Measuring the Impacts of Curatorial Actions
Despite the potential for innovation and advancement that data sharing holds, we don’t yet know how to prioritize datasets for professional preparation and archiving. It’s likely that some datasets hold more downstream potential than others, and data sharing policies should prioritize high-value data over others instead of being one-size-fits-all. This project will help us understand the relative impacts of features of datasets (e.g., questions asked, populations included, topics covered) and curatorial actions (e.g., variable standardization, documentation improvements) on data reuse (e.g., citations, downloads). It will produce metrics to explain the return on various types of resource investment—e.g., what kinds of curatorial action increase data reuse and by what margin?
Funding Source: National Science Foundation and the Institute for Museum and Library Services
Social Science Domains