Accelerating Cloud-Native Adoption through Community Building, User Engagement and Upskilling

The key to expanding the adoption of cloud-native geospatial technologies lies in effective community building, user engagement and upskilling. This keynote presents lessons from three approaches to fostering cloud-native adoption: building a community of practice around Earth Engine at Yale University, engaging Sentinel data users through the EOPF Toolkit's open resources and notebook competition, and delivering tailored, role-specific training through thriveGEO. Drawing on these experiences, the talk summarises effective strategies that work across different scales, from institutional communities to global user bases.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-01
DOI
https://doi.org/10.5281/zenodo.19555232
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
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article

Accelerating Cloud-Native Adoption through Community Building, User Engagement and Upskilling

Sabrina H. Szeto
Zenodo (CERN European Organization for Nuclear Research)
Geographic Information Systems Studies
article

Accelerating Cloud-Native Adoption through Community Building, User Engagement and Upskilling

Sabrina H. Szeto
article en

Abstract

The key to expanding the adoption of cloud-native geospatial technologies lies in effective community building, user engagement and upskilling. This keynote presents lessons from three approaches to fostering cloud-native adoption: building a community of practice around Earth Engine at Yale University, engaging Sentinel data users through the EOPF Toolkit's open resources and notebook competition, and delivering tailored, role-specific training through thriveGEO. Drawing on these experiences, the talk summarises effective strategies that work across different scales, from institutional communities to global user bases.

Zenodo (CERN European Organization for Nuclear Research)
Thrive (US)
Openalex Percentile: Top 12%
Geographic Information Systems Studies
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