Health sciences librarians' engagement in open science: a scoping review.

OBJECTIVES: To identify the engagement of health sciences librarians (HSLs) in open science (OS) through the delivery of library services, support, and programs for researchers. METHODS: We performed a scoping review guided by Arksey and O'Malley's framework and Joanna Briggs' Manual for Scoping Reviews. Our search methods consisted of searching five bibliographic databases (MEDLINE, Embase, CINAHL, LISTA, and Web of Science Core Collection), reference harvesting, and targeted website and journal searching. To determine study eligibility, we applied predetermined inclusion and exclusion criteria and reached consensus when there was disagreement. We extracted data in duplicate and performed qualitative analysis to map key themes. RESULTS: We included fifty-four studies. Research methods included descriptive or narrative approaches (76%); surveys, questionnaires, and interviews (15%); or mixed methods (9%). We labeled studies with one or more of FOSTER's six OS themes: open access (54%), open data (43%), open science (24%), open education (6%), open source (6%), and citizen science (6%). Key drivers in OS were scientific integrity and transparency, openness as a guiding principle in research, and funder mandates making research publicly accessible. CONCLUSIONS: HSLs play key roles in advancing OS worldwide. Formal studies are needed to assess the impact of HSLs' engagement in OS. HSLs should promote adoption of OS within their research communities and develop strategic plans aligned with institutional partners. HSLs can promote OS by adopting more rigorous and transparent research practices of their own. Future research should examine HSLs' engagement in OS through social justice and equity perspectives.

The Medical Library Association Data Services Competency: a framework for data science and open science skills development.

Increasingly, users of health and biomedical libraries need assistance with challenges they face in working with their own and others' data. Librarians have a unique opportunity to provide valuable support and assistance in data science and open science but may need to add to their expertise and skill set to have the most impact. This article describes the rationale for and development of the Medical Library Association Data Services Competency, which outlines a set of five key skills for data services and provides a course of study for gaining these skills.

Announcing the Journal of the Medical Library Association's data sharing policy.

As librarians are generally advocates of open access and data sharing, it is a bit surprising that peer-reviewed journals in the field of librarianship have been slow to adopt data sharing policies. Starting October 1, 2019, the Journal of the Medical Library Association (JMLA) is taking a step forward and implementing a firm data sharing policy to increase the rigor and reproducibility of published research, enable data reuse, and promote open science. This editorial explains the data sharing policy, describes how compliance with the policy will fit into the journal's workflow, and provides further guidance for preparing for data sharing.

Defining data librarianship: a survey of competencies, skills, and training.

OBJECTIVES: Many librarians are taking on new roles in research data services. However, the emerging field of data librarianship, including specific roles and competencies, has not been clearly established. This study aims to better define data librarianship by exploring the skills and knowledge that data librarians utilize and the training that they need to succeed. METHODS: Librarians who do data-related work were surveyed about their work and educational backgrounds and asked to rate the relevance of a set of data-related skills and knowledge to their work. RESULTS: Respondents considered a broad range of skills and knowledge important to their work, especially "soft skills" and personal characteristics, like communication skills and the ability to develop relationships with researchers. Traditional library skills like cataloging and collection development were considered less important. A cluster analysis of the responses revealed two types of data librarians: data generalists, who tend to provide data services across a variety of fields, and subject specialists, who tend to provide more specialized services to a distinct discipline. DISCUSSION: The findings of this study suggest that data librarians provide a broad range of services to their users and, therefore, need a variety of skills and expertise. Libraries hiring a data librarian may wish to consider whether their communities will be best served by a data generalist or a subject specialist and write their job postings accordingly. These findings also have implications for library schools, which could consider adjusting their curricula to better prepare their students for data librarian roles.

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.

Data literacy training needs of biomedical researchers.

OBJECTIVE: The research investigated topic priorities for data literacy training for biomedical researchers and staff. METHODS: An electronic survey was used to assess researchers' level of knowledge related to data literacy skills and the relevance of these skills to their work. RESULTS: Most respondents did not have any formal training in data literacy. Respondents considered most tasks highly relevant to their work but rated their expertise in tasks lower. CONCLUSION: Among this group, researchers have diverse data literacy training needs. Librarians' expertise makes them well suited to provide such training.

Explaining persistent under-use of colonoscopic cancer screening in African Americans: a systematic review.

INTRODUCTION: Although African Americans have the highest incidence and mortality from colorectal cancer (CRC), they are less likely than other racial groups to undergo CRC screening. Previous research has identified barriers to CRC screening among African Americans. However we lack a systematic review that synthesizes contributing factors and informs interventions to address persistent disparities. METHODS: We conducted a systematic review to evaluate barriers to colonoscopic CRC screening in African Americans. We developed a conceptual model to summarize the patient-, provider-, and system-level barriers and suggest strategies to address these barriers. RESULTS: Nineteen studies met inclusion criteria. Patient barriers to colonoscopy included fear, poor knowledge of CRC risk, and low perceived benefit of colonoscopy. Provider-level factors included failure to recommend screening and knowledge deficits about guidelines and barriers to screening. System barriers included financial obstacles, lack of insurance and access to care, and intermittent primary care visits. CONCLUSIONS: There are modifiable barriers to colonoscopic CRC screening among African Americans. Future interventions should confront patient fear, patient and physician knowledge about barriers, and access to healthcare services. As the Affordable Care Act aims to improve uptake of preventive services, focused interventions to increase CRC screening in African Americans are essential and timely.

The librarian as research informationist: a case study.

QUESTION: How can an embedded research informationist add value to the scientific output of research teams? SETTING: The University of California-Los Angeles (UCLA) Louise M. Darling Biomedical Library is an academic health sciences library serving the clinical, educational, and research needs of the UCLA community. METHODS: A grant from the National Library of Medicine funded a librarian to join a UCLA research team as an informationist. The informationist meets regularly with the research team and provides guidance related to data management, preservation, and other information-related issues. MAIN RESULTS: Early results suggest that the informationist's involvement has influenced the team's data gathering, storage, and curation methods. The UCLA Library has also changed the librarian's title to research informationist to reflect the new activities that she performs. CONCLUSION: The research informationist role provides an opportunity for librarians to become effective members of research teams and improve research output.

Data Science Curriculum in the iField.

Many disciplines, including the broad Field of Information (iField), have been offering Data Science (DS) programs. There have been significant efforts exploring an individual discipline's identity and unique contributions to the broader DS education landscape. To advance DS education in the iField, the iSchool Data Science Curriculum Committee (iDSCC) was formed and charged with building and recommending a DS education framework for iSchools. This paper reports on the research process and findings of a series of studies to address important questions: What is the iField identity in the multidisciplinary DS education landscape? What is the status of DS education in iField schools? What knowledge and skills should be included in the core curriculum for iField DS education? What are the jobs available for DS graduates from the iField? What are the differences between graduate-level and undergraduate-level DS education? Answers to these questions will not only distinguish an iField approach to DS education but also define critical components of DS curriculum. The results will inform individual DS programs in the iField to develop curriculum to support undergraduate and graduate DS education in their local context.

Long-term availability of data associated with articles in PLOS ONE.

The adoption of journal policies requiring authors to include a Data Availability Statement has helped to increase the availability of research data associated with research articles. However, having a Data Availability Statement is not a guarantee that readers will be able to locate the data; even if provided with an identifier like a uniform resource locator (URL) or a digital object identifier (DOI), the data may become unavailable due to link rot and content drift. To explore the long-term availability of resources including data, code, and other digital research objects associated with papers, this study extracted 8,503 URLs and DOIs from a corpus of nearly 50,000 Data Availability Statements from papers published in PLOS ONE between 2014 and 2016. These URLs and DOIs were used to attempt to retrieve the data through both automated and manual means. Overall, 80% of the resources could be retrieved automatically, compared to much lower retrieval rates of 10-40% found in previous papers that relied on contacting authors to locate data. Because a URL or DOI might be valid but still not point to the resource, a subset of 350 URLs and 350 DOIs were manually tested, with 78% and 98% of resources, respectively, successfully retrieved. Having a DOI and being shared in a repository were both positively associated with availability. Although resources associated with older papers were slightly less likely to be available, this difference was not statistically significant, suggesting that URLs and DOIs may be an effective means for accessing data over time. These findings point to the value of including URLs and DOIs in Data Availability Statements to ensure access to data on a long-term basis.

An open toolkit for tracking open science partnership implementation and impact.

Serious concerns about the way research is organized collectively are increasingly being raised. They include the escalating costs of research and lower research productivity, low public trust in researchers to report the truth, lack of diversity, poor community engagement, ethical concerns over research practices, and irreproducibility. Open science (OS) collaborations comprise of a set of practices including open access publication, open data sharing and the absence of restrictive intellectual property rights with which institutions, firms, governments and communities are experimenting in order to overcome these concerns. We gathered two groups of international representatives from a large variety of stakeholders to construct a toolkit to guide and facilitate data collection about OS and non-OS collaborations. Ultimately, the toolkit will be used to assess and study the impact of OS collaborations on research and innovation. The toolkit contains the following four elements: 1) an annual report form of quantitative data to be completed by OS partnership administrators; 2) a series of semi-structured interview guides of stakeholders; 3) a survey form of participants in OS collaborations; and 4) a set of other quantitative measures best collected by other organizations, such as research foundations and governmental or intergovernmental agencies. We opened our toolkit to community comment and input. We present the resulting toolkit for use by government and philanthropic grantors, institutions, researchers and community organizations with the aim of measuring the implementation and impact of OS partnership across these organizations. We invite these and other stakeholders to not only measure, but to share the resulting data so that social scientists and policy makers can analyse the data across projects.

Data sharing in PLOS ONE: An analysis of Data Availability Statements.

A number of publishers and funders, including PLOS, have recently adopted policies requiring researchers to share the data underlying their results and publications. Such policies help increase the reproducibility of the published literature, as well as make a larger body of data available for reuse and re-analysis. In this study, we evaluate the extent to which authors have complied with this policy by analyzing Data Availability Statements from 47,593 papers published in PLOS ONE between March 2014 (when the policy went into effect) and May 2016. Our analysis shows that compliance with the policy has increased, with a significant decline over time in papers that did not include a Data Availability Statement. However, only about 20% of statements indicate that data are deposited in a repository, which the PLOS policy states is the preferred method. More commonly, authors state that their data are in the paper itself or in the supplemental information, though it is unclear whether these data meet the level of sharing required in the PLOS policy. These findings suggest that additional review of Data Availability Statements or more stringent policies may be needed to increase data sharing.

Closing gaps between open software and public data in a hackathon setting: User-centered software prototyping.

In genomics, bioinformatics and other areas of data science, gaps exist between extant public datasets and the open-source software tools built by the community to analyze similar data types.  The purpose of biological data science hackathons is to assemble groups of genomics or bioinformatics professionals and software developers to rapidly prototype software to address these gaps.  The only two rules for the NCBI-assisted hackathons run so far are that 1) data either must be housed in public data repositories or be deposited to such repositories shortly after the hackathon's conclusion, and 2) all software comprising the final pipeline must be open-source or open-use.  Proposed topics, as well as suggested tools and approaches, are distributed to participants at the beginning of each hackathon and refined during the event.  Software, scripts, and pipelines are developed and published on GitHub, a web service providing publicly available, free-usage tiers for collaborative software development. The code resulting from each hackathon is published at https://github.com/NCBI-Hackathons/ with separate directories or repositories for each team.

Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff.

BACKGROUND: Significant efforts are underway within the biomedical research community to encourage sharing and reuse of research data in order to enhance research reproducibility and enable scientific discovery. While some technological challenges do exist, many of the barriers to sharing and reuse are social in nature, arising from researchers' concerns about and attitudes toward sharing their data. In addition, clinical and basic science researchers face their own unique sets of challenges to sharing data within their communities. This study investigates these differences in experiences with and perceptions about sharing data, as well as barriers to sharing among clinical and basic science researchers. METHODS: Clinical and basic science researchers in the Intramural Research Program at the National Institutes of Health were surveyed about their attitudes toward and experiences with sharing and reusing research data. Of 190 respondents to the survey, the 135 respondents who identified themselves as clinical or basic science researchers were included in this analysis. Odds ratio and Fisher's exact tests were the primary methods to examine potential relationships between variables. Worst-case scenario sensitivity tests were conducted when necessary. RESULTS AND DISCUSSION: While most respondents considered data sharing and reuse important to their work, they generally rated their expertise as low. Sharing data directly with other researchers was common, but most respondents did not have experience with uploading data to a repository. A number of significant differences exist between the attitudes and practices of clinical and basic science researchers, including their motivations for sharing, their reasons for not sharing, and the amount of work required to prepare their data. CONCLUSIONS: Even within the scope of biomedical research, addressing the unique concerns of diverse research communities is important to encouraging researchers to share and reuse data. Efforts at promoting data sharing and reuse should be aimed at solving not only technological problems, but also addressing researchers' concerns about sharing their data. Given the varied practices of individual researchers and research communities, standardizing data practices like data citation and repository upload could make sharing and reuse easier.