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[submitted] encube: large-scale comparative visualisation and analysis of sets of multidimensional data

Encube is a qualitative, quantitative and comparative visualisation and analysis framework, with application to high-resolution, immersive three-dimensional environments and desktop displays — providing a capable visual analytics experience across the display ecology. Encube includes mechanisms for the support of: 1) interactive visual analytics of sufficiently large subsets of data; 2) synchronous and asynchronous collaboration; and 3) documentation of the discovery workflow. The framework is modular, allowing additional functionalities to be included as required.

Code site:
https://github.com/mivp/encube
Appears in:
http://Vohl D, Barnes DG, Fluke CJ, Poudel G, Georgiou-Karistianis N, Hassan AH, Benovitski Y, Wong TH, Kaluza OL, Nguyen TD, Bonnington CP. (2016) Large-scale comparative visualisation of sets of multidimensional data. PeerJ Computer Science 2:e88 https://doi.org/10.7717/peerj-cs.88 http://Vohl, D., Fluke, C.J., Barnes, D.G., Hassan, A.H., Kilborn, V. A. 2016. “Collaborative visual analytics of radio surveys in the Big Data era”, to appear in Proceedings of IAU Symposium 325 astroinformatics (Sorrento, Italy; 2016), Cambridge Press. http://Vohl, D., Fluke, C.J., Barnes, D.G., Hassan, A.H., Kilborn, V. A. 2016. “Collaborative visual analytics of large radio surveys”, to appear in Proceedings of ADASS XXVI (Trieste, Italy; 2016), ASP Conf. Series. http://Vohl, D., Fluke, C.J., Barnes, D.G., Hassan, A.H., 2016. “An interactive, comparative and quantitative 3D visualisation system for large-scale spectral-cube surveys using CAVE2”, In Proceedings of the twenty-fifth annual Astronomical Data Analysis Software and Systems Conference, In press.
Preferred citation method:

Vohl et al. (2016) Large-scale comparative visualisation of sets of multidimensional data. PeerJ Computer Science 2:e88 https://doi.org/10.7717/peerj-cs.88


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