Mapping the Research Software Ecosystem
CZI workshop, December 9th, 2020, 11:30am
Questions and notes
📝 Google doc with questions and notes. Please add your name next to your comment.
Discussion Questions
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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?
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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?)
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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?
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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?
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Q5. Can visibility of interdependencies motivate Industry to provide pro-bono support to those building software crucial to science? (direct link to notes)
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Q6. What else do you want to do at an ecosystem level that this wouldn’t help with? (direct link to notes)
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!
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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
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Bogart, C., Howison, J., & Herbsleb, J. D. (2015). Mapping the Network of Scientific Software. http://james.howison.name/pubs/BogartetAl_ScientificNetworkMapPreprint.pdf
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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
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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/
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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
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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
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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
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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
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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
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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/