Spatial Data Science for Impact:
Advances in open source, open science frameworks, methods, applications, and infrastructures for the public good
Open source and open science are characterized by transparency and reproducibility, which together foster cross-university and international as well as interdisciplinary collaboration. This collaboration becomes even more essential during a global pandemic, when the need for reliable, verified, publicly accessible COVID-19 data has never been greater, and given the many social, environmental, and health challenges our world faces. Spatial data science provides a “spatial” perspective to these challenges. How we seek a better model for the development, dissemination and application of spatial data analysis in an open science world is an essential question. In this emerging paradigm, development and research are explicitly linked to open data, modeling, software, collaboration, and publication.
For the AAG 2022 Conference, we invite virtual or in-person contributions from all aspects integrating spatial data within an open source & open science world that push spatial thinking to the mainstream as well as frontiers of GIScience. This session will showcase innovative approaches to cutting-edge open source spatial data infrastructures and applications that are designed to facilitate open science research for a public good. This may include, but not limited to data warehouses, dashboards, platforms, or other repositories that are free and completely open to access and/or collaboration.
Featured talks may cover topics such as:
- open source package development;
- geospatial data or visualization infrastructures;
- frameworks or methodological conceptualization;
- community collaborations and data ownership ideas;
- empirical application with open tools; and more.
This session will be in-person with virtual options. Participants can either submit full presentations (20-minute talk) or submit a lightning session (5-minute talk). Lightning session talks will be added as panelists, meaning participants can still present a full-length talk in another session. Please submit your interest and AAG Pin # by October 18th using this form. Session acceptance will be communicated by November 1st.
This session will be co-organized and sponsored by Marynia Kolak, Julia Koschinksy, Qinyun Lin, Susan Paykin, Dylan Halpern, and Stuart Lynn, Healthy Regions & Policies Lab and Center for Spatial Data Data Science at University of Chicago, and Wei Kang, Inland Center for Sustainable Development at University of California, Riverside.