Open Source GIScience

Joseph Holler's Open Source GIScience Resources at Middlebury College

Open CyberGIS Community

Oct-26 : In this lesson, we will envision a CyberGIS community practicing open science.

Reading

  1. Wang, S. (2019). Cyberinfrastructure. The Geographic Information Science & Technology Body of Knowledge (2nd Quarter 2019 Edition), John P. Wilson (Ed.). DOI:10.22224/gistbok/2019.2.4.

Lecture and Notes

  1. Kedron, Peter and Joseph Holler, 2021-08-23, Geospatial Fellows Webinar Series: Working with students to reproduce COVID-19 research to establish the credibility of findings and accelerate policymaker adoption

Reflecting

Please prepare a short blog post for your site from the perspective of an undergraduate student learning spatial analysis with reproducible research notebooks in a CyberGIS environment, e.g. CyberGISX Draw on specific examples from the Kang et al (2020) accessibility study and its associated research compendium and computational notebooks. Does the reproduction study with a research compendium in CyberGIS facilitate learning spatial analysis? How? Are there ways in which the research compendium could be improved to better facilitate learning? How?

References

  1. Ibanez, L., W. J. Schroeder, and M. D. Hanwell. 2014. Practicing open science. In Implementing Reproducible Research, eds. V. Stodden, F. Leisch, and R. D. Peng, 241–280. Boca Raton: CRC Press.
  2. Millman, K. J., and F. Perez. 2014. Developing Open-Source Scientific Practice. In Implementing Reproducible Research, eds. V. Stodden, F. Leisch, and R. D. Peng, 149–183. Boca Raton: CRC Press.
  3. Nüst, D., C. Boettiger, and B. Marwick. 2018. How to Read a Research Compendium. arXiv:1806.09525.
  4. Wilson, J. P., K. Butler, S. Gao, Y. Hu, W. Li, and D. J. Wright. 2021. A Five-Star Guide for Achieving Replicability and Reproducibility When Working with GIS Software and Algorithms. Annals of the American Association of Geographers 111 (5):1311–1317. DOI:10.1080/24694452.2020.1806026.

Big Code

Serge Rey gave a great talk at the 2020 AAG Annual Meeting on Big Code in which he referenced the importance of code as text, discussed issues of inclusivity and algorithmic bias in spatial analysis at length, and considered the potential for open source spatial analysis code to become a means for co-production of algorithmic knowledge with communities that have historically been excluded from the field (a very white male crowd).

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