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| Paper: |
Collaborative Visual Analytics of Large Radio Surveys |
| Volume: |
521, Astronomical Data Analysis Software and Systems XXVI |
| Page: |
264 |
| Authors: |
Vohl, D.; Fluke, C. J.; Hassan, A. H.; Barnes, D. G.; Kilborn, a. V. A. |
| Abstract: |
Radio survey datasets comprise an increasing number of individual observations stored as sets of multi-dimensional data. In large survey projects, astronomers commonly face limitations regarding: 1) interactive visual analytics of sufficiently large subsets of data; 2) synchronous and asynchronous collaboration; and 3) documentation of the discovery workflow. To support collaborative data inquiry, we present encube, a large scale comparative visual analytics framework. encube can utilise large tiled-displays such as the CAVE2 (a hybrid 2D and 3D virtual reality environment powered with a 100 Tflop/s GPU-based supercomputer) for collaborative analysis of large subsets of data from radio surveys. It also works on standard desktops, providing a seamless visual analytics experience regardless of the display ecology. At the heart of encube is a data management unit built in Python – making it simple to incorporate other Python-based astronomical packages and Virtual Observatory capabilities developed within our community. We discuss how encube builds a bridge between the CAVE2 and the classical desktop, preserving all traces of the work completed on either platform – providing a research process that can be continuous regardless of location. |
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