| Publication Type |
pre-print |
| Department |
Computing, School of |
| Creator |
Pascucci, Valerio |
| Other Author |
Wong, Pak Chung; Shen, Han-Wei |
| Title |
Extreme-scale visual analytics |
| Date |
2012-01-01 |
| Description |
The September/October 2004 CG&A introduced the term visual analytics (VA) to the computer science literature.1 In 2005, an international advisory panel with representatives from academia, industry, and government defined VA as "the science of analytical reasoning facilitated by interactive visual interfaces."2 VA has grown rapidly into a vibrant R&D community offering data analytics and exploration solutions to both scientific and nonscientific problems in diverse domains and platforms. This special issue further examines advances related to extreme-scale VA problems, their analytical and computational challenges, and their real-world applications. |
| Type |
Text |
| Publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
| Volume |
32 |
| Issue |
4 |
| First Page |
23 |
| Last Page |
25 |
| Dissertation Institution |
University of Utah |
| Language |
eng |
| Bibliographic Citation |
Wong, P.C., Shen, H.-W., & Pascucci, V. (2012). Extreme-scale visual analytics. IEEE Computer Graphics and Applications, 32(4), no. 6265053, 23-5. |
| Rights Management |
(c) 2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
| Format Medium |
application/pdf |
| Format Extent |
2,313,765 bytes |
| Identifier |
uspace,17750 |
| ARK |
ark:/87278/s65x2tqg |
| Setname |
ir_uspace |
| ID |
708111 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s65x2tqg |
