Mapping the Research Software Ecosystem

CZI workshop, December 9th, 2020, 11:30am

🖼️ Slides: https://inundata.org/talks/eoss-software-map/
📑 PDF copy of slides

Questions and notes

📝 Google doc with questions and notes. Please add your name next to your comment.

Discussion Questions

• Q1. Which packages are increasingly used together in scientific workflows? (direct link to notes)

  • How might the map assist with how you know and interact with your project’s upstream and downstream dependencies?
  • Can funding help make software more compatible?

• Q2. What groups of interdependent software are increasingly important for scientific fields? (direct link to notes)

  • How visible is their importance? Can directed funding ensure the stability and maturity of critical dependencies and tool networks?
  • Does indirect usage do the work needed to demonstrate impact (with funders, with evaluators?)

• Q3. Which software components are seeing use outside their areas of original development? (direct link to notes)

  • Can funded interventions shore up interdisciplinary opportunities?
  • Are there “leading” and “lagging” fields?
  • Can funded interventions bring lessons in achieving change within fields?

• Q4. How can we assess the weaknesses and opportunities in the ecosystem? (direct link to notes)

  • Can project health data (like the CHAOSS project) be integrated to highlight strengths and weaknesses?

• Q5. Can visibility of interdependencies motivate Industry to provide pro-bono support to those building software crucial to science? (direct link to notes)

• Q6. What else do you want to do at an ecosystem level that this wouldn’t help with? (direct link to notes)

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Got additional questions after the workshop? Email us at karthik.ram@berkeley.edu and jhowison@ischool.utexas.edu

Recommended reading

At risk of leaving out significant work in this area here are some links to relevant work!

• CHAOSS project

• Depsy. Piwowar, H. A., & Priem, J. (2016). Depsy: Valuing the software that powers science. See Singh Chawla, D. (2016). The unsung heroes of scientific software. Nature News, 529(7584), 115. https://doi.org/10.1038/529115a

• https://libraries.io/experiments

• Bogart, C., Howison, J., & Herbsleb, J. D. (2015). Mapping the Network of Scientific Software. http://james.howison.name/pubs/BogartetAl_ScientificNetworkMapPreprint.pdf

• McConahy, A., Eisenbraun, B., Howison, J., Herbsleb, J. D., & Sliz, P. (2012). Techniques for Monitoring Runtime Architectures of Socio-technical Ecosystems. Workshop on Data-Intensive Collaboration in Science and Engineering (CSCW 2012). http://james.howison.name/pubs/Mcconahy-et-al.pdf

• Nagle, Frank, Jessica Wilkerson, James Dana, and Jennifer L. Hoffman. "Vulnerabilities in the Core: Preliminary Report and Census II of Open Source Software." White Paper, February 2020. https://www.coreinfrastructure.org/programs/census-program-ii/

• Pan, X., Yan, E., & Hua, W. (2016). Disciplinary differences of software use and impact in scientific literature. Scientometrics, 1–18. https://doi.org/10.1007/s11192-016-2138-4

• Kruger, F., & Schindler, D. (2020). A Literature Review on Methods for the Extraction of Usage Statements of Software and Data. Computing in Science & Engineering, 22(1), 26–38. https://doi.org/10.1109/MCSE.2019.2943847

• Ma, Y., Bogart, C., Amreen, S., Zaretzki, R., & Mockus, A. (2019). World of Code: An Infrastructure for Mining the Universe of Open Source VCS Data. 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR), 143–154. https://doi.org/10.1109/MSR.2019.00031

• Katz, D. S. (2014). Transitive Credit as a Means to Address Social and Technological Concerns Stemming from Citation and Attribution of Digital Products. Journal of Open Research Software, 2(1), e20. https://doi.org/10.5334/jors.be

• Allen, A., Teuben, P. J., & Ryan, P. W. (2018). Schroedinger’s Code: A Preliminary Study on Research Source Code Availability and Link Persistence in Astrophysics. The Astrophysical Journal Supplement Series, 236(1), 10. https://doi.org/10.3847/1538-4365/aab764

• Nadia Eghbal. (2016). Roads and Bridges: The Unseen Labor Behind Our Digital Infrastructure. Ford Foundation. https://www.fordfoundation.org/work/learning/research-reports/roads-and-bridges-the-unseen-labor-behind-our-digital-infrastructure/