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CyberGIS-compute for enabling computationally intensive geospatial research.

, , , , , , and . SpatialAPI@SIGSPATIAL, page 3:1-3:2. ACM, (2021)

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CyberGIS-Jupyter for reproducible and scalable geospatial analytics., , , , , , and . Concurr. Comput. Pract. Exp., (2019)A distributed resource broker for spatial middleware using adaptive space-filling curve., and . GIS-HPDGIS, page 27-30. ACM, (2010)Local consensus ontologies for B2B-oriented service composition., , and . AAMAS, page 647-654. ACM, (2003)CyberGIS-compute for enabling computationally intensive geospatial research., , , , , , and . SpatialAPI@SIGSPATIAL, page 3:1-3:2. ACM, (2021)Leveraging XSEDE HPC resources to address computational challenges with high-resolution topography data., , , , , , , , and . XSEDE, page 59:1-59:2. ACM, (2014)Where Chicagoans tweet the most: Semantic analysis of preferential return locations of Twitter users., , , , and . UrbanGIS@SIGSPATIAL, page 55-58. ACM, (2015)A CyberGIS-Jupyter Framework for Geospatial Analytics at Scale., , , , , and . PEARC, page 18:1-18:8. ACM, (2017)Happy or not: Generating topic-based emotional heatmaps for Culturomics using CyberGIS., , , , and . eScience, page 1-6. IEEE Computer Society, (2012)Developing the Modular Information Provider (MIP) to Support Interoperable Grid Information Services., , , , and . GCC, page 448-453. IEEE Computer Society, (2006)HPDGIS 2010 workshop report: ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems (San Jose, California - November 2, 2010)., , , , , and . ACM SIGSPATIAL Special, 3 (1): 8-9 (2011)