Archive for the 'Data Curation, Open Data, and Research Data Management' Category

"Peer Review of Datasets: When, Why, and How"

Posted in Data Curation, Open Data, and Research Data Management, Publishing on May 14th, 2014

Matthew S. Mayernik et al. have published "Peer Review of Datasets: When, Why, and How" in the Bulletin of the American Meteorological Society.

Here's an excerpt:

This paper discusses issues related to data peer review, in particular the peer review processes, needs, and challenges related to the following scenarios: 1) Data analyzed in traditional scientific articles, 2) Data articles published in traditional scientific journals, 3) Data submitted to open access data repositories, and 4) Datasets published via articles in data journals.

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    U.S. Open Data Action Plan

    Posted in Data Curation, Open Data, and Research Data Management, Open Access on May 12th, 2014

    The White House has released the U.S. Open Data Action Plan.

    Here's an excerpt:

    The Smithsonian Cooper-Hewitt National Design Museum Collection plans to make all digitized collections metadata public domain, and digitized collection images without copyright or other restriction publicly available at the highest available resolution for non-commercial, educational use. . . .

    The Smithsonian Freer Gallery of Art and Arthur M. Sackler Gallery plans to make all digitized collections metadata public domain, and digitized collection images without copyright or other restriction publicly available at the highest available resolution for non-commercial, educational use. . . .

    After a successful limited release of an API of the Smithsonian American Art Museum collection and hackathon that resulted in a number of working prototypes, the Smithsonian American Art Museum is planning a staged release, from open metadata, like artist or medium, to an open API of digitized collections images without copyright or other restriction available for non- commercial, educational use.

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      Big Data: Seizing Opportunities, Preserving Values

      Posted in Data Curation, Open Data, and Research Data Management, Emerging Technologies on May 6th, 2014

      The Executive Office of the President has released Big Data: Seizing Opportunities, Preserving Values.

      Here's an excerpt:

      On January 17, in a speech at the Justice Department about reforming the United States' signals intelligence practices, President Obama tasked his Counselor John Podesta with leading a comprehensive review of the impact big data technologies are having, and will have, on a range of economic, social, and government activities. Podesta was joined in this effort by Secretary of Commerce Penny Pritzker, Secretary of Energy Ernest Moniz, the President's Science Advisor John Holdren, the President's Economic Advisor Jeffrey Zients, and other senior government officials. The President's Council of Advisors for Science & Technology conducted a parallel report to take measure of the underlying technologies. Their findings underpin many of the technological assertions in this report.

      This review was conceived as fundamentally a scoping exercise. Over 90 days, the review group engaged with academic experts, industry representatives, privacy advocates, civil rights groups, law enforcement agents, and other government agencies. The White House Office of Science and Technology Policy jointly organized three university conferences, at the Massachusetts Institute of Technology, New York University, and the University of California, Berkeley. The White House Office of Science & Technology Policy also issued a "Request for Information" seeking public comment on issues of big data and privacy and received more than 70 responses. In addition, the WhiteHouse.gov platform was used to conduct an unscientific survey of public attitudes about different uses of big data and various big data technologies. A list of the working group's activities can be found in the Appendix.

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        What Drives Academic Data Sharing?

        Posted in Data Curation, Open Data, and Research Data Management on May 2nd, 2014

        RatSWD has released What Drives Academic Data Sharing?.

        Here's an excerpt:

        Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher’s point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration.

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          "Data Publication Consensus and Controversies"

          Posted in Data Curation, Open Data, and Research Data Management, Publishing, Scholarly Journals on April 30th, 2014

          F1000Research has released an eprint of "Data Publication Consensus and Controversies."

          Here's an excerpt:

          As data publication venues proliferate, significant debate continues over formats, processes, and terminology. Here, we present an overview of data publication initiatives underway and the current conversation, highlighting points of consensus and issues still in contention.

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            How to Discover Requirements for Research Data Management Services

            Posted in Data Curation, Open Data, and Research Data Management on April 9th, 2014

            The DCC and DataONE have released How to Discover Requirements for Research Data Management Services.

            Here's an excerpt:

            This guide is meant for people whose role involves developing services or tools to support research data management (RDM) and digital curation, whether in a Higher Education Institution or a project working across institutions. Your RDM development role might be embedded with the research groups concerned, or at a more centralised level, such as a library or computing service. You will need a methodical approach to plan, elicit, analyse, document and prioritise a range of users' requirements.

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              The Value and Impact of Data Sharing and Curation: A Synthesis of Three Recent Studies of UK Research Data Centres

              Posted in Data Curation, Open Data, and Research Data Management, Digital Repositories, Reports and White Papers on April 4th, 2014

              JISC has released The Value and Impact of Data Sharing and Curation: A Synthesis of Three Recent Studies of UK Research Data Centres.

              Here's an excerpt from the announcement:

              The data centre studies combined quantitative and qualitative approaches in order to quantify value in economic terms and present other, non-economic, impacts and benefits. Uniquely, the studies cover both users and depositors of data, and we believe the surveys of depositors undertaken are the first of their kind. All three studies show a similar pattern of findings, with data sharing via the data centres having a large measurable impact on research efficiency and on return on investment in the data and services. These findings are important for funders, both for making the economic case for investment in data curation and sharing and research data infrastructure, and for ensuring the sustainability of such research data centres.

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                "Measuring the Value of Research Data: A Citation Analysis of Oceanographic Data Sets"

                Posted in Data Curation, Open Data, and Research Data Management, Publishing, Scholarly Journals on April 2nd, 2014

                Christopher W. Belter has published "Measuring the Value of Research Data: A Citation Analysis of Oceanographic Data Sets" in PLOS ONE.

                Here's an excerpt:

                Evaluation of scientific research is becoming increasingly reliant on publication-based bibliometric indicators, which may result in the devaluation of other scientific activities—such as data curation—that do not necessarily result in the production of scientific publications. This issue may undermine the movement to openly share and cite data sets in scientific publications because researchers are unlikely to devote the effort necessary to curate their research data if they are unlikely to receive credit for doing so. This analysis attempts to demonstrate the bibliometric impact of properly curated and openly accessible data sets by attempting to generate citation counts for three data sets archived at the National Oceanographic Data Center. My findings suggest that all three data sets are highly cited, with estimated citation counts in most cases higher than 99% of all the journal articles published in Oceanography during the same years. I also find that methods of citing and referring to these data sets in scientific publications are highly inconsistent, despite the fact that a formal citation format is suggested for each data set. These findings have important implications for developing a data citation format, encouraging researchers to properly curate their research data, and evaluating the bibliometric impact of individuals and institutions.

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