Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10609/151819
Título : Workflow and tools to track and visualize behavioural data from a Virtual Reality environment using a lightweight GIS
Autoría: Soler-Dominguez, Jose Luis
Contero, Manuel
Alcaniz, Mariano
Citación : Soler-Domínguez, J. L. [Jose Luis], Contero, M. [Manuel] & Alcañiz, M. [Mariano]. (2019). Workflow and tools to track and visualize behavioural data from a Virtual Reality environment using a lightweight GIS. SoftwareX, 10, 100269. doi: 10.1016/j.softx.2019.100269
Resumen : Evaluating user behaviour in Virtual Reality is a challenge for every researcher involved in designing and executing experiments in immersive environments. Behavioural information could lead to relevant findings in presence, engagement or, for example, the mood of the player during a VR experience. Saving this kind of information and exploding it in an appropriate way could lead researchers or even game designers to identify relevant behavioural patterns or correlations. In this article, we are proposing a simple, replicable workflow and a set of scripted tools in order to acquire user’s navigational data and visualize it using the inherent capabilities of a Geographic Information System. Our workflow goes from data acquisition in Unity3D with C# to the final representation in a map using Leaflet, an open-source GIS JavaScript based, passing through the pre-processing of XML files. Using a GIS to visualize navigational data is a flexible, ecological and effective solution that improves productivity and awareness on data storytelling capabilities.
Palabras clave : virtual reality
user experience
geographic information system
human–computer interaction
DOI: https://doi.org/10.1016/j.softx.2019.100269
Tipo de documento: info:eu-repo/semantics/article
Versión del documento: info:eu-repo/semantics/publishedVersion
Fecha de publicación : 16-jul-2019
Licencia de publicación: https://creativecommons.org/licenses/by/4.0/  
Datos relacionados: https://github.com/ElsevierSoftwareX/SOFTX%5F2018%5F69
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