“Complying with the UKRI open access policy: member experiences
Representatives from three HEI libraries will share their experiences of implementing the UKRI OA policy at their institution.”
Abstract: Many journals now require data sharing and require articles to include a Data Availability Statement. However, several studies over the past two decades have shown that promissory notes about data sharing are rarely abided by, and that data is generally not available upon request. This has negative consequences for many essential aspects of scientific knowledge production, including independent verification of results, efficient secondary use of data, and knowledge synthesis. Here, I assessed the prevalence of data sharing upon request in articles employing the Implicit Relational Assessment Procedure published within the last 5 years. Of 52 articles, 42% contained a Data Availability Statement, most of which stated that data was available upon request. This rose from 0% in 2018 to 100% in 2022. Only 25% of articles’ authors actually shared data upon request. Among articles stating that data was available upon request, only 17% shared data upon request. The presence of Data Availability Statements was not associated with higher rates of data sharing (p = .80). Results replicate those found elsewhere: data is generally not available upon request, and promissory Data Availability Statements are typically not adhered to. Issues, causes, and implications are considered.
“AAAS and other groups warn of rise of inequalities from implementation of White House request Sixteen US scientific societies and associations have called for studies of scholarly publishing costs, as the country’s largest biomedical research funder deliberates on how to respond to government requirements on open access to papers. Last year, the White House asked federal research funders including the National Institutes of Health to ensure immediate open access to publications reporting work they have supported. Individual funders have leeway over the implementation, and the NIH recently sought input on its plan to comply….”
Representatives from three HEI libraries will share their experiences of implementing the UKRI OA policy at their institution
“In this moment of success for their open access advocacy, it is healthy for libraries to pause and consider the path forward. Today, I advance the proposal that the academic library should not take responsibility for implementing open access mandates. This is first of a series of posts reviewing strategies for university engagement with funder mandates….”
“We have combined Sherpa Romeo, Sherpa Juliet, Sherpa Fact, OpenDoar, and our Transitional Agreement Look-up tool in to a single platform.
The new platform allows our users access to our services in one location and has been rebuilt allowing consideration for future tools….”
“As more funder open access policies are launched—and more researchers are covered by one or more requirements—there is an increasing need to support authors in fulfilling the varied terms of these policies. With a mission to build tools so that open access is easy and equitable, OA.Works has focused on providing support to faculty, funders, and libraries to make compliance as easy as possible. Join the next OpenCon Library Community Call on Tuesday, April 11th, at 12pm ET / 9am PT for a conversation with Joe McArthur, director of OA.Works, about emerging tools to support compliance and what kinds of future support would be most helpful for libraries….”
“Demands are mounting on researchers to have data management and sharing plans, with the National Institutes of Health (NIH) being the latest government funder to implement a mandate in the form of the 2023 NIH Data Management and Sharing Policy. This webinar features a panel discussion from experts on how research teams can implement best-practice data management, with particular emphasis on the NIH’s requirements. The panelists will also discuss the emerging space of tooling designed to make adhering to best practices and funder guidelines easy for researchers.”
Abstract: Purpose: This study investigated how well current open access (OA) diamond journals in the Directory of Open Access Journals (DOAJ) and a survey conform to Plan S requirements, including licenses, peer review, author copyright, unique article identifiers, digital archiving, and machine-readable licenses.
Method: Data obtained from DOAJ journals and surveyed journals from mid-June to mid-July 2020 were analyzed for a variety of Plan S requirements. The results were presented using descriptive statistics.
Results: Out of 1,465 journals that answered, 1,137 (77.0%) reported compliance with the Committee on Publication Ethics (COPE) principles. The peer review types used by OA diamond journals were double-blind (6,339), blind (2,070), peer review (not otherwise specified, 1,879), open peer review (42), and editorial review (118) out of 10,449 DOAJ journals. An author copyright retention policy was adopted by 5,090 out of 10,448 OA diamond journals (48.7%) in DOAJ. Of the unique article identifiers, 5,702 (54.6%) were digital object identifiers, 58 (0.6%) were handles, and 14 (0.1%) were uniform resource names, while 4,675 (44.7%) used none. Out of 1,619 surveyed journals, the archiving solutions were national libraries (n=170, 10.5%), Portico (n=67, 4.1%), PubMed Central (n=15, 0.9%), PKP PN (n=91, 5.6%), LOCKSS (n=136, 8.4%), CLOCKSS (n=87, 5.4%), the National Computing Center for Higher Education (n=6, 0.3%), others (n=69, 4.3%), no policy (n=855, 52.8%), and no reply (n=123, 7.6%). Article-level metadata deposition was done by 8,145 out of 10,449 OA diamond journals (78.0%) in DOAJ.
Conclusion: OA diamond journals’ compliance with industry standards exemplified by the Plan S technical requirements was insufficient, except for the peer review type.
Purpose:
This study investigated how well current open access (OA) diamond journals in the Directory of Open Access Journals (DOAJ) and a survey conform to Plan S requirements, including licenses, peer review, author copyright, unique article identifiers, digital archiving, and machine-readable licenses.
Method:
Data obtained from DOAJ journals and surveyed journals from mid-June to mid-July 2020 were analyzed for a variety of Plan S requirements. The results were presented using descriptive statistics.
Results:
Out of 1,465 journals that answered, 1,137 (77.0%) reported compliance with the Committee on Publication Ethics (COPE) principles. The peer review types used by OA diamond journals were double-blind (6,339), blind (2,070), peer review (not otherwise specified, 1,879), open peer review (42), and editorial review (118) out of 10,449 DOAJ journals. An author copyright retention policy was adopted by 5,090 out of 10,448 OA diamond journals (48.7%) in DOAJ. Of the unique article identifiers, 5,702 (54.6%) were digital object identifiers, 58 (0.6%) were handles, and 14 (0.1%) were uniform resource names, while 4,675 (44.7%) used none. Out of 1,619 surveyed journals, the archiving solutions were national libraries (n=170, 10.5%), Portico (n=67, 4.1%), PubMed Central (n=15, 0.9%), PKP PN (n=91, 5.6%), LOCKSS (n=136, 8.4%), CLOCKSS (n=87, 5.4%), the National Computing Center for Higher Education (n=6, 0.3%), others (n=69, 4.3%), no policy (n=855, 52.8%), and no reply (n=123, 7.6%). Article-level metadata deposition was done by 8,145 out of 10,449 OA diamond journals (78.0%) in DOAJ.
Conclusion:
OA diamond journals’ compliance with industry standards exemplified by the Plan S technical requirements was insufficient, except for the peer review type.
Abstract: Objective: In the interest of making data findable, accessible, interoperable, and reusable (FAIR), the National Institutes of Health (NIH) will institute a new Data Management and Sharing Policy in January 2023. This policy will require researchers applying for NIH funding to submit a Data Management and Sharing Plan. As 63% of grant dollars received by University of Massachusetts Chan Medical School (UMass Chan) researchers comes from the NIH, we explored whether UMass Chan researchers are currently sharing data associated with their published research and how they shared their data.
Methods: PubMed was searched for articles published in 2019 with a UMass Chan researcher as either the first or last author. These articles were examined for evidence of original or reused data, the type of data, whether the article stated that data was available, and where and how to find that data.
Results: Of the 361 articles with original data, 26% had a data availability statement. However, most articles (71%) did not mention where data could be accessed. The data storage location of the estimated 1551 original datasets was similarly not mentioned for 74% the datasets with the next largest category being available upon request (8.6%). Genomic data repositories such as the Gene Expression Omnibus were among the top repositories used by authors. Similar areas for improvement were noted for permanent identifier use (46% had a permanent identifier), using non-proprietary file formats (most popular format was Excel), and citing reused data. Authors who published open access were more likely to share their data.
Conclusions: While some researchers at UMass Chan have embraced data sharing, particularly genomic data sharing, we expect there will be more data shared in the coming years with the implementation of the new NIH Data Management and Sharing Policy.
“The goal of this post is to share the process I used to collect open research publications data, using primarily OpenRefine, to understand the impact of our Open Access (OA) Publication Policy at the Michael J. Fox Foundation (MJFF). Inspired by the Year of Open Science, it is my hope that the practical recipes shared here can help others assess the impact of open research at their organizations.
Tools used
For this work, I used three free tools which you can either use online or download to your computer:
Google Sheets – A spreadsheet program included as part of the free, web-based Google Docs Editors suite offered by Google. Wikipedia
OpenRefine – An open-source desktop application for data cleanup and transformation to other formats, an activity commonly known as data wrangling. Wikipedia
Publish or Perish – A software program that retrieves and analyzes academic citations….”
“One of the most important features of OSF is something you may not even be aware of, yet you use it all the time: Metadata. All OSF Projects, Registrations, and Preprints come with associated metadata — information about the OSF object like the title, description, or keywords. Sometimes metadata is so integral to research we may not even notice it as a distinct element (as may be the case with a title, or with the date something is created). But without that title, or description, or keyword your research becomes hard to find and even harder to understand.
Researchers are now able to add information about the types of materials they are sharing on the OSF, as well as sources of funding or support. With an increasingly large number of resources online, whether on the OSF or not, this kind of information is crucial to enable organization, discovery, and reuse of your research outputs.
This metadata is so essential, in fact, that a number of new policies from major national, international, and other funding and research support agencies are requiring it. A new Data Sharing Policy from the NIH, that just went into effect on January 25th, calls for sharing of a set of common data elements, including the funder and resource type information that our recent changes support. In addition to specific guidelines like those, other agencies and institutions are supporting the creation of more mature infrastructure for data sharing. The recent policy from the White House Office of Science and Technology Policy, (which we wrote about last fall), and the UNESCO Recommendation on Open Science envision a research ecosystem that will need enhanced metadata to function….”
“Beginning with the first funding deadlines in January, all NIH grant proposals will be required to include a formal, two-page Data Management and Sharing Plan (DMSP), which must include the following elements….
Crucially, in addition to adding a required DMSP, the data management strategies stated in the plan will be audited and monitored externally, and compliance with stated plans may affect the funding status of grants.
Fortunately, here at Harvard affiliates have access to a variety of computing infrastructure and systems to effectively manage and steward a wide range of research outputs associated with modern, data-driven, computational research.
Harvard’s libraries, Harvard University Information Technology (HUIT), Research Computing, and Sponsored Programs offices have all been adding services and building capacity to support researchers complying with this new policy next year.
In the resources section below, we’ve included links to an executive summary of the policy and a collection of FAQs that we created specifically for Harvard users. We’ve also included resources from the NIH designed to support researchers writing and implementing a DMSP for the 2023 funding cycles.
Along with the requirement to make research data publicly available, in its new policy the NIH strongly encourages the use of established data repositories. When selecting an appropriate repository, researchers should plan to utilize subject- or domain-specific repositories for their data types if possible. When a disciplinary repository does not exist, researchers should use generalist repositories that accept all data types. We’ve included information on Harvard Dataverse and other generalist repositories in the resources section below….”