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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Husen DataSciJourn2017 16-1.png|240px]]</div>
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'''"[[Journal:Recommended versus certified repositories: Mind the gap|Recommended versus certified repositories: Mind the gap]]"'''
'''"[[Journal:Open data: Accountability and transparency|Open data: Accountability and transparency]]"'''


Researchers are increasingly required to make research data publicly available in data repositories. Although several organizations propose criteria to recommend and evaluate the quality of data repositories, there is no consensus of what constitutes a good data repository. In this paper, we investigate, first, which data repositories are recommended by various stakeholders (publishers, funders, and community organizations) and second, which repositories are certified by a number of organizations. We then compare these two lists of repositories, and the criteria for recommendation and certification. We find that criteria used by organizations recommending and certifying repositories are similar, although the certification criteria are generally more detailed. We distill the lists of criteria into seven main categories: “Mission,” “Community/Recognition,” “Legal and Contractual Compliance,” “Access/Accessibility,” “Technical Structure/Interface,” “Retrievability,” and “Preservation.” Although the criteria are similar, the lists of repositories that are recommended by the various agencies are very different. Out of all of the recommended repositories, less than six percent obtained certification. As certification is becoming more important, steps should be taken to decrease this gap between recommended and certified repositories, and ensure that certification standards become applicable, and applied, to the repositories which researchers are currently using. ('''[[Journal:Recommended versus certified repositories: Mind the gap|Full article...]]''')<br />
The movements by national governments, funding agencies, universities, and research communities toward “open data” face many difficult challenges. In high-level visions of open data, researchers’ data and metadata practices are expected to be robust and structured. The integration of the internet into scientific institutions amplifies these expectations. When examined critically, however, the data and metadata practices of scholarly researchers often appear incomplete or deficient. The concepts of “accountability” and “transparency” provide insight in understanding these perceived gaps. Researchers’ primary accountabilities are related to meeting the expectations of research competency, not to external standards of data deposition or metadata creation. Likewise, making data open in a transparent way can involve a significant investment of time and resources with no obvious benefits. This paper uses differing notions of accountability and transparency to conceptualize “open data” as the result of ongoing achievements, not one-time acts. ('''[[Journal:Open data: Accountability and transparency|Full article...]]''')<br />
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Revision as of 16:13, 20 December 2017

Fig1 Mayernik BigDataSoc2017 4-2.gif

"Open data: Accountability and transparency"

The movements by national governments, funding agencies, universities, and research communities toward “open data” face many difficult challenges. In high-level visions of open data, researchers’ data and metadata practices are expected to be robust and structured. The integration of the internet into scientific institutions amplifies these expectations. When examined critically, however, the data and metadata practices of scholarly researchers often appear incomplete or deficient. The concepts of “accountability” and “transparency” provide insight in understanding these perceived gaps. Researchers’ primary accountabilities are related to meeting the expectations of research competency, not to external standards of data deposition or metadata creation. Likewise, making data open in a transparent way can involve a significant investment of time and resources with no obvious benefits. This paper uses differing notions of accountability and transparency to conceptualize “open data” as the result of ongoing achievements, not one-time acts. (Full article...)

Recently featured:

Recommended versus certified repositories: Mind the gap
Usability evaluation of laboratory information systems
Data management: New tools, new organization, and new skills in a French research institute