TY - GEN
T1 - TopoLens
T2 - Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016
AU - Hu, Hao
AU - Hong, Xingchen
AU - Terstriep, Jeff
AU - Liu, Yan Y.
AU - Finn, Michael P.
AU - Rush, Johnathan
AU - Wendel, Jeffrey
AU - Wang, Shaowen
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/7/17
Y1 - 2016/7/17
N2 - Geospatial data, often embedded with geographic references, are important to many application and science domains, and represent a major type of big data. The increased volume and diversity of geospatial data have caused serious usability issues for researchers in various scientific domains, which call for innovative cyberGIS solutions. To address these issues, this paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Through the collaboration between the CyberGIS Center at the University of Illinois at Urbana-Champaign (UIUC) and the U.S. Geological Survey (USGS), a community data service for accessing, customizing, and sharing digital elevation model (DEM) and its derived datasets from the 10-meter national elevation dataset, namely TopoLens, is created to demonstrate the workflow integration of geospatial big data sources, computation, analysis needed for customizing the original dataset for end user needs, and a friendly online user environment. TopoLens provides online access to precomputed and on-demand computed high-resolution elevation data by exploiting the ROGER supercomputer. The usability of this prototype service has been acknowledged in community evaluation.
AB - Geospatial data, often embedded with geographic references, are important to many application and science domains, and represent a major type of big data. The increased volume and diversity of geospatial data have caused serious usability issues for researchers in various scientific domains, which call for innovative cyberGIS solutions. To address these issues, this paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Through the collaboration between the CyberGIS Center at the University of Illinois at Urbana-Champaign (UIUC) and the U.S. Geological Survey (USGS), a community data service for accessing, customizing, and sharing digital elevation model (DEM) and its derived datasets from the 10-meter national elevation dataset, namely TopoLens, is created to demonstrate the workflow integration of geospatial big data sources, computation, analysis needed for customizing the original dataset for end user needs, and a friendly online user environment. TopoLens provides online access to precomputed and on-demand computed high-resolution elevation data by exploiting the ROGER supercomputer. The usability of this prototype service has been acknowledged in community evaluation.
KW - CyberGIS
KW - Data sharing
KW - Elevation data
KW - Geospatial big data
KW - Microservices
KW - Web-based gateway environment
UR - https://www.scopus.com/pages/publications/84989170531
U2 - 10.1145/2949550.2949652
DO - 10.1145/2949550.2949652
M3 - Conference contribution
AN - SCOPUS:84989170531
T3 - ACM International Conference Proceeding Series
BT - Proceedings of XSEDE 2016
PB - Association for Computing Machinery
Y2 - 17 July 2016 through 21 July 2016
ER -