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Immersive and Collaborative Data Visualization Using Virtual Reality Platforms

Donalek, Ciro and Djorgovski, S. G. and Cioc, Alex and Wang, Anwell and Zhang, Jerry and Lawler, Elizabeth and Yeh, Stacy and Mahabal, Ashish and Graham, Matthew and Drake, Andrew and Davidoff, Scott and Norris, Jeffrey S. and Longo, Giuseppe (2014) Immersive and Collaborative Data Visualization Using Virtual Reality Platforms. In: IEEE International Conference on Big Data, 2014. IEEE , Piscataway, NJ, pp. 609-614. ISBN 978-1-4799-5666-1/14.

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Effective data visualization is a key part of the discovery process in the era of “big data”. It is the bridge between the quantitative content of the data and human intuition, and thus an essential component of the scientific path from data into knowledge and understanding. Visualization is also essential in the data mining process, directing the choice of the applicable algorithms, and in helping to identify and remove bad data from the analysis. However, a high complexity or a high dimensionality of modern data sets represents a critical obstacle. How do we visualize interesting structures and patterns that may exist in hyper-dimensional data spaces? A better understanding of how we can perceive and interact with multidimensional information poses some deep questions in the field of cognition technology and human-computer interaction. To this effect, we are exploring the use of immersive virtual reality platforms for scientific data visualization, both as software and inexpensive commodity hardware. These potentially powerful and innovative tools for multi-dimensional data visualization can also provide an easy and natural path to a collaborative data visualization and exploration, where scientists can interact with their data and their colleagues in the same visual space. Immersion provides benefits beyond the traditional “desktop” visualization tools: it leads to a demonstrably better perception of a datascape geometry, more intuitive data understanding, and a better retention of the perceived relationships in the data.

Item Type:Book Section
Related URLs:
URLURL TypeDescription Paper
Djorgovski, S. G.0000-0002-0603-3087
Mahabal, Ashish0000-0003-2242-0244
Graham, Matthew0000-0002-3168-0139
Longo, Giuseppe0000-0002-9182-8414
Additional Information:© 2014 IEEE. S. G. Djorgovski and C. Donalek acknowledge a partial support from the NSF grants HCC-0917814, IIS-1118041, and AST-1313422. Support for this work was provided in part by NASA through a contract issued by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA. S. Davidoff is supported by NASA/JPL Raise-the-Bar and the Space Communication and Networking programs (SCAN). Djorgovski, Donalek, and Davidoff also acknowledge a partial support from a Caltech I-Grant. A. Cioc, J. Zhang, E. Lawler, and S. Yeh were supported in part by the Caltech SURF fellowships. A. Wang contributed to this work as a summer intern at Caltech.
Funding AgencyGrant Number
Space Communication and Networking programs (SCAN)UNSPECIFIED
Caltech Summer Undergraduate Research Fellowship (SURF)UNSPECIFIED
Subject Keywords:astroinformatics; visualization; virtual reality; data analysis; big data; pattern recognition
Record Number:CaltechAUTHORS:20150113-112433536
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Official Citation:Donalek, Ciro; Djorgovski, S.G.; Cioc, Alex; Wang, Anwell; Zhang, Jerry; Lawler, Elizabeth; Yeh, Stacy; Mahabal, Ashish; Graham, Matthew; Drake, Andrew; Davidoff, Scott; Norris, Jeffrey S.; Longo, Giuseppe, "Immersive and collaborative data visualization using virtual reality platforms," Big Data (Big Data), 2014 IEEE International Conference on , vol., no., pp.609,614, 27-30 Oct. 2014 doi: 10.1109/BigData.2014.7004282
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:53626
Deposited By: Ruth Sustaita
Deposited On:13 Jan 2015 19:55
Last Modified:10 Nov 2021 20:04

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