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11- Institutional Perspective on Credit Systems for Research Data
Pages 77-80

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From page 77...
... Simply put, it is because academic research institutions depend on reliable records of scholarly accomplishments for key decisions about hiring, promotion, and tenure. These mechanisms evolved over decades for books, peer-reviewed publications, and sometimes grey literature (e.g., theses, technical reports and working papers, conference proceedings, and similar kinds of information that are not peer-reviewed)
From page 78...
... For example, this is a quote from the NSF Administration Guide: "Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing."2 Also, university copyright policies are evolving.
From page 79...
... From an institutional perspective, some of the requirements for data citation include: ` Persistent or discoverable location ` Works even if the data moves or there are multiple copies ` Verifiable content ` Authenticity ( i.e., "I am looking at what was cited, unchanged") ` Requires discovery and provenance metadata ` Standardized ` Data identifiers: DataCite, DOIs ` People identifiers: ORCID registry ` Institutional identifiers: OCLC?
From page 80...
... We have to involve experts whose job is to worry about quality control and metadata production, and that is also very expensive. So, we have to keep in mind these issues and requirements when we think about data citation techniques.


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