Kevin Read

Research data management

Management of research data is a service area of increasing interest to libraries. Librarians have begun to provide a range of services in this area and now teach data management to researchers, work with individual researchers to improve their data management practices, create data management subject guides, and assist in supporting funding agency and publisher data requirements. This paper is a primer on research data management for librarians who have little or no experience in this topic. It includes general background about research data, an overview of what is meant by data management, and suggestions for how to begin to move into this service area.

Sizing the problem of improving discovery and access to NIH-Funded data: A preliminary study

Objective This study informs efforts to improve the discoverability of and access to biomedical datasets by providing a preliminary estimate of the number and type of datasets generated annually by research funded by the U.S. National Institutes of Health (NIH). It focuses on those datasets that are “invisible” or not deposited in a known repository. Methods We analyzed NIH-funded journal articles that were published in 2011, cited in PubMed and deposited in PubMed Central (PMC) to identify those that indicate data were submitted to a known repository. After excluding those articles, we analyzed a random sample of the remaining articles to estimate how many and what types of invisible datasets were used in each article. Results About 12% of the articles explicitly mention deposition of datasets in recognized repositories, leaving 88% that are invisible datasets. Among articles with invisible datasets, we found an average of 2.9 to 3.4 datasets, suggesting there were approximately 200,000 to 235,000 invisible datasets generated from NIH-funded research published in 2011. Approximately 87% of the invisible datasets consist of data newly collected for the research reported; 13% reflect reuse of existing data. More than 50% of the datasets were derived from live human or non-human animal subjects. Conclusion In addition to providing a rough estimate of the total number of datasets produced per year by NIH-funded researchers, this study identifies additional issues that must be addressed to improve the discoverability of and access to biomedical research data: the definition of a “dataset,” determination of which (if any) data are valuable for archiving and preservation, and better methods for estimating the number of datasets of interest. Lack of consensus amongst annotators about the number of datasets in a given article reinforces the need for a principled way of thinking about how to identify and characterize biomedical datasets.

Digging into Digg: genres of online news

A better understanding of the types and forms of communication prevalent in the online news domain will support the design of systems able to retrieve content suited to individual needs. Genre analysis and classification are proposed as methods of studying online news content. We present a research framework for ongoing work in this area.

A new hat for librarians: providing REDCap support to establish the library as a central data hub

Background REDCap, an electronic data capture tool, supports good research data management, but many researchers lack familiarity with the tool. While a REDCap administrator provided technical support and a clinical data management support unit provided study design support, a service gap existed. Case Presentation Librarians with REDCap expertise sought to increase and improve usage through outreach, workshops, and consultations. In collaboration with a REDCap administrator and the director of the clinical data management support unit, the role of the library was established in providing REDCap training and consultations. REDCap trainings were offered to the medical center during the library’s quarterly data series, which served as a springboard for offering tailored REDCap support to researchers and research groups. Conclusions Providing REDCap support has proved to be an effective way to associate the library with data-related activities in an academic medical center and identify new opportunities for offering data services in the library. By offering REDCap services, the library established strong partnerships with the Information Technology Department, Clinical Data Support Department, and Compliance Office by filling in training gaps, while simultaneously referring users back to these departments when additional expertise was required. These new partnerships continue to grow and serve to position the library as a central data hub in the institution.

Data Day to Day: building a community of expertise to address data skills gaps in an academic medical center

Background The New York University Health Sciences Library data services team had developed educational material for research data management and data visualization and had been offering classes at the request of departments, research groups, and training programs, but many members of the medical center were unaware of these library data services. There were also indications of data skills gaps in these subject areas and other data-related topics. Case Presentation The data services team enlisted instructors from across the medical center with data expertise to teach in a series of classes hosted by the library. We hosted eight classes branded as a series called “Data Day to Day.” Seven instructors from four units in the medical center, including the library, taught the classes. A multipronged outreach approach resulted in high turnout. Evaluations indicated that attendees were very satisfied with the instruction, would use the skills learned, and were interested in future classes. Conclusions Data Day to Day met previously unaddressed data skills gaps. Collaborating with outside instructors allowed the library to serve as a hub for a broad range of data instruction and to raise awareness of library services. We plan to offer the series three times in the coming year with an expanding roster of classes.

Practicing what we preach: developing a data sharing policy for the Journal of the Medical Library Association

Providing access to the data underlying research results in published literature allows others to reproduce those results or analyze the data in new ways. Health sciences librarians and information professionals have long been advocates of data sharing. It is time for us to practice what we preach and share the data associated with our published research. This editorial describes the activity of a working group charged with developing a research data sharing policy for the Journal of the Medical Library Association.