Best practices to evaluate the impact of biomedical research software-metric collection beyond citations

dc.contributor.authorAfiaz, Awan
dc.contributor.authorIvanov, Andrey A.
dc.contributor.authorChamberlin, John
dc.contributor.authorHanauer, David
dc.contributor.authorSavonen, Candace L.
dc.contributor.authorGoldman, Mary J.
dc.contributor.authorMorgan, Martin
dc.contributor.authorReich, Michael
dc.contributor.authorGetka, Alexander
dc.contributor.authorHolmes, Aaron
dc.contributor.authorPati, Sarthak
dc.contributor.authorKnight, Dan
dc.contributor.authorBoutros, Paul C.
dc.contributor.authorBakas, Spyridon
dc.contributor.authorCaporaso, J. Gregory
dc.contributor.authorDel Fiol, Guilherme
dc.contributor.authorHochheiser, Harry
dc.contributor.authorHaas, Brian
dc.contributor.authorSchloss, Patrick D.
dc.contributor.authorEddy, James A.
dc.contributor.authorAlbrecht, Jake
dc.contributor.authorFedorov, Andrey
dc.contributor.authorWaldron, Levi
dc.contributor.authorHoffman, Ava M.
dc.contributor.authorBradshaw, Richard L.
dc.contributor.authorLeek, Jeffrey T.
dc.contributor.authorWright, Carrie
dc.contributor.departmentPathology and Laboratory Medicine, School of Medicine
dc.date.accessioned2024-10-09T09:30:31Z
dc.date.available2024-10-09T09:30:31Z
dc.date.issued2024
dc.description.abstractMotivation: Software is vital for the advancement of biology and medicine. Impact evaluations of scientific software have primarily emphasized traditional citation metrics of associated papers, despite these metrics inadequately capturing the dynamic picture of impact and despite challenges with improper citation. Results: To understand how software developers evaluate their tools, we conducted a survey of participants in the Informatics Technology for Cancer Research (ITCR) program funded by the National Cancer Institute (NCI). We found that although developers realize the value of more extensive metric collection, they find a lack of funding and time hindering. We also investigated software among this community for how often infrastructure that supports more nontraditional metrics were implemented and how this impacted rates of papers describing usage of the software. We found that infrastructure such as social media presence, more in-depth documentation, the presence of software health metrics, and clear information on how to contact developers seemed to be associated with increased mention rates. Analysing more diverse metrics can enable developers to better understand user engagement, justify continued funding, identify novel use cases, pinpoint improvement areas, and ultimately amplify their software's impact. Challenges are associated, including distorted or misleading metrics, as well as ethical and security concerns. More attention to nuances involved in capturing impact across the spectrum of biomedical software is needed. For funders and developers, we outline guidance based on experience from our community. By considering how we evaluate software, we can empower developers to create tools that more effectively accelerate biological and medical research progress. Availability and implementation: More information about the analysis, as well as access to data and code is available at https://github.com/fhdsl/ITCR_Metrics_manuscript_website.
dc.eprint.versionFinal published version
dc.identifier.citationAfiaz A, Ivanov AA, Chamberlin J, et al. Best practices to evaluate the impact of biomedical research software-metric collection beyond citations. Bioinformatics. 2024;40(8):btae469. doi:10.1093/bioinformatics/btae469
dc.identifier.urihttps://hdl.handle.net/1805/43830
dc.language.isoen_US
dc.publisherOxford University Press
dc.relation.isversionof10.1093/bioinformatics/btae469
dc.relation.journalBioinformatics
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePMC
dc.subjectBiomedical research
dc.subjectComputational biology
dc.subjectSoftware
dc.titleBest practices to evaluate the impact of biomedical research software-metric collection beyond citations
dc.typeArticle
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