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Accepted (AM)Open Access (License Unspecified), Open
Journal article
Top Ten Challenges in Extreme-Scale Visual Analytics
IEEE Computer Graphics and Applications, v 32(4)
08 May 2012
Abstract
In the current special issue of IEEE Computer Graphics and Applications (CG&A), researchers share their research and development (R&D) findings and results on applying visual analytics to extreme-scale data. Having surveyed the special issue articles and other related R&D efforts in the area, we have identified what we consider to be the top challenges of extreme-scale visual analytics. To cater to the diverse readership of CG&A, our discussion evaluates challenges in all areas of the field, including algorithms, hardware, software, engineering, and social issues.
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Details
- Title
- Top Ten Challenges in Extreme-Scale Visual Analytics
- Creators
- Pak C Wong - Pacific Northwest National LaboratoryHan-Wei Shen - The Ohio State UniversityChristopher R JohnsonChaomei Chen - Drexel UniversityRob RossPacific Northwest National Laboratory (PNNL), Richland, WA (US), Environmental Molecular Sciences Laboratory (EMSL)
- Publication Details
- IEEE Computer Graphics and Applications, v 32(4)
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science; [Retired Faculty]
- Web of Science ID
- WOS:000305499000011
- Scopus ID
- 2-s2.0-84865212981
- Other Identifier
- 991019168291804721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Software Engineering