Category: Data Curation, Open Data, and Research Data Management

The LIBER Quarterly has released a future article: "Research Libraries' New Role in Research Data Management, Current Trends and Visions in Denmark."

Here's an excerpt:

The first part of this paper presents the findings of a research project carried out under the auspices of DEFF. . . .This paper describes the various paths chosen by individual universities and research institutions, and the background for their strategies of research data management. Among the main reasons for the uneven practices are the lack of a national policy in this field, the different scientific traditions and cultures and the differences in the use and organization of IT-services. The second part of this paper presents perspectives of this development that are of particular relevance to research libraries. As they already curate digital collections and are active in establishing web archives,the research libraries become involved in research and dissemination of knowledge in new ways. This paper gives examples of how The State and University Library's services facilitate research data management with special regard to digitization of research objects, storage, preservation and sharing of research data. This paper concludes that the experience and skills of research libraries make the libraries important partners in a research data management infrastructure.

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Lisa R. Johnston has self-archived A Workflow Model for Curating Research Data in the University of Minnesota Libraries: Report from the 2013 Data Curation Pilot.

Here's an excerpt:

The 2013 Data Curation Project set out to test and expand the University Libraries' programmatic and technical capacities to support research data management needs on campus by establishing a fixed-term data curation pilot. This pilot utilized our current suite of services and expertise in the University with the objective of developing a model workflow for curating a variety of types of research data in the Libraries. Specifically, in eight months, this project resulted in 1) a data curation workflow utilizing existing university resources; 2) five pilot research datasets that were solicited, selected, and curated for discovery and reuse in the libraries' digital repository, the University Digital Conservancy, at the persistent URL, http://purl.umn.edu/160292; and 3) and a summary report describing the successes and shortcomings of this approach. This report summarizes the steps taken to curate the datasets in the pilot, faculty needs and reactions to the result, and in addition to the specific dataset treatments, an overall data curation workflow is presented that outlines the steps needed for any dataset. A discussion of this process provides some useful lessons learned. As a result of this project, the University Libraries now hold a more realistic sense of the overall capacities and expertise needed to develop a sustainable data curation service model. Additionally, the Libraries are better prepared to fine-tune and implement selected recommendations from previous assessments and committee reports.

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Beth Plale has published "Synthesis of Working Group and Interest Group Activity One Year into the Research Data Alliance" in D-Lib Magazine.

Here's an excerpt:

The Research Data Alliance (RDA) uses Working Groups and Interest Groups to carry out its work. Groups form when a concerned community develops around a topic for which there are well defined issues, common goals, and an opportunity to create a framework for timely action. One year in, RDA has 26 Working Groups and Interest Groups whose activities are focused on overcoming barriers to successful research data sharing, publishing, referencing and archiving, and on developing the infrastructure necessary to support those tasks.

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Alyssa Goodman et al. have self-archived "10 Simple Rules for the Care and Feeding of Scientific Data" in arXiv.org.

Here's an excerpt:

This article offers a short guide to the steps scientists can take to ensure that their data and associated analyses continue to be of value and to be recognized. In just the past few years, hundreds of scholarly papers and reports have been written on questions of data sharing, data provenance, research reproducibility, licensing, attribution, privacy, and more, but our goal here is not to review that literature. Instead, we present a short guide intended for researchers who want to know why it is important to "care for and feed" data, with some practical advice on how to do that.

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Michael J. Chapple has published "Speaking the Same Language: Building a Data Governance Program for Institutional Impact" in EDUCAUSE Review.

Here's an excerpt:

The need for consistent, reliable data across business and academic units is creating an unprecedented push toward strong data governance practices on college and university campuses. Working together, leaders from the central IT organization, the institutional research division, central administrative offices, and the academy can build a valuable platform to support data-driven decision-making across the institution. The tools used to create this platform will vary from institution to institution, but all should build toward the common goals of creating a data environment that embraces the five pillars of Quality & Consistency, Policies & Standards, Security & Privacy, Compliance, and Retention & Archiving.

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OCLC Research has released Starting the Conversation: University-wide Research Data Management Policy.

Here's an excerpt:

Starting the Conversation: University-wide Research Data Management Policy is a call for action that summarizes the benefits of systemic data management planning and identifies the stakeholders and their concerns. It also suggests that the library director proactively initiate a conversation among these stakeholders to get buy-in for a high-level, responsible data planning and management policy that is proactive, rather than reactive.

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College & Research Libraries has released an e-print of "Where Have All the Scientific Data Gone? LIS Perspective on the Data-At-Risk Predicament."

Here's an excerpt:

Scientists produce vast amounts of data that often are not preserved properly or do not have inventories, placing them at risk. As part of an effort to more fully understand the data-at-risk predicament, researchers engaged in the DARI project at UNC's Metadata Research Center surveyed information custodians working in a range of settings. The survey collected information on the data characteristics and preservation plans. Forty-three information custodians completed the survey. The results indicate that at-risk data include a variety of formats, subject areas, and ownership status, as well as compliance with a variety of standards. Although a majority of respondents agree data preservation is important, they caution that time is the greatest barrier to sharing these data. The study has implications for data rescue and for training information custodians.

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Daniel Goldstein et al. have published "Report on Data Management and Data-Management Plans for the History of Science Society Committee on Research and the Profession (September 6, 2013)" in the History of Science Society Newsletter.

Here's an excerpt:

The growing attention paid to data management by funding agencies reflects two additional trends. First is the idea that agencies that fund research ought to have some say in how that research is disseminated. Second is a growing trend in academia toward the increased sharing and broader dissemination of research data. In addition to these contexts, our report is also informed by the recognition that some historians of science are employing computational methods in their research for which the accumulation of and shared access to data is increasingly central. This report therefore considers what data mean in the context of history of science, when they should and should not be shared, and what mechanisms exist or could be developed for their access and preservation. In the process, the report raises pertinent questions that should be considered and, perhaps, addressed by applicants for NSF grants, but it does not provide a template for grant application plans. This report is intended to serve as a starting point for discussion, to identify issues and suggest possibilities.

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Lisa Federer has published "The Librarian as Research Informationist: A Case Study" in the Journal of the Medical Library Association.

Here's an excerpt:

Whereas traditional library services have generally focused on the "last mile" or finished product of the research process—the peer-reviewed literature—librarians have expertise that can help researchers create better research output in the form of more useful data. In the last several years, new policies from major funding bodies (such as the National Science Foundation's data management plan requirement and the NIH's public access policy) indicate that funders expect researchers to demonstrate the highest possible return on investment for their grant dollars. The need for better research data management has given rise to a new role for librarians: the "research informationist." Research informationists work with research teams at each step of the research process, from project inception and grant seeking to final publication, providing expert guidance on data management and preservation, bibliometric analysis, expert searching, compliance with grant funder policies regarding data management and open access, and other information-related areas.

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Colin L. Bird, Cerys Willoughby, Simon J. Coles, and Jeremy G. Frey have published "Data Curation Issues in the Chemical Sciences" in a special issue of Information Standards Quarterly on data curation.

Here's an excerpt:

In this article, the authors investigate the extent to which chemists respect the importance of curation in their day-to-day activities in the laboratory or, nowadays, frequently at the computer. They emphasize that an essential ingredient in the curation process is metadata, especially for capturing context, which critical for reproducibility. They also consider the potential roles for librarians and information specialists in assisting with scientific curation, both directly and in training scientists. They assert that curation practice will increasingly emphasize the capture of metadata at the time data and information are created, described as curation at source. Innovative and automated methods for curation will be needed to overcome the perceived burden of curation.

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Jenny Delasalle has published "Research Data Management at the University of Warwick: Recent Steps towards a Joined-up Approach at a UK University" in LIBREAS. Library Ideas.

Here's an excerpt:

This paper charts the steps taken and possible ways forward for the University of Warwick in its approach to research data management, providing a typical example of a UK research university's approach in two strands: requirements and support. The UK government approach and funding landscape in relation to research data management provided drivers for the University of Warwick to set requirements and provide support, and examples of good practice at other institutions, support from a central national body (the UK Digital Curation Centre) and learning from other universities' experiences all proved valuable to the University of Warwick. Through interviews with researchers at Warwick, various issues and challenges are revealed: perhaps the biggest immediate challenges for Warwick going forward are overcoming scepticism amongst researchers, overcoming costs, and understanding the implications of involving third party companies in research data management. Building technical infrastructure could sit alongside and beyond those immediate steps and beyond the challenges that face one University are those that affect academia as a whole.

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Martin Hamilton has released "Metadata is a Love Note to the Future—UK Higher Education Research Data Management (RDM) Survey."

Here's an excerpt:

I'm delighted to be able to present here the results of our recent survey of the UK Higher Education community's plans for Research Data Management, along with a little initial analysis and an executive summary. To stay true to the spirit of openness, we have made a redacted version of the raw data available, along with our analysis, using the figshare cloud RDM service.

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SURF has released the European Landscape Study of Research Data Management.

Here's an excerpt:

This report presents the results of an online survey to establish which interventions are already being used by funding agencies, research institutions, national bodies and publishers across the European Union member states and a number of countries outside Europe in order to improve the capacity and skills of researchers in making effective use of research data infrastructures. It also makes recommendations that organisations can adopt to help their researchers. . . .

Interviews with researchers indicate that the main drivers for writing a data management plan are requirements by the funder or the publisher. Nearly half of the research funders who took part in the survey have a policy covering research data management, whilst a quarter of the funders require data management plans as part of the grant application. Data management plans should address data acquisition, use, re-use, storage and protection and the rights of ownership. Just over one third of the responding funding organisations designate a specific organisation for preservation, although no term has been identified.

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Presentations from the Research Data Management Forum 10 are now available.

Here are some representative presentations:

• Keynote 1: "What's so Different about Arts and Humanities Data?"
• Keynote 2: "Err, What Do I Do with This? Exploring Infrastructure Requirements for Visual Arts Researchers"
• Researcher Support and Development Requirements
• Advocacy and Outreach
• A Researcher's View on Arts and Humanities Data Management/Sharing (with a Focus on Infrastructure Needs and Wants)

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The CODATA-ICSTI Task Group on Data Citation Standards and Practices has published "Out of Cite, Out of Mind: The Current State of Practice, Policy, and Technology for the Citation of Data" (edited by Yvonne M. Socha) in the Data Science Journal.

Here's an excerpt:

The use of published digital data, like the use of digitally published literature, depends upon the ability to identify, authenticate, locate, access, and interpret them. Data citations provide necessary support for these functions, as well as other functions such as attribution of credit and establishment of provenance. References to data, however, present challenges not encountered in references to literature. For example, how can one specify a particular subset of data in the absence of familiar conventions such as page numbers or chapters? The traditions and good practices for maintaining the scholarly record by proper references to a work are well established and understood in regard to journal articles and other literature, but attributing credit by bibliographic references to data are not yet so broadly implemented. This report discusses the current state of data citation practices, its supporting infrastructure, a set of guiding principles for implementing data citation, challenges to implementation of good data citation practices, and open research questions

.

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