Forking Awesome: Adventures in Highly Reproducible Geospatial Analytics and Shareable Findings
Topics: Digital Geographies
, Cartography
, Temporal GIS
Keywords: interactive, web cartography, spatial data science, reproducibility
Session Type: Virtual Paper Abstract
Day: Monday
Session Start / End Time: 2/28/2022 08:00 AM (Eastern Time (US & Canada)) - 2/28/2022 09:20 AM (Eastern Time (US & Canada))
Room: Virtual 34
Authors:
Dylan Halpern, University of Chicago
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Abstract
Interactive and exploratory geospatial data dashboards are more essential than ever: understanding mobility data is critical to uncovering gaps in access, socio-economic data at varying scales is prolific (and sometimes troublesome), and COVID-19 remains a global and inherently spatial challenge. Without a doubt, today’s context won’t be the last time we need geospatial tools and thinking to understand and analyze problems facing the world. Considering how open source tools, projects, and platforms can be reproduced, replicable, and extended is critical for future challenges. Through the learnings of the US Covid Atlas project, a free and open source browser-based multi-year archive of the pandemic in the US, this talk will explore the affordances and limitations of different infrastructures, frameworks, programming ecosystems, and strategies as they relate to making a reproducible interactive geospatial web application. On the user-facing end, this talk will touch on the importance of sharing findings in an exploratory data application and techniques for capturing data views or application state. By the end of this talk, participants will have an understanding of various strategies for how to build reproducible geospatial data science projects, key emerging and established technologies, and considerations for how to enable shareable features for easier communication of findings.
Forking Awesome: Adventures in Highly Reproducible Geospatial Analytics and Shareable Findings
Category
Virtual Paper Abstract
Description
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