Report Open Access
Evidence for the importance of research software
Barker, Michelle;
Katz, Daniel S.;
Gonzalez-Beltran, Alejandra
This blog analyses work evidencing the importance of research software to research outcomes, to enable the research software community to find useful evidence to share with key influencers. This analysis considers papers relating to meta-research, policy, community, education and training, research breakthroughs and specific software.
The Research Software Alliance (ReSA) Taskforce for the importance of research software was formed initially to bring together existing evidence showing the importance of research software in the research process. This kind of information is critical to achieving ReSA’s vision to have research software recognised and valued as a fundamental and vital component of research worldwide.
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Evidence for the importance of research software.pdf
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evidence_for_the_importance_of_research_software.md
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Barone, L., Williams, J., & Micklos, D. (2017). Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators. PLOS Computational Biology, 13(10), e1005755. https://doi.org/10/gcgdcc
Bello, M., & Galindo-Rueda, F. (2020). Charting the digital transformation of science: Findings from the 2018 OECD International Survey of Scientific Authors (ISSA2) (2020/06; OECD Science, Technology and Industry Working Papers). OECD Publishing. https://doi.org/10.1787/c7bdaa03-en
Brookhaven National Laboratory. (2018, August 1). Software framework designed to accelerate drug discovery wins IEEE International Scalable Computing Challenge. https://phys.org/news/2018-08-software-framework-drug-discovery-ieee.html
Browning, S. R., Browning, B. L., Zhou, Y., Tucci, S., & Akey, J. M. (2018). Analysis of Human Sequence Data Reveals Two Pulses of Archaic Denisovan Admixture. Cell, 173(1), 53-61.e9. https://doi.org/10.1016/j.cell.2018.02.031
Duca, D., & Metzler, K. (2019). The Ecosystem of Technologies for Social Science Research [White paper]. Sage. doi: 10.4135/wp191101
European Commission, Directorate-General for Research and Innovation, & PwC EU Services. (2018). Cost-benefit analysis for FAIR research data: Cost of not having FAIR research data. 10.2777/02999
Gallagher, S. (2019, October 15). Researchers find bug in Python script may have affected hundreds of studies. Ars Technica. https://arstechnica.com/information-technology/2019/10/chemists-discover-cross-platform-python-scripts-not-so-cross-platform/
Hettrick, S., Antonioletti, M., Carr, L., Chue Hong, N., Crouch, S., De Roure, D., Emsley, I., Goble, C., Hay, A., Inupakutika, D., Jackson, M., Nenadic, A., Parkinson, T., Parsons, M. I., Pawlik, A., Peru, G., Proeme, A., Robinson, J., & Sufi, S. (2014). UK Research Software Survey 2014 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14809
Houghton, J., & Gruen, N. (2014). Open Research Data report. Report to the Australian National Data Service (ANDS). https://www.ands.org.au/__data/assets/pdf_file/0019/393022/open-research-data-report.pdf
Leng, J., Shoura, M., McLeish, T. C. B., Real, A. N., Hardey, M., McCafferty, J., Ranson, N. A., & Harris, S. A. (2019). Securing the future of research computing in the biosciences. PLOS Computational Biology, 15(5), e1006958. https://doi.org/10.1371/journal.pcbi.1006958
McFadden, C. (2019, March 6). These 7 CERN Spinoffs Show The Project Isn't Just Theoretical. https://interestingengineering.com/these-7-cern-spinoffs-show-the-project-isnt-just-theoretical
McInnes, L. C., Katz, D. S., & Lathrop, S. (2019, December 2). Computational Research Software: Challenges and Community Organizations Working for Culture Change. Siam News. https://sinews.siam.org/Details-Page/computational-research-software-challenges-and-community-organizations-working-for-culture-change
Momcheva, I., & Tollerud, E. (2015). Software Use in Astronomy: An Informal Survey. ArXiv:1507.03989 [Astro-Ph]. http://arxiv.org/abs/1507.03989
Nangia, U., & Katz, D. S. (2017). Understanding Software in Research: Initial Results from Examining Nature and a Call for Collaboration. 2017 IEEE 13th International Conference on E-Science (e-Science), 486–487. https://doi.org/10/ggfkvb
NumFOCUS. (n.d.). Case Study: First Photograph of a Black Hole, Enabled by NumFOCUS Tools. Retrieved May 12, 2020, from https://numfocus.org/case-studies/first-photograph-black-hole
Osimo, D., & Switters, J. (2019). Recognising the importance of software in research: Research Software Engineers (RSEs), a UK example—Study. Directorate-General for Research and Innovation (European Commission). https://op.europa.eu/en/publication-detail/-/publication/fd0f6775-e0dd-11e9-9c4e-01aa75ed71a1
Research Data Alliance. (2020). RDA COVID-19 Guidelines and Recommendations. https://doi.org/10.15497/RDA00046
Rynge, M. (2016, February 11). Pegasus powers LIGO gravitational wave detection analysis – Pegasus WMS. https://pegasus.isi.edu/2016/02/11/pegasus-powers-ligo-gravitational-waves-detection-analysis/
Siepel, A. (2019). Challenges in funding and developing genomic software: Roots and remedies. Genome Biology, 20. https://doi.org/10.1186/s13059-019-1763-7
Sweeny, K., Fridman, M., & Rasmussen, B. (2017). Estimating the value and impact of Nectar Virtual Laboratories. https://nectar.org.au/wp-content/uploads/2016/06/Estimating-the-value-and-impact-of-Nectar-Virtual-Laboratories-2017.pdf
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| Data volume | 28.6 MB | 26.0 MB |
| Unique views | 442 | 389 |
| Unique downloads | 305 | 280 |
- Publication date:
- June 8, 2020
- DOI:
-
- Keyword(s):
- Software Research Education and training Policy Community
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International