Update from Data policy standardisation and implementation IG
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The document discusses the standardization and implementation of research data policies among various publishers and journals, highlighting the variability and challenges for researchers. It introduces a draft framework aimed at creating common standards for data policies, thereby enhancing compliance and reproducibility in research. The framework includes features such as data availability statements, mandatory sharing requirements, and citation guidelines, with plans for community feedback and further implementation steps outlined.
Update from Data policy standardisation and implementation IG
- 1. Data Policy Standardisation and Implementation IG Varsha Khodiyar, PhD RDA P12 , 5th Nov 2018 IllustrationinspiredbytheworkofAlfredNobel
- 2. 1 Current landscape of publisher research data policies • Springer Nature: Four policies – Type 1 to Type 4 with additional requirements for life sciences journals. 2016
- 3. 2 Data policy standardisation and implementation IG est 2016 https://www.rd-alliance.org/groups/data-policy-standardisation-and-implementation Co-chairs: Natasha Simons (ARDC), Simon Goudie (Wiley), Azhar Hussain (Jisc), Iain Hrynaszkiewicz (Springer Nature) Primary objective is to help define common frameworks for research data policy – starting with journals and publishers and latterly funding agencies
- 4. 3 Current landscape of publisher research data policies • Springer Nature: 2016 Four policies – Type 1 to Type 4 with additional requirements for life sciences journals. • Elsevier: 2017 Five options – A-E, from encouraging research data deposit and citation to requiring data deposit, data citation and data peer review • Wiley: 2017 Three policies – Encourages Data Sharing, Expects Data Sharing, Mandates Data Sharing. • Taylor & Francis: 2018 Four policies – Basic, Share on Reasonable Request, Publicly Available, Open Data and Open and Fully FAIR.
- 5. 4 Journal and publisher research data policy DRAFT framework https://docs.google.com/document/d/1DTAfOKkE1a2n2f_1hGcrXlrw-5Tq_AL5tk-ju8B82_E An increasing number of publishers and journals are implementing policies that require or recommend published articles to be accompanied by the underlying research data. These policies are an important part of the shift toward reproducible research and contribute to the availability of research data for reuse. While uptake of journal data policies is on the rise, there is wide variation between policies…difficult for researchers in understanding and complying with data policies, and complex for infrastructure providers and research support staff to assist data policy compliance. There is clear benefit in a more standardised approach, as evidenced in the findings of the Jisc UK Journal Data Registry Project and the pioneering work of publishers such as Springer Nature to develop and support standard policy types for their journals. This draft framework is intended to help Journal Editors to navigate the creation or enhancement of a data availability policy. It reflects international efforts by the Research Data Alliance Data Policy Standardisation and Implementation Interest Group to identify the key elements of a good data availability policy and to standardise data policies.
- 6. 5 Features 1 to 4 Feature What and why How (implementation) Definition of research data Define which research data the policy applies to Define research data as being the data that support the findings or claims made in the published article. Definition of exceptions Acknowledge legitimate exceptions Define sensitive data Embargoes Define if and what embargoes on data release are permitted Include a positional statement on embargoes Supplementary materials Define the position on data sharing via supplementary material Specify if sharing via supplementary materials is permitted but data sharing via repositories must be preferred wherever possible.
- 7. 6 Features 5 to 8 Feature What and why How (implementation) Data repositories State position on use of data repositories Must be supported with list of recommended, trusted or supported data repositories Data citation Statement on support for persistent identifiers Specify that data citation is permitted and provide style guide for referencing data Data licensing Define position on licensing and copyright for research data Specify permitted data licenses Researcher/ author support Research data sharing remains a new concept for some journals and disciplines Provide details for an individual or team, that authors can contact with questions on research data policy compliance and data sharing in general
- 8. 7 Features 9 to 12 Feature What and why How (implementation) Data availability statements (DASs) Define position on provision of DASs Include definition of a DAS, advice on enforcement, and guidance on placement within manuscript. Mandatory data sharing (specific papers) Statement on whether data sharing is mandatory for specific types of research data Specify any data sharing mandates that are a condition of submission and/or publication. Provide advice on mechanisms for compliance. Data formats and standards State position on the use of community/discipline specific data standards Provide a statement in support of community standards. Note minimal reporting standards are NOT included in this policy. Mandatory data sharing (all papers) Sharing of research data via repositories or supplementary information is required on or publication for all articles For these journals “available on request” DASs are not acceptable. Provide advice on mechanisms for compliance.
- 9. 8 Features 12 to 15 Feature What and why How (implementation) Mandatory data citation To ensure consistent linking of important research outputs to published articles State requirements for authors to formally reference any publicly-available data on which the conclusions of the paper rely Peer review of data Where data are made available with research articles they are accessible to peer reviewers. For journals with a strong focus on data peer review of the data can be required. Statement on whether peer review of data is expected or required Data Management Plans (DMPs) Analogous to medical journals encouraging sharing or publication of study protocols. Define if DMPs are encouraged or required to be shared under the research data policy.
- 10. 9 Policy levels - features 1 to 9 Feature Policy 1 Policy 2 Policy 3 Policy 4 Policy 5 Policy 6 Definition of the research data ● ● ● ● ● ● Definition of exceptions ● ● ● ● ● ● Embargoes ● ● ● ● ● ● Supplementary materials ● ● ● ● ● ● Data repositories ● ● ● ● ● ● Data citation ● ● ● ● ● ● Data licensing ● ● ● ● ● ● Researcher/ author support ◐ ● ● ● ● ● Data availability statements ○ ◐ ● ● ● ● ○ ◐ ● Not required May be required/ encouraged Required and enforced
- 11. 10 Policy levels - features 10 to 15 Feature Policy 1 Policy 2 Policy 3 Policy 4 Policy 5 Policy 6 Mandatory data sharing (specific papers) ○ ◐ ◐ ● ● ● Data formats and standards ○ ◐ ◐ ◐ ◐ ● Mandatory data sharing (all papers) ○ ○ ◐ ◐ ● ● Mandatory data citation ○ ○ ◐ ◐ ◐ ● Peer review of data ○ ○ ◐ ◐ ◐ ● Data Management Plans (DMPs) ○ ○ ◐ ◐ ◐ ● ○ ◐ ● Not required May be required/ encouraged Required and enforced
- 12. 11 Comments or feedback on the draft policy framework? Key issues being addressed in revision of framework • Improve clarity around when an implementation action is simply to provide information, and when implementation requires a new check by editors, reviewers or publishers, or action by an author • Better define the scope e.g. the document will not define criteria for trusted data repositories or provide detailed guidance on data availability statements (other projects are working on these) • Getting the balance between pragmatism and immediate practical use, and aspiration (e.g. DMP requirements, supplementary information files) • Your comments?
- 13. 12 Next steps for the data policy standardisation and implementation IG • Nov-Dec 2018: Complete revision, in light of community comments, of Master Policy framework • Jan-Mar 2019: Release revision for community comment • Apr 2019: Present final draft at RDA Plenary • April 2019 – • Increase publisher, funder, institution and editor engagement • Implementation of framework at first journals/publishers • Submit framework for peer reviewed publication • Explore other adoption, implementation and outreach activities e.g. • Assessment tools for journals and publishers • Case studies • Impact (cost and benefit) analyses • Open to suggestions..!
- 14. 1313 The story behind the image Alfred Nobel (1833–1896) Alfred Nobel was a Swedish chemist, engineer and inventor of dynamite. Dynamite made him very wealthy but partly in response to concerns about its negative uses, he decided to give the vast majority of his estate to establish the four Nobel Prizes with a fifth awarded in his memory, to people or organisations who promote peace around the world. Thank you [email protected] @varsha_khodiyar Presented on behalf of Iain Hrynaszkiewicz Head of Data Publishing [email protected]