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CyberGIS for data-intensive knowledge discovery
| Content Provider | ACM Digital Library |
|---|---|
| Author | Hu, Hao Padmanabhan, Anand Liu, Yan Wang, Shaowen Lin, Tao Soltani, Kiumars |
| Abstract | CyberGIS is an interdisciplinary field combining advanced cyberinfrastructure, geographic information science and systems (GIS), spatial analysis and modeling, and a number of geospatial domains to improve research productivity and enable scientific breakthroughs. It has emerged as a new-generation GIS that enables synergistic advances in data-driven knowledge discovery, visualization and visual analytics, and collaborative problem solving and decision making. This paper describes a cutting-edge cyberGIS software environment from a system perspective. Two case studies focus on elucidating BioScope: a data-driven and computationally intensive cyberGIS application for bioenergy supply chain optimization, and MovePattern: interactive and multi-scale visual analytics for complex and massive movement data extracted from the Twitter steaming application programming interfaces. These studies demonstrate widely accessible capabilities of cyberGIS for resolving the variety, velocity, and volume of spatial big data to enable unprecedented data-intensive knowledge discovery. |
| Starting Page | 26 |
| Ending Page | 33 |
| Page Count | 8 |
| File Format | |
| ISSN | 19467729 |
| DOI | 10.1145/2744700.2744704 |
| Journal | SIGSPATIAL Special (SIGSPACIAL) |
| Volume Number | 6 |
| Issue Number | 2 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-06-21 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Content Type | Text |
| Resource Type | Article |
