Forum Articles on Reproducibility and Replicability Published in the Annals of the American Association of Geographers

To date, reproducibility and replicability (R&R) have received limited attention within geography. Yet there are several reasons for believing that geography presents a distinct context for this discussion. In February 2019, the members of the Spatial Analysis Research Center at Arizona State University organized a workshop on Reproducibility and Replicability in Geospatial Research to explore this topic, its implications for the field, and research practices more broadly. 

Those conversations developed into a series of articles collectively published as a Forum within the Annals of the American Association of Geographers. Links to the collection of articles are included below. We hope that this work stimulates discussion and debate on the issues of reproducibility and replicability from a wide range of perspectives; and provides a foundation for increased attention to R&R in geography programs at all levels.

Goodchild, Fotheringham, Kedron, and Li - Introduction: Forum on Reproducibility and Replicability in Geography (https://doi.org/10.1080/24694452.2020.1806030)

Sui and Kedron - Reproducibility and Replicability in the Context of the Contested Identities of Geography (https://doi.org/10.1080/24694452.2020.1806024)

Wainwright - Is Critical Human Geography Research Replicable? (https://doi.org/10.1080/24694452.2020.1806025)

Nust and Pebesma - Practical Reproducibility in Geography and Geosciences (https://doi.org/10.1080/24694452.2020.1806028)

Wilson, Butler, Gao, Hu, Li and Wright - A Five-Star Guide for Achieving Replicability and Reproducibility When Working with GIS Software and Algorithms (https://doi.org/10.1080/24694452.2020.1806026)

Tullis and Kar - Where Is the Provenance? Ethical Replicability and Reproducibility in GIScience and Its Critical Applications (https://doi.org/10.1080/24694452.2020.1806029)

Waters - Motivations and Methods for Replication in Geography: Working with Data Streams (https://doi.org/10.1080/24694452.2020.1806027)