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Data Papers are Witness to Trusted Resources in Grey Literature: Driving Access to Data thru Public Awareness

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Data Papers are Witness to Trusted Resources in Grey Literature: Driving Access to Data thru Public Awareness
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14
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CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Abstract
In 2011, GreyNet embarked on an Enhanced Publications Project with DANS, Data Archiving and Networked Services in an effort to circumvent the data versus document camps entrenched in grey literature communities. The results of that two year project served to incorporate in GreyNet’s workflow the acquisition, indexing, and linking of research data with their full-text and accompanying metadata. Recently, GreyNet discussed with a data management librarian from UFL, University of Florida a proposed follow-up project dealing with data papers – a new document type within grey literature. Data papers are defined as scholarly publications of a searchable metadata document describing a particular online accessible dataset or a group of datasets published in accordance to standard academic practices. As such, data papers represent a scholarly communication approach to data sharing. The outcome of that discussion has led to the formation of a project team with the twofold purpose of producing and publishing a set of data papers originating in the field of grey literature, and in so doing raise awareness to this new document type by demonstrating its value for library and information science. The method of approach includes the construction of an online standardized template that encompasses a data paper, defining the population asked to complete the template, instruction and further contact with the authors/researchers during the course of the project, along with an analysis of the results. While there are no direct costs associated with this project, each of the partners is committed to allocate human and material resources needed to carry out their related tasks. The anticipated outcome of the project would provide a tested template that could be used by other grey literature communities in the production of data papers. It would demonstrate how OA, DSA and FAIR principles are implemented and reinforced via data papers. And, it would further provide examples of how data citations can generate trusted bibliographic references.