Spatial Data Science for Impact 2
Type: Virtual Paper
Day: 2/28/2022
Start Time: 9:40 AM
End Time: 11:00 AM
Theme:
Sponsor Group(s):
Digital Geographies Specialty Group
, Health and Medical Geography Specialty Group
, Spatial Analysis and Modeling Specialty Group
,
,
,
,
,
,
Organizer(s):
Dylan Halpern
, Julia Koschinsky
,
,
Chairs(s):
Stuart Lynn, University of Chicago
; ,
Description:
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.
Presentation(s), if applicable
Marynia Kolak, University of Illinois Urbana-Champaign; Breathing Life Into Environmental Data with Harmonized, Interactive, FOSS Applications |
Kevin Credit, ; The built environment-mode choice nexus: A method for making international comparisons using open spatial data |
Qinyun Lin, University of Chicago; Mapping historical and ongoing spatial inequities in access to medications for opioid use disorder |
Connor Donegan, University of Texas - Dallas; The geostan R package for Bayesian spatial analysis: strategies for modeling and measuring health inequalities |
Susan Paykin, University of Chicago; Open-source data and infrastructure for exploring the risk environment impacting opioid use in justice communities |
Non-Presenting Participants Agenda
| Role | Participant |
|
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
Spatial Data Science for Impact 2
Description
Virtual Paper
Contact the Primary Organizer
Marynia Kolak - mkolak@illinois.edu
Session Sponsored By