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Software is vital for the advancement of biology and medicine. Analysis ofusage and impact metrics can help developers determine user and communityengagement, justify additional funding, encourage additional use, identifyunanticipated use cases, and help define improvement areas. However, there arechallenges associated with these analyses including distorted or misleadingmetrics, as well as ethical and security concerns. More attention to thenuances involved in capturing impact across the spectrum of biological softwareis needed. Furthermore, some tools may be especially beneficial to a smallaudience, yet may not have compelling typical usage metrics. We propose moregeneral guidelines, as well as strategies for more specific types of software.We highlight outstanding issues regarding how communities measure or evaluatesoftware impact. To get a deeper understanding of current practices forsoftware evaluations, we performed a survey of participants in the InformaticsTechnology for Cancer Research (ITCR) program funded by the National CancerInstitute (NCI). We also investigated software among this community and othersto assess how often infrastructure that supports such evaluations isimplemented and how this impacts rates of papers describing usage of thesoftware. We find that developers recognize the utility of analyzing softwareusage, but struggle to find the time or funding for such analyses. We also findthat infrastructure such as social media presence, more in-depth documentation,the presence of software health metrics, and clear information on how tocontact developers seem to be associated with increased usage rates. Ourfindings can help scientific software developers make the most out ofevaluations of their software.

Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful?