Reuse metrics for data and software

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I’ve recently presented a poster about reuse metrics for data and software at the RDA 13th Plenary Meeting. Often reuse of research resources is measured by citation counts. Existing services mostly track the usage of research data / software related DOIs in the reference section of publications, which covers only a fraction of real data / software use cases as data and software citations tend to be quite idiosyncratic.
I would like to share my poster with you as it demonstrates that the general existence of PIDs for data and software is nice and important, but the benefits of PIDs cannot come to their full potential as long as the identifiers are not (yet) broadly used.

van de Sandt, Stephanie. (2019). The Mysterious Case of Research Data Reuse - or a series of unfortunate measurements. Zenodo. http://doi.org/10.5281/zenodo.2621239

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Hi Stephanie, thanks for sharing this! I didn’t get chance to talk to you in Philadelphia but I loved your poster and found it a really compelling way of explaining the difficulties. Does it relate to a specific instance or your experience more generally?

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Hej Jez, thanks a lot for your reply! I am happy that you liked my poster :grinning: I am a doctoral student and the poster teases some fundamentals of my PhD research. I am interested in what happens after research data and software got published, focusing on the “reuse” of research resources. Beside quantifying data and software use, I am trying to improve the tracking of data and software (re)use in publications. To do so, I work with three case studies (High Energy Physics, Life Sciences, Social Sciences) in order to understand discipline specific approaches and to get a general understanding of the differences between “citing” software and data.
The poster reflects my research experience and difficulties to identify (re)use case in publications. Tracking (re)use often feels like a mystery case to me and you certainly have to be Sherlock Holmes to catch them all.

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