Collaborative visual analytics 
 of radio surveys in the Big Data era Dany Vohl | Astroinformatics 2016 | In collaboration with Christopher J. Fluke, Amr H. Hassan, 
 David G. Barnes (Monash University) and Virginia A. Kilborn @danyvohl 

Background Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 Meidt, Rand & Merrifield, 2009. ApJ. doi:10.1088/0004-637X/702/1/277 

Background Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 Large-Scale Spectral-Cube Surveys • large # of spectral-cubes, each with large # of sources • e.g. Apertif: 20,000 spectral-cubes, each containing ~100 sources
 (Verheijen et al. 2009, Punzo et al. 2015) ASKAP Cube Dimensions 
 6144 x 6144 x 16384
 APERTIF Cube Dimensions 
 2048 x 2048 (spatial) x 16384 (spectral)
 0.25 TB 

Background Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 Visualisation & 
 Analysis Common limitations of large surveys Synchronous & async.
 collaboration Documentation of 
 discovery workflow 

encube — Collaborative visual analytics Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 DOI 10.7717/peerj-cs.88 arXiv:1610.00760 

encube — Collaborative visual analytics Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 Interaction Unit Panel 1 Panel 2 Panel 3 Panel 4 Display Units Manager Unit Process-Render Units Process data / Render visualisation Metadata server / scheduler / Workflow serialization control / query / visualise visualise data cubes Input/output layer Process layer Panel 1 Panel 2 Panel 3 Panel 4 Panel 1 Panel 2 Panel 3 Panel 4 … … Simple Instruction Multiple Visualisation 

encube — Collaborative visual analytics Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 

encube — Collaborative visual analytics Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 • Part immersive visualization environment • 8-meter diameter working area, • 320 degree panoramic display system; • 80 stereo-capable displays • arranged in 20 four-panel columns, • 84 million pixels • Part supercomputer • 40 GPUs • ∼100 TFLOP/s of integrated 
 GPU-based processing power Hybrid 2D/3D virtual reality environment for immersive simulation and information analysis. 

encube — Collaborative visual analytics Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 Data: The HI Nearby Galaxy Survey (THINGS, Walter et al. 2008 ) Simple Instruction Multiple Visualisations 

encube — Collaborative visual analytics Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 Flux (Jy) P(Flux) Simple Instruction Multiple Visualisations 

encube — Collaborative visual analytics Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 Simple Instruction Multiple Visualisations 

Workflow serialisation a key to synchronous and asynchronous collaboration Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 Documentation of 
 discovery workflow Synchronous & 
 asynchronous collaboration 

On-going work Integration with GraphTIVA and the Cloud Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 Rendered the whole southern sky 
 from 387 cubes (HIPASS survey) Data from Russell Jurek, ATNF 2013 :
 Hassan, Fluke, Barnes & Kilborn 
 (Swinburne University of Technology) 3D Visualisation with GraphTIVA • 96 GPUs cluster • 0.5 TB Cube • 7–10 frames per second 

On-going work Integration with GraphTIVA and the Cloud Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 

Final Thoughts Dany Vohl | Astroinformatics 2016 | 22 Oct. 2016 • The CAVE2 permits new approaches to, and applications of, visual analytics
 • It offers great potential to accelerate the discovery process 
 in the era of large-scale spectral-cube surveys. 
 • encube provides a best of both worlds approach through support of high-end, collaborative visualisation in the CAVE2 while also supporting desktop-based analysis and discovery. This work was enabled and supported by the Monash Immersive Visualisation Platform (http://monash.edu/mivp). Thanks to CaveHD team. Thanks to the Astronomical Society of Australia for their travel financial support. DOI 10.7717/peerj-cs.88 arXiv:1610.00760