@inproceedings{5d969773a4b342e8a240168b9d091649,
title = "A CyberGIS-Jupyter Framework for Geospatial Analytics at Scale",
abstract = "The interdisciplinary field of cyberGIS (geographic information science and systems (GIS) based on advanced cyberinfrastructure) has a major focus on data-and computation-intensive geospatial analytics. The rapidly growing needs across many application and science domains for such analytics based on disparate geospatial big data poses significant challenges to conventional GIS approaches. This paper describes CyberGIS-Jupyter, an innovative cyberGIS framework for achieving data-intensive, reproducible, and scalable geospatial analytics using the Jupyter Notebook based on ROGER-the first cyberGIS supercomputer. The framework adapts the Notebook with built-in cyberGIS capabilities to accelerate gateway application development and sharing while associated data, analytics and workflow runtime environments are encapsulated into application packages that can be elastically reproduced through cloud computing approaches. As a desirable outcome, data-intensive and scalable geospatial analytics can be efficiently developed and improved, and seamlessly reproduced among multidisciplinary users in a novel cyberGIS science gateway environment.",
keywords = "Computational reproducibility, CyberGIS, Flood mapping, Geospatial big data, Science gateway",
author = "Dandong Yin and Yan Liu and Anand Padmanabhan and Jeff Terstriep and Johnathan Rush and Shaowen Wang",
note = "Funding Information: National Science Foundation (NSF) under grant numbers 1047916 and 1443080. Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.; 2017 Practice and Experience in Advanced Research Computing, PEARC 2017 ; Conference date: 09-07-2017 Through 13-07-2017",
year = "2017",
month = jul,
day = "9",
doi = "10.1145/3093338.3093378",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "PEARC 2017 - Practice and Experience in Advanced Research Computing 2017",
address = "United States",
}