CFP: The Next Steps for Research on R&R in the Cartographic and Geographic Information Sciences

We invite expressions of interest for two or three papers to join a special issue planned for Cartography and Geographic Information Science. Please email Joseph Holler josephh@middlebury.edu or Peter Kedron peter.kedron@asu.edu with an abstract or statement of interest. Please share this email with interested colleagues.

CFP Tentative Title: The Next Steps for Research on R&R in the Cartographic and Geographic Information Sciences Guest Editors: Peter Kedron, Joseph Holler

Synopsis: Reproducibility and replicability are increasingly recognized as essential characteristics of open science and of scientific research publications (NASEM 2019 doi:10.17226/25303, NSF Dear Colleague Letter 23-018). Reproducibility is the ability to repeat a prior study with the same data and produce the same results, offering opportunities to check the internal validity of the study and to enhance the transparency and efficiency of scientific communication and open science. Replicability is the ability to repeat a prior study with new data and confirm the same findings, offering opportunities to verify the external validity and generalizability of the prior findings. Together, reproductions and replications are means by which the scientific community may verify, correct, and improve the claims that science makes about phenomena. Furthermore, reproducibility and replicability can enhance the credibility and reliability of research for informing public policy and building public trust in science. Conversely, the lack of reproducibility is increasingly becoming a barrier between scientific research and public policy actions.

In keeping with geography’s diverse and often debated traditions, attention to R&R has been slower to develop in geography than in other fields (Sui and Kedron, 2021; Kedron and Holler 2021). The heterogeneities and dependencies that characterizes geographic phenomena suggest that the use of R&R to check and extend the claims of prior work may be difficult and may even necessitate the recognition that replication across space and time must be weak (Goodchild and Li, 2021). Furthermore, the results of research in cartography and geographic information science are more heterogeneous than the results of statistical hypothesis tests common in other disciplines, requiring further research on appropriate methods for comparing the results of reproduction and replication studies to prior studies. The volume and complexity of spatial data and computations presents its own challenges for R&R. However, there is reason to believe that these unique challenges to achieving R&R also offer unique opportunities to examine and advance R&R as an epistemological tool for advancing knowledge in cartography and geographic information science.

To that end, we invite research paper presentations that advance reproducibility and/or replicability (R&R) in the cartographic and geographic information sciences. We encourage submissions that develop new R&R related infrastructure, examine a subfield of cartography or GIScience in light of R&R, or introduce R&R-related advances made in other fields into cartography and GIScience. We also encourage new reviews and perspectives that extend past summaries of the current state of the field and offer new insights into where a focus on R&R might take geographic information science. Finally, we encourage the submission of high-quality attempts to reproduce and internally validate important studies, or replication attempts that seek to test existing methods and explanations in new geographic contexts.

Timeline:

• Abstracts: April 30, 2023
• Submission Deadline: July 31, 2023
• Complete peer-review process: January 31, 2024
• Final delivery of manuscripts to Editor-in-Chief: March 31, 2024

We intend to publish manuscripts online as they complete the review process. We expect authors to publish reproducible data and code with their study in an open and FAIR repository. We would also like to make the final manuscripts open-access if possible.