Vohl Dany
Centre for Astrophysics & Supercomputing – Swinburne University of Technology, Hawthorn

Miscellaneous Information

Miscellaneous Information

Abstract Reference: 30256
Identifier: P2.23
Presentation: Poster presentation
Key Theme: 2 Management of Scientific and Data Analysis Projects

Collaborative visual analytics of large radio surveys

Vohl Dany, Fluke Christopher J., Hassan Amr H., Barnes David G., Kilborn Virginia A.

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 — allowing the research process to continue wherever you are.