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This data landscape project explores where datasets are discoverable, under which conditions, and evaluating the presence and status of open access datasets in the open scholarship infrastructure.. We have gone about this by using OpenAlex, which is a free and open catalog of the world's scholarly research system. Our work also builds upon the Realities of Academic Sharing (RADS) Project Phase 1, which used Crossref and DataCite as a source and was completed before OpenAlex was launched. Since OpenAlex has access to many open access datasets via ORCID, ROR, DOAJ, Unpaywall, Pubmed, Pubmed Central, the ISSN International Centre, Subject-area and institutional repositories from arXiv to Zenodo, this allows us to get a data landscape of the current status of dataset management based on these sources.
We used Python to access OpenAlex’s dataset metadata via its API; we narrowed our scope to datasets published from authors who are affiliated with institutional members of the Data Curation Network (DCN), whose vision it is to advance open research by making data more ethical, reusable, and understandable. Narrowing our scope to datasets affiliated with DCN members, allows us to compare partners who collaborate and use similar dataset submission processes and standards. This way we can see how DCN members' datasets are being presented in the open scholarship landscape. In addition, we can compare how member institutions stack up against each other, and how our own institution, the University of Minnesota, compares to the larger group, and how this may inform our library’s guidelines and policies
