AAG 2020 Symposium on Frontiers in CyberGIS and Geospatial Data Science

Description

Geospatial data science is an emerging interdisciplinary and transdisciplinary field that rests at the intersection of three broad knowledge domains: (1) geospatial sciences and technologies, (2) mathematical and statistical sciences, and (3) cyberinfrastructure and computational sciences. The center of this disciplinary intersection is defined by the synergy and interaction that exist between big data and cyberGIS with geospatial principles guiding critical thinking, discovery, and innovation (Figure 1) (Wang and Goodchild, 2018).  CyberGIS is defined as geographic information science and systems (GIS) based on advanced computing and cyberinfrastructure. Though geospatial big data have played important roles in many domains with significant societal impacts, geospatial data science remains to be established as a means of advancing data-intensive geographic research and education in the era of big data and cyberGIS. 

Figure 1: The scope of geospatial data science

At the AAG 2020 annual meeting, the Symposium on Frontiers in CyberGIS and Geospatial Data Science will provide an exciting and timely forum for sharing recent progress and future trends in cyberGIS and geospatial data science. A suite of paper and panel sessions will outline the leading-edge of cyberGIS and geospatial data science. Particular attention will be given to the following themes: 

• Foundations, principles, and theories of cyberGIS and geospatial data science
• Data-driven geography
• Artificial intelligence and data-intensive approaches to geographic problem solving
• Reproducibility and replicability in geographic research
• Geographic knowledge discovery enabled by cyberGIS
• Advances and challenges in educating the next generation of geographers
• Spatial cyberinfrastructure.

Sponsorship

Cyberinfrastructure Specialty Group (CISG), Geographic Information Science and Systems (GISS) Specialty Group, Remote Sensing Specialty Group, and Spatial Analysis and Modeling (SAM) Specialty Group

Panel Sessions (Incomplete)

• CyberGIS and Geospatial Data Science Curriculum
• CyberGIS and Geospatial Data Science: Frontiers and Opportunities
• Uncertainty and Bias in Geospatial Data Science

Paper Sessions (Incomplete)

• Reproducibility and Replicability in Geography (Chair: Peter Kedron)
• Spatial Machine Learning and Deep Learning (Chair: Jin Xing)
• Data-Intensive Geography (Chair: Harvey Miller)
• Education Advances and Challenges in CyberGIS and Geospatial Data Science (Chair: Diana Sinton)
• Foundations, Principles, and Theories of CyberGIS and Geospatial Data Science (Chair: Shaowen Wang)
• Spatial Prediction (Chair: Micheal Goodchild)
• Big Data Computing for Geospatial Applications (Chair: Zhenlong Li)
• CyberGIS-enabled Spatial Modeling and Simulation (Chair: Jeon-Young Kang)
• CyberGIS-enabled Urban Informatics and Urban Computing (Chair: Shaohua Wang)
• Advances in Computational Approaches for Spatial Analysis and Modeling (Chair: Minrui Zheng)
• Synergizing Geospatial Data Science with Domain Applications I: Societal Impacts of Climate Change (Chair: Jing Gao)
• Applications of CyberGIS and Geospatial Data Science II: Public Health (Chair: Guofeng Cao)
• Synergizing Geospatial Data Science with Domain Applications III: Disaster Management (Chair: Zhe Zhang)

If you are interested in organizing any sessions or panels as part of the Symposium, please contact Jeon-Young Kang via geokang@illinois.edu To present a paper in any of the Symposium sessions, please register and submit your abstract online, and email your presenter identification number (PIN), paper title, and abstract to geokang@illinois.edu by the AAG submission deadline (November, 12, 2019).  We look forward to your submissions and participation!

Co-Chairs

• Guofeng Cao, Texas Tech University
• Jing Gao, University of Delaware
• Jeon-Young Kang, University of Illinois at Urbana-Champaign
• Peter Kedron, Arizona State University
• Harvey Miller, the Ohio State University
• Shaowen Wang, University of Illinois at Urbana-Champaign
• Dawn Wright, Esri and Oregon State University
• Zhe Zhang, Texas A&M University

Program Committee

• Jared Aldstadt, State University of New York at Buffalo
• Luc Anselin, University of Chicago
• Marc Armstrong, the University of Iowa
• Peter Atkinson, Lancaster University
• Budhendra L. Bhaduri, Oak Ridge National Laboratory
• Ling Bian, State University of New York at Buffalo
• Christopher Brunsdon, Maynooth University
• Yanjia Cao, Stanford University
• Alexis Comber, University of Leeds
• Zhenhong Du, Zhejiang University
• Giles Foody, University of Nottingham
• Stewart Fotheringham, Arizona State University
• Song Gao, University of Wisconsin – Madison
• Michael Goodchild, University of California – Santa Barbara
• Alexander Hohl, The University of Utah
• Yingjie Hu, State University of New York at Buffalo
• Myeong-Hun Jeong, Chosun University
• Jeon-Young Kang, University of Illinois at Urbana-Champaign
• Carsten Kessler, Aalborg University Copenhagen
• Mei-Po Kwan, University of Illinois at Urbana-Champaign
• Wenwen Li, Arizona State University
• Zhenlong Li, University of South Carolina
• Yu Liu, Peking University
• Binbin Lu, Wuhan University
• Steven Manson, University of Minnesota
• Ali Mansourian, Lund University
• Grant McKenzie, McGill University
• Shawn Newsam, University of California – Merced
• Anand Padmanabhan, University of Illinois at Urbana-Champaign
• Ed Parsons, Google
• Serge Rey, University of California – Riverside
• Shih-Lung Shaw, University of Tennessee – Knoxville
• Wen-zhong Shi, Hong Kong Polytechnic University
• Eric Shook, University of Minnesota – Twin Cities
• Kathleen Stewart, University of Maryland – College Park
• Daniel Sui, University of Arkansas
• Wenwu Tang, University of North Carolina at Charlotte
• Tao Pei, Chinese Academy of Sciences
• Ming-Hsiang (Ming) Tsou, San Diego State University
• E. Lynn Usery, U.S. Geological Survey
• Fahui Wang, Louisiana State University
• Shaohua Wang, University of Illinois at Urbana-Champaign
• Monica Wachowicz, University of New Brunswick
• John Wilson, University of Southern California
• Ningchuan Xiao, the Ohio State University
• Chaowei (Phil) Yang, George Mason University
• Xinyue Ye, New Jersey Institute of Technology
• May Yuan, University of Texas at Dallas
• Chuanrong Zhang, University of Connecticut
• Minrui Zheng, University of North Carolina at Charlotte

References

• Armstrong, M.P., Wang, S., and Zhang, Z. (2018) “The Internet of Things and Fast Data Streams: Prospects for Geospatial Data Science in Emerging Information Ecosystems.” Cartography and Geographic Information Science, https://doi.org/10.1080/15230406.2018.1503973
• Bowlick, F.J. and Wright, D.J. (2018) “Digital Data-centric Geography: Implications for Geography’s Frontier”. The Professional Geographer, DOI: 10.1080/00330124.2018.1443478
• Brunsdon, C. (2016). “Quantitative Methods I: Reproducible Research and Quantitative Geography.” Progress in Human Geography, 40(5), 687–96.
• Kedron, P., Frazier, A., Trgovac, A., Nelson, T., and Fotheringham, S. (2019) “Reproducibility and Replicability in Geographical Analysis” Geographical Analysis, https://doi.org/10.1111/gean.12221 
• Konkol, M., Kray, C., and Pfeiffer, M. (2019a). “Computational reproducibility in geoscientific papers: Insights from a series of studies with geoscientists and a reproduction study”. International Journal of Geographical Information Science, 33(2), 408-429.
• Miller H.J. (2017) “Geographic Information Observatories and Opportunistic GIScience”. Progress in Human Geography, 41, 489-500
• Miller, H.J. (2018) “Mesogeography: Social physics, GIScience and the Quest for Geographic Knowledge”. Progress in Human Geography, 42, 600-609
• Miller H.J. and Goodchild, M.F. (2016) “Data-driven Geography”. GeoJournal, 80, 449-461
• Wang, S. (2016) “CyberGIS and Spatial Data Science”. GeoJournal. 81(6), 965-968
• Wang, S. and Goodchild, M.F. (2018) “CyberGIS for Geospatial Innovation and Discovery”. Springer, Dordrecht, Netherlands, DOI: 10.1007/978-94-024-1531-5
• Wright, D. J. and Wang, S. (2011) “The Emergence of Spatial Cyberinfrastructure”. PNAS, 108(14): 5488-5491