NIH to Host Informational Webinar on the Draft NIH Policy for Data Management and Sharing and Supplemental Draft Guidance

“NIH will be hosting an informational public webinar on the Draft NIH Policy for Data Management and Sharing and supplemental draft guidance on Monday, December 16, 2019 from 12:30 p.m. to 2:00 p.m. ET. The purpose of this webinar is to provide information on the draft policy and answer any clarifying questions about the public comment process. Public comments will NOT be accepted via the webinar but must instead be sent through the comment form. Comments on the draft Policy and draft supplemental guidance can be submitted here https://osp.od.nih.gov/draft-data-sharing-and-management/ electronically through Friday, January 10, 2020….”

Data sharing from clinical trials: lessons from the YODA Project – STAT

“This week, the National Academies of Science, Engineering, and Medicine are convening the workshop “Sharing Clinical Trial Data: Challenges and a Way Forward” just shy of five years after the Institute of Medicine released its seminal report, “Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk.”

During this time, the scientific culture regarding data sharing has shifted. Just last week, the National Institutes of Health requested public comments on its draft “Policy for Data Management and Sharing.” In 2018, the International Committee of Medical Journal Editors began requiring data-sharing plans for clinical trials as a condition for publication in member journals. And platforms such as ClinicalStudyDataRequest.com, Project Data Sphere, and BioLINCC have emerged or grown. These platforms use a variety of different governance structures and models for data access, developed both with and without the support of industry or government….

The Yale Open Data Access (YODA) Project, which two of us (J.S.R. and H.M.K.) co-direct, launched in 2011 and formed a partnership with Johnson & Johnson in 2014. This five-year partnership offers an opportunity to reflect on some of the questions about sharing clinical trial data that may inform ongoing and future efforts….”

STRIDES Initiative | Data Science at NIH

“The NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) Initiative allows NIH to explore the use of cloud environments to streamline NIH data use by partnering with commercial providers. NIH’s STRIDES Initiative provides cost-effective access to industry-leading partners to help advance biomedical research. These partnerships enable access to rich datasets and advanced computational infrastructure, tools, and services.

The STRIDES Initiative is one of many NIH-wide efforts to implement the NIH Strategic Plan for Data Science, which provides a roadmap for modernizing the NIH-funded biomedical data science ecosystem.

By leveraging the STRIDES Initiative, NIH and NIH-funded institutions can begin to create a robust, interconnected ecosystem that breaks down silos related to generating, analyzing, and sharing research data….”

Why NIH is beefing up its data sharing rules after 16 years | Science | AAAS

“The U.S. National Institutes of Health last week released a draft policy that will require all investigators with NIH funding to make their data sets available to colleagues. For the first time, grantees holding any NIH-funded grant—not just those above a $500,000 threshold in direct costs—will need to submit a detailed plan for sharing data, including steps to protect the privacy of research subjects….”

NIH Requests Public Comment on a Draft Policy for Data Management and Sharing and Supplemental Draft Guidance | SEA Currents

“Yesterday, NIH released a Draft NIH Policy for Data Management and Sharing and supplemental draft guidance for public comment. The purpose of this draft policy and supplemental draft guidance is to promote effective and efficient data management and sharing that furthers NIH’s commitment to making the results and accomplishments of the research it funds and conducts available to the public. Complete information about the draft Policy and draft supplemental guidance can be found on the NIH OSP website.

Stakeholder feedback is essential to ensure that any future policy maximizes responsible data sharing, minimizes burden on researchers, and protects the privacy of research participants.  Stakeholders are invited to comment on any aspect of the draft policy, the supplemental draft guidance, or any other considerations relevant to NIH’s data management and sharing policy efforts that NIH should consider.

To facilitate commenting, NIH has established a web portal that can be accessed here. To ensure consideration, comments must be received no later than January 10, 2020….”

Potential risks and solutions for sharing genome summary data from African populations | BMC Medical Genomics | Full Text

Abstract:  Genome data from African population can substantially assist the global effort to identify aetiological genetic variants, but open access to aggregated genomic data from these populations poses some significant risks of community- and population- level harms. A recent amendment to National Institutes of Health policy, following various engagements with predominantly North American scientists, requires that genomic summary results must be made available openly on the internet without access oversight or controls.

The policy does recognise that some sensitive, identifiable population groups might be harmed by such exposure of their data, and allows for exemption in these cases. African populations have a very wide and complex genomic landscape, and because of this diversity, individual African populations may be uniquely re-identified by their genomic profiles and genome summary data. Given this identifiability, combined with additional vulnerabilities such as poor access to health care, socioeconomic challenges and the risk of ethnic discrimination, it would be prudent for the National Institutes of Health to recognise the potential of their current policy for community harms to Africans; and to exempt all African populations as sensitive or vulnerable populations with regard to the unregulated exposure of their genome summary data online.

Three risk-mitigating mechanisms for sharing genome summary results from African populations to inform global genomic health research are proposed here; namely use of the Beacon Protocol developed by the Global Alliance for Genomics and Health, user access control through the planned African Genome Variation Database, and regional aggregation of population data to protect individual African populations from re-identification and associated harms.

NIH’s DRAFT Data Management and Sharing Policy: We Need to Hear From You! – Office of Science Policy

“Around this time last year, I wrote about a request for information (RFI) on potential key elements that could comprise a future NIH data management and sharing policy.  Not surprisingly, we received a lot of helpful feedback. Most commenters supported data sharing and the importance of prospectively planning for where, when, and how scientific data should be managed and shared.  There were, however, concerns about how one policy could fit all sizes and types of data across the biomedical research universe as well as potential burden on the research community.

Over the course of the last year, NIH has been incorporating many of these suggestions into our thinking and continuing to engage the community on their thoughts about data management and sharing. We’ve also been working with sovereign Tribal Nations through consultation sessions held across the U.S which have been vital in shaping NIH”s perspective on the potentially unique data sharing needs of those communities.

Today, NIH has released for public comment in the Federal Register a Draft NIH Policy for Data Management and Sharing along with supplement draft guidance. The draft policy furthers NIH longstanding commitment to making available the results and products of the research we fund and conduct.

To facilitate public comments, NIH has established a web-portal where folks can easily and securely provide their feedback.  The portal can be accessed by clicking here. To ensure that your comments are considered, responses must be submitted no later than January 10, 2020….”

The NIH public access policy did not harm biomedical journals

Abstract:  The United States National Institutes of Health (NIH) imposed a public access policy on all publications for which the research was supported by their grants; the policy was drafted in 2004 and took effect in 2008. The policy is now 11 years old, yet no analysis has been presented to assess whether in fact this largest-scale US-based public access policy affected the vitality of the scholarly publishing enterprise, as manifested in changed mortality or natality rates of biomedical journals. We show here that implementation of the NIH policy was associated with slightly elevated mortality rates and mildly depressed natality rates of biomedical journals, but that birth rates so exceeded death rates that numbers of biomedical journals continued to rise, even in the face of the implementation of such a sweeping public access policy.

 

“Assessing Data Management Needs of Bioengineering and Biomedical Faculty” by Christie A. Wiley and Margaret H. Burnette

Abstract:  Objectives: This study explores data management knowledge, attitudes, and practices of bioengineering and biomedical researchers in the context of the National Institutes of Health-funded research projects. Specifically, this study seeks to answer the following questions:

What is the nature of biomedical and bioengineering research on the Illinois campus and what kinds of data are being generated?
To what degree are biomedical and bioengineering researchers aware of best practices for data management and what are the actual data management behaviors?
What aspects of data management present the greatest challenges and frustrations?
To what degree are biomedical and bioengineering researchers aware of data sharing opportunities and data repositories, and what are their attitudes towards data sharing?
To what degree are researchers aware of campus services and support for data management planning, data sharing, and data deposit, and what is the level of interest in instruction in these areas?

 

Methods: Librarians on the University of Illinois at Urbana Champaign campus conducted semi-structured interviews with bioengineering and biomedical researchers to explore researchers’ knowledge of data management best practices, awareness of library campus services, data management behavior and challenges managing research data. The topics covered during the interviews were current research projects, data types, format, description, campus repository usage, data-sharing, awareness of library campus services, data reuse, the anticipated impact of health on public and challenges (interview questions are provided in the Appendix).

Results: This study revealed the majority of researchers explore broad research topics, various file storage solutions, generate numerous amounts of data and adhere to differing discipline-specific practices. Researchers expressed both familiarity and unfamiliarity with DMP Tool. Roughly half of the researchers interviewed reported having documented protocols for file names, file backup, and file storage. Findings also suggest that there is ambiguity about what it means to share research data and confusion about terminology such as “repository” and “data deposit”. Many researchers equate publication to data sharing.

Conclusions: The interviews reveal significant data literacy gaps that present opportunities for library instruction in the areas of file organization, project workflow and documentation, metadata standards, and data deposit options. The interviews also provide invaluable insight into biomedical and bioengineering research in general and contribute to the authors’ understanding of the challenges facing the researchers we strive to support.

“Assessing Data Management Needs of Bioengineering and Biomedical Faculty” by Christie A. Wiley and Margaret H. Burnette

Abstract:  Objectives: This study explores data management knowledge, attitudes, and practices of bioengineering and biomedical researchers in the context of the National Institutes of Health-funded research projects. Specifically, this study seeks to answer the following questions:

What is the nature of biomedical and bioengineering research on the Illinois campus and what kinds of data are being generated?
To what degree are biomedical and bioengineering researchers aware of best practices for data management and what are the actual data management behaviors?
What aspects of data management present the greatest challenges and frustrations?
To what degree are biomedical and bioengineering researchers aware of data sharing opportunities and data repositories, and what are their attitudes towards data sharing?
To what degree are researchers aware of campus services and support for data management planning, data sharing, and data deposit, and what is the level of interest in instruction in these areas?

 

Methods: Librarians on the University of Illinois at Urbana Champaign campus conducted semi-structured interviews with bioengineering and biomedical researchers to explore researchers’ knowledge of data management best practices, awareness of library campus services, data management behavior and challenges managing research data. The topics covered during the interviews were current research projects, data types, format, description, campus repository usage, data-sharing, awareness of library campus services, data reuse, the anticipated impact of health on public and challenges (interview questions are provided in the Appendix).

Results: This study revealed the majority of researchers explore broad research topics, various file storage solutions, generate numerous amounts of data and adhere to differing discipline-specific practices. Researchers expressed both familiarity and unfamiliarity with DMP Tool. Roughly half of the researchers interviewed reported having documented protocols for file names, file backup, and file storage. Findings also suggest that there is ambiguity about what it means to share research data and confusion about terminology such as “repository” and “data deposit”. Many researchers equate publication to data sharing.

Conclusions: The interviews reveal significant data literacy gaps that present opportunities for library instruction in the areas of file organization, project workflow and documentation, metadata standards, and data deposit options. The interviews also provide invaluable insight into biomedical and bioengineering research in general and contribute to the authors’ understanding of the challenges facing the researchers we strive to support.