2016/10/03 by D. Vohl, Dany Vohl, David G. Barnes +10
Computer Science · Decision Sciences · Physics and Astronomy · #Artificial intelligence #Computer science #Data Visualization and Analytics #Data mining #Data science #Data visualization #Documentation #Human–computer interaction #Modularity (biology) #Operating system #Peer-to-Peer Network Technologies #Process (computing) #Scale (ratio) #Scientific Computing and Data Management #Variety (cybernetics) #Visualization #astro-ph.IM #cs.HC
paper · pdf · doi:10.7717/peerj-cs.88
26 pages, 11 figures, 5 tables. Accepted for publication in PeerJ Computer Science
arxiv created 2016/10/03 · arxiv updated 2016/10/07 · openalex publication_date 2016/10/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We present encube —a qualitative, quantitative and comparative visualisation and analysis system, with application to high-resolution, immersive three-dimensional environments and desktop displays. encube extends previous comparative visualisation systems by considering: (1) the integration of comparative visualisation and analysis into a unified system; (2) the documentation of the discovery process; and (3) an approach that enables scientists to continue the research process once back at their desktop. Our solution enables tablets, smartphones or laptops to be used as interaction units for manipulating, organising, and querying data. We highlight the modularity of encube , allowing additional functionalities to be included as required. Additionally, our approach supports a high level of collaboration within the physical environment. We show how our implementation of encube operates in a large-scale, hybrid visualisation and supercomputing environment using the CAVE2 at Monash University, and on a local desktop, making it a versatile solution. We discuss how our approach can help accelerate the discovery rate in a variety of research scenarios.