TopoLens: Building a CyberGIS community data service for enhancing the usability of high-resolution national topographic datasets

Hao Hu; Xingchen Hong; Jeff Terstriep; Yan Y. Liu; Michael P. Finn; Johnathan Rush; Jeffrey Wendel; Shaowen Wang

doi:10.1145/2949550.2949652

TopoLens: Building a CyberGIS community data service for enhancing the usability of high-resolution national topographic datasets

Hao Hu, Xingchen Hong, Jeff Terstriep, Yan Y. Liu, Michael P. Finn, Johnathan Rush, Jeffrey Wendel, Shaowen Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English (US)
Title of host publication	Proceedings of XSEDE 2016
Subtitle of host publication	Diversity, Big Data, and Science at Scale
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450347556
DOIs	https://doi.org/10.1145/2949550.2949652
State	Published - Jul 17 2016
Event	Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016 - Miami, United States Duration: Jul 17 2016 → Jul 21 2016

Publication series

Name	ACM International Conference Proceeding Series
Volume	17-21-July-2016

Other

Other	Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016
Country/Territory	United States
City	Miami
Period	7/17/16 → 7/21/16

Keywords

CyberGIS
Data sharing
Elevation data
Geospatial big data
Microservices
Web-based gateway environment

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Online availability

10.1145/2949550.2949652

Library availability

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Hu, H., Hong, X., Terstriep, J., Liu, Y. Y., Finn, M. P., Rush, J., Wendel, J., & Wang, S. (2016). TopoLens: Building a CyberGIS community data service for enhancing the usability of high-resolution national topographic datasets. In Proceedings of XSEDE 2016: Diversity, Big Data, and Science at Scale Article a39 (ACM International Conference Proceeding Series; Vol. 17-21-July-2016). Association for Computing Machinery. https://doi.org/10.1145/2949550.2949652

TopoLens: Building a CyberGIS community data service for enhancing the usability of high-resolution national topographic datasets. / Hu, Hao; Hong, Xingchen; Terstriep, Jeff et al.
Proceedings of XSEDE 2016: Diversity, Big Data, and Science at Scale. Association for Computing Machinery, 2016. a39 (ACM International Conference Proceeding Series; Vol. 17-21-July-2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hu, H, Hong, X, Terstriep, J, Liu, YY, Finn, MP, Rush, J, Wendel, J & Wang, S 2016, TopoLens: Building a CyberGIS community data service for enhancing the usability of high-resolution national topographic datasets. in Proceedings of XSEDE 2016: Diversity, Big Data, and Science at Scale., a39, ACM International Conference Proceeding Series, vol. 17-21-July-2016, Association for Computing Machinery, Conference on Diversity, Big Data, and Science at Scale, XSEDE 2016, Miami, United States, 7/17/16. https://doi.org/10.1145/2949550.2949652

Hu H, Hong X, Terstriep J, Liu YY, Finn MP, Rush J et al. TopoLens: Building a CyberGIS community data service for enhancing the usability of high-resolution national topographic datasets. In Proceedings of XSEDE 2016: Diversity, Big Data, and Science at Scale. Association for Computing Machinery. 2016. a39. (ACM International Conference Proceeding Series). doi: 10.1145/2949550.2949652

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TopoLens: Building a CyberGIS community data service for enhancing the usability of high-resolution national topographic datasets

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Online availability

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