Abstract

AI workflows in geospatial data science offer significant societal benefits but raise ethical, transparency, and reproducibility challenges. Current ethical frameworks and tools are often hard to integrate into daily research practice. This paper introduces the I-GUIDE Data Ethics Toolkit (DET), a lightweight suite designed for users of the NSF-funded Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE). Based on a longitudinal mixed-methods study, including surveys, interviews, and observations, we identified five design priorities: usability, anticipatory planning, distributed responsibility, comprehensive coverage, and policy compliance. We integrated existing AI and data research lifecycles into an eight-stage I-GUIDE Research Lifecycle, serving as the DET’s foundation. The DET includes four tools: (1) Data Cards and (2) Model Cards to document provenance, bias, and usage constraints; (3) a Research Product Management Plan for project-level governance; and (4) MEG-AID, a checklist to manage and audit ethical and reproducibility tasks. Future work will embed DET into the I-GUIDE cyberinfrastructure, automating metadata extraction, bias diagnostics, and training modules to ensure responsible geospatial AI research practices.

Keywords

AI toolkit, data card, data ethics, geospatial data science, GIS model card, responsible AI

Document Type

Paper

Start Date

19-6-2025 10:50 AM

End Date

19-6-2025 11:50 AM

DOI

10.5703/1288284318496

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Jun 19th, 10:50 AM Jun 19th, 11:50 AM

Mapping Responsible Workflows for Geospatial Data Science: Developing the I-GUIDE Data Ethics Toolkit

AI workflows in geospatial data science offer significant societal benefits but raise ethical, transparency, and reproducibility challenges. Current ethical frameworks and tools are often hard to integrate into daily research practice. This paper introduces the I-GUIDE Data Ethics Toolkit (DET), a lightweight suite designed for users of the NSF-funded Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE). Based on a longitudinal mixed-methods study, including surveys, interviews, and observations, we identified five design priorities: usability, anticipatory planning, distributed responsibility, comprehensive coverage, and policy compliance. We integrated existing AI and data research lifecycles into an eight-stage I-GUIDE Research Lifecycle, serving as the DET’s foundation. The DET includes four tools: (1) Data Cards and (2) Model Cards to document provenance, bias, and usage constraints; (3) a Research Product Management Plan for project-level governance; and (4) MEG-AID, a checklist to manage and audit ethical and reproducibility tasks. Future work will embed DET into the I-GUIDE cyberinfrastructure, automating metadata extraction, bias diagnostics, and training modules to ensure responsible geospatial AI research practices.