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Research data: publishers, policies and patient privacy

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Presentation by Iain Hrynaszkiewicz, Springer Nature, to the AHMEN meeting on 19 June 2017 in Sydney, Australia.

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Research data: publishers, policies and patient privacy

  1. 1. 0 Research data: publishers, policies and patient privacy Iain Hrynaszkiewicz AHMEN - ANDS meeting 19th June 2017
  2. 2. 1 Policy as an incentive and barrier to data sharing • Funder policy motivates researchers to share data (88%1) But • Complying with funder policies is a challenge for more than half of researchers (54%2) 1. Schmidt et al. (2016). PLoS ONE 11(1): e0146695. doi:10.1371/journal.pone.0146695 (n=1248) (& image credit, CC BY) 2. Treadway et al. (2016). figshare. https://dx.doi.org/10.6084/m9.figshare.4036398.v1 (n= 2061)
  3. 3. 2 http://www.springernature.com/gp/authors/research-data-policy Springer Nature’s data policy standardisation project Reference: Standardising and harmonising research data policy in scholarly publishing Iain Hrynaszkiewicz, Aliaksandr Birukou, Mathias Astell, Sowmya Swaminathan, Amye Kenall, Varsha Khodiyar bioRxiv 122929; doi: https://doi.org/10.1101/122929
  4. 4. 3 Policy implementation progress – 19th June 2017 • More than 1,000 (~45%) Springer Nature journals have adopted a standard policy • Includes all Nature and BioMed Central journals; Springer Research Group journals being added weekly • Policies and recommended repository list released under CC BY (open access) to enable wider policy adoption and development • Research Data Alliance Interest Group formed to explore policy standardisation across other publishers and stakeholders (co-chaired by Wiley) https://www.rd-alliance.org/groups/data-policy-standardisation-and- implementation
  5. 5. 4 https://www.rd-alliance.org/groups/data-policy-standardisation-and-implementation Community and stakeholder engagement via RDA Co-chairs: Natasha Simons (ANDS), Simone Taylor (Wiley), David Kernohan (Jisc), Iain Hrynaszkiewicz (Springer Nature) Proposed group activities can build on and be informed by research carried by Jisc, ongoing activities of ANDS and work of Springer Nature on data policy
  6. 6. 5 (Proposed) Group objectives summary • Define a common framework for research data policy, focusing on journals and publishers (first), then funders and other stakeholders • Produce guidance on complying with and implementing research data policy for different stakeholders • Facilitate greater understanding between stakeholders (publishers, institutions, researchers, repositories, societies) • Increase adoption of research data policies in particular journals and publishers • Highlight examples of good/best practice • Understanding the needs of researchers and research support staff Community call planned for July 2017 to gather requirements for policies to feed into RDAP10 meeting in Montreal in September
  7. 7. 6 Common approaches to data sharing in journals Data availability statements provide a statement about where data supporting the results reported in a published article can be found. Required by many journals/publishers (PLOS, BMJ, Nature, BMC, new ICMJE policy) and some funding agencies (e.g. EPSRC in the UK). Common forms: • The datasets generated during and/or analysed during the current study are available in the [NAME] repository, [PERSISTENT WEB LINK TO DATASETS]. • The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. • All data generated or analysed during this study are included in this published article (and its supplementary information files). http://www.springernature.com/gp/group/data-policy/data-availability-statements
  8. 8. 7 Anonymisation is often non-trivial “...datasets that contain three or more indirect identifiers, such as age or sex, should be reviewed by an independent researcher or ethics committee” Hrynaszkiewicz et al., BMJ 2010;340:c181
  9. 9. 8 • Data availability declines over time1 • The most effective journal data polices mandate data sharing in a repository and a data availability statement with a link to the data2 • Data availability from authors on request has been found wanting in several studies/case studies3-5 • Sharing of clinical research data usually happens between individuals and research groups (non-publicly) 1. Vines et al. (2013) Current Biology. DOI: http://dx.doi.org/10.1016/j.cub.2013.11.014 2. Vines, et al. (2013) FASEB J doi: 10.1096/a.12-218164 3. Systematic Reviews 2014, 3:97 doi:10.1186/2046-4053-3-97 4. American Psychologist, Vol 61(7), Oct 2006, 726-728. doi:10.1037/0003-066X.61.7.726 5. PLoS ONE 4(9): e7078. doi:10.1371/journal.pone.0007078 Data on (reasonable) request – issues
  10. 10. 9 Recommendations: • New scholarly journal and article types and formats to increase accessibility to non- public research data e.g. data papers, data statements • Journals to develop stronger links with specialist data repositories • Use and promote voluntary data sharing services e.g. YODA, CSDR • Increase collaboration between journals, data repositories, researchers, funders, and voluntary data sharing services • Use the journal Scientific Data to test and provide example of changes to article format and peer-review process to more robustly link them to and peer review data that are only available on request • Assess and promote features of data repositories to better accommodate non- public clinical datasets, including Data Use Agreements (DUAs) Publishing papers about non-public data: doing better Hrynaszkiewicz et al. Publishing descriptions of non-public clinical datasets: proposed guidance for researchers, repositories, editors and funding organisations. Research Integrity and Peer Review 2016 1:6 DOI: 10.1186/s41073-016-0015-6
  11. 11. In practice example: Open access data descriptor (paper) Scientific Data 4, Article number: 170045 (2017) doi:10.1038/sdata.2017.45
  12. 12. Linked to controlled access data (in Synapse) Gosline, S. J.C. Synapse http://doi.org/10.7303/syn4984604 (2016).
  13. 13. • Be broadly supported and recognised within their scientific community • Ensure long-term persistence and preservation of datasets in their published form • Implement relevant, community-endorsed reporting requirements • Provide stable identifiers for submitted datasets • Allow [public] access to data without unnecessary restrictions • Provide stable identifiers for metadata records about non-public dataset(s) • Allow access to data with the minimum of restrictions needed to ensure protection of privacy and appropriateness of secondary analyses, codified in Data Use Agreements (DUAs) • Allow access to data in a timely manner • Provide support for users of data Appendix: Repositories for non-public data: criteria Hrynaszkiewicz et al. Publishing descriptions of non-public clinical datasets: proposed guidance for researchers, repositories, editors and funding organisations. Research Integrity and Peer Review 2016 1:6 DOI: 10.1186/s41073-016-0015-6
  14. 14. 1313 ANDS_AHMEN_19Jun_2017 Thank you rda-data-policy-standardisation-ig@rda-groups.org iain.hrynaszkiewicz@nature.com

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