riccardo
• dc.contributor.author Arsiwalla, Xerxes D.
• dc.contributor.author Omedas, Pedro
• dc.contributor.author Verschure, Paul F. M. J.
• dc.date.accessioned 2018-11-07T15:38:28Z
• dc.date.available 2018-11-07T15:38:28Z
• dc.date.issued 2014
• dc.description Comunicació presentada a: the 2014 Virtual Reality International Conference (VRIC 2014), celebrada del 9 a l'11 d'abril de 2014 a Laval, Françaca
• dc.description.abstract The quantity of information we are producing is soaring: this generates large amounts of data that are frequently left unexplored. Novel tools are needed to stem this “data deluge”. We developed a system that enhances the understanding of large datasets through embodied navigation and natural gestures using the immersive mixed reality space called “eXperience Induction Machine” (XIM). One of the applications of our system is in the exploration of the human brain connectome: the network of nodes and connections that defines the information flow in the brain. We exposed participants to a connectome dataset using either our system or a state of the art software for visualization and analysis of connectomic data. We measured their understanding and visual memory of the connectome structure. Our results showed that participants retained more information about the structure of the network when using our system. Overall, our system constitutes a novel approach in the exploration and understanding of large network datasets.en
• dc.description.sponsorship The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7- ICT-2009-5) under grant agreement n. 258749 [CEEDS]. Thanks to the Comissionat per a Universitats i Recerca (CUR) del Departament d’Innovació, Universitats i Empresa (DIUE) of the Generalitat de Catalunya and to the European Social Fund for supporting this research.en
• dc.format.mimetype application/pdf
• dc.identifier.citation Betella A, Martinez Bueno E, Kongsantad W, Zucca R, Arsiwalla XD, Omedas P, Verschure PFMJ. Understanding large network datasets through embodied interaction in virtual reality. In: Proceedings of the 2014 Virtual Reality International Conference (VRIC 2014); 2014 Apr 9-11; Laval, France. New York: ACM; 2014. article no. 23. DOI: 10.1145/2617841.2620711
• dc.identifier.doi http://dx.doi.org/10.1145/2617841.2620711
• dc.identifier.isbn 978-145032626-1
• dc.identifier.uri http://hdl.handle.net/10230/35715
• dc.language.iso eng
• dc.publisher ACM Association for Computer Machinery
• dc.relation.ispartof Proceedings of the 2014 Virtual Reality International Conference (VRIC 2014); 2014 Apr 9-11; Laval, France. New York: ACM; 2014. article no. 23.
• dc.rights © ACM, 2014. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 2014 Virtual Reality International Conference (VRIC 2014). http://doi.acm.org/10.1145/2617841.2620711
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Virtual realityen
• dc.subject.keyword Graphs and networksen
• dc.title Understanding large network datasets through embodied interaction in virtual reality
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion