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TopoLens: Building a CyberGIS Community Data Service for Enhancing the Usability of High-resolution National Topographic Datasets

Authors:

Jeff Terstriep,

Michael P. Finn,

Johnathan Rush,

Jeffrey Wendel,

Shaowen WangAuthors Info & Claims

XSEDE16: Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale

Article No.: 39, Pages 1 - 8

https://doi.org/10.1145/2949550.2949652

Published: 17 July 2016 Publication History

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.

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Cited By

Liu YMaidment DTarboton DZheng XWang S(2018)A CyberGIS Integration and Computation Framework for High‐Resolution Continental‐Scale Flood Inundation MappingJAWRA Journal of the American Water Resources Association10.1111/1752-1688.1266054:4(770-784)Online publication date: 12-Jun-2018
https://doi.org/10.1111/1752-1688.12660
Landeta PVásquez JRea XGarcía-Santillán I(2018)Edition, Publication and Visualization of Geoservices Using Open-Source ToolsInformation and Communication Technologies of Ecuador (TIC.EC)10.1007/978-3-030-02828-2_20(266-280)Online publication date: 18-Oct-2018
https://doi.org/10.1007/978-3-030-02828-2_20
Yin DLiu YHu HTerstriep JHong XPadmanabhan AWang S(2018)CyberGIS‐Jupyter for reproducible and scalable geospatial analyticsConcurrency and Computation: Practice and Experience10.1002/cpe.504031:11Online publication date: 6-Nov-2018
https://doi.org/10.1002/cpe.5040
Show More Cited By

TopoLens: Building a CyberGIS Community Data Service for Enhancing the Usability of High-resolution National Topographic Datasets
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
2. Information systems
  1. Information systems applications

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cover image ACM Other conferences

XSEDE16: Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale

July 2016

405 pages

ISBN:9781450347556

DOI:10.1145/2949550

General Chair:
Kelly Gaither
Texas Advanced Computing Center

Copyright © 2016 ACM.

© 2016 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the United States Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

In-Cooperation

SIGAPP: ACM Special Interest Group on Applied Computing
Xsede: Xsede
San Diego Supercomputer Center: San Diego Supercomputer Center
NICS: National Institute for Computational Sciences
University of Illinois: The University of Illinois at Urbana-Champaign

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 July 2016

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XSEDE16

XSEDE16: Diversity, Big Data, and Science at Scale

July 17 - 21, 2016

Miami, USA

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Overall Acceptance Rate 129 of 190 submissions, 68%

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Cited By

Liu YMaidment DTarboton DZheng XWang S(2018)A CyberGIS Integration and Computation Framework for High‐Resolution Continental‐Scale Flood Inundation MappingJAWRA Journal of the American Water Resources Association10.1111/1752-1688.1266054:4(770-784)Online publication date: 12-Jun-2018
https://doi.org/10.1111/1752-1688.12660
Landeta PVásquez JRea XGarcía-Santillán I(2018)Edition, Publication and Visualization of Geoservices Using Open-Source ToolsInformation and Communication Technologies of Ecuador (TIC.EC)10.1007/978-3-030-02828-2_20(266-280)Online publication date: 18-Oct-2018
https://doi.org/10.1007/978-3-030-02828-2_20
Yin DLiu YHu HTerstriep JHong XPadmanabhan AWang S(2018)CyberGIS‐Jupyter for reproducible and scalable geospatial analyticsConcurrency and Computation: Practice and Experience10.1002/cpe.504031:11Online publication date: 6-Nov-2018
https://doi.org/10.1002/cpe.5040
Yin DLiu YPadmanabhan ATerstriep JRush JWang SHart D(2017)A CyberGIS-Jupyter Framework for Geospatial Analytics at ScalePractice and Experience in Advanced Research Computing 2017: Sustainability, Success and Impact10.1145/3093338.3093378(1-8)Online publication date: 9-Jul-2017
https://dl.acm.org/doi/10.1145/3093338.3093378

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