Connecting virtual reality and ecology: a new tool to run seamless immersive experiments in R

Author:

Vercelloni Julie12,Peppinck Jon12,Santos-Fernandez Edgar12,McBain Miles1,Heron Grace1,Dodgen Tanya1,Peterson Erin E.12,Mengersen Kerrie12

Affiliation:

1. Queensland University of Technology, Australian Research Council, Centre of Excellence for Mathematical and Statistical Frontiers, Brisbane, Australia

2. School of Mathematical Sciences, Faculty of Science and Engineering, Queensland University of Technology, Brisbane, Brisbane, QLD, Australia

Abstract

Virtual reality (VR) technology is an emerging tool that is supporting the connection between conservation research and public engagement with environmental issues. The use of VR in ecology consists of interviewing diverse groups of people while they are immersed within a virtual ecosystem to produce better information than more traditional surveys. However, at present, the relatively high level of expertise in specific programming languages and disjoint pathways required to run VR experiments hinder their wider application in ecology and other sciences. We present R2VR, a package for implementing and performing VR experiments in R with the aim of easing the learning curve for applied scientists including ecologists. The package provides functions for rendering VR scenes on web browsers with A-Frame that can be viewed by multiple users on smartphones, laptops, and VR headsets. It also provides instructions on how to retrieve answers from an online database in R. Three published ecological case studies are used to illustrate the R2VR workflow, and show how to run a VR experiments and collect the resulting datasets. By tapping into the popularity of R among ecologists, the R2VR package creates new opportunities to address the complex challenges associated with conservation, improve scientific knowledge, and promote new ways to share better understanding of environmental issues. The package could also be used in other fields outside of ecology.

Funder

Australian Research Council Laureate Fellowship

Publisher

PeerJ

Subject

General Computer Science

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