As the largest journal in the world, PLOS ONE publishes an incredible amount of data alongside its research articles, yet the article itself remains the gold standard for attributing credit. While data is the fundamental unit of research, it isn’t recognized as an important component of a researcher’s scholarly output. How can we change this?
At present, sharing data can be onerous work, but Data-Level Metrics (DLMs) can equip researchers with concrete evidence of the value of their efforts. PLOS, in partnership with UC3 and DataONE, has undertaken a project called Make Data Count to develop DLMs. This 12-month NSF-funded project is aimed at piloting a suite of metrics that track and measure data use so that it can be shared to funders, tenure & promotion committees, etc.
But first, we need to better understand the needs of researchers across disciplines and communities—how might you get credit for the data you produce? what do you want to know about how your data is used? Please take this 5-10 minute survey and help us craft data-level metrics: surveymonkey.com/s/makedatacount. Feel free to share widely!
We are excited to engage the PLOS ONE community in designing a new system of crediting scholarly work on data. Please contact Jennifer Lin (email@example.com) for more information or to share your feedback directly.