On January 26, 2017 in Barcelona, the EU project LEARN (LEaders Activating Research Networks: Implementing the LERU Research Data Roadmap and Toolkit) are organizing their 5th workshop on Research Data Management, entitled “Shaping and aligning research data management policies”, to which this document is a contribution. The workshop has been live streamed, and the videos archived. There have also been tweets under the #learnbcn hashtag.
Integrating policy and infrastructure in research data management: the perspective of researchers
As the interest in research data management is growing in many parts of the research ecosystem, policies and infrastructures are being put in place in a growing number of contexts. I will comment on these developments from the perspective of researchers who are supposed to abide by the policies and to use the infrastructures for their research. Drawing on examples from the ongoing Zika virus outbreak, I will pay special attention to policy and infrastructure elements that are facilitating or complicating research data management and explore avenues for standardization.
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- see this image used in his talk
- We should go beyond regarding publication as a (and even one) step within the research cycle, but start thinking about publishing the research process
- some funders now require that data be kept for 10 years after last consultation
- we should pay more attention to what should be deleted, and when (cf. CERN)
- see slide 17 of Paul Ayris talk, which summarized Research funder policies relevant to University College London
- I'll zoom in on that
- Science Europe argues for a bottom-up approach to open science
- I think it's important that we encourage all stakeholders to help advance open science, be it bottom-up, top-down or otherwise
- Framework was "submitted to several communities" but amongst the search results for "DMP framework", none are obviously related to Science Europe?
- Using Data management plans to enforce policies
- Not practical at the moment
- Need to move towards machine readable DMPs that are versioned and public
- I'll zoom in a bit here as well
- Domain Data Protocols?
- only thing I found is slide 5 in this presentation
- Open science is often perceived as yet another layer of bureaucracy
- Lots of bureaucratic procedures exist for reasons closely tied to the lack of transparency
- Look for opportunities to reduce bureaucracy by increasing openness and transparency
- cross-disciplinary, e.g.
- field-specific, e.g.
- Bermuda principles for human genome sequencing
- Policy memorandum by John Holdren, Director of the White House Office of Science and Technology Policy, "direct[ing] Federal agencies with more than $100M in R&D expenditures to develop plans to make the results of federally funded research freely available to the public". (Feb 2013)
- SPARC overview of responses (regularly updated)
- Apart from NIH, three agencies so far (AHRQ, NASA, NIST) opted for an approach based on PubMed Central for handling the literature part
- NIH policies on access and sharing
- NSF policy
- several of these agencies envision a "research data commons"
- SPARC overview of responses (regularly updated)
- Executive Order by President Obama: Making Open and Machine Readable the New Default for Government Information (May 2013)
- Personalized Medicine Initiative
- Precision Medicine Initiative (PMI) Working Group Report to the Advisory Committee to the Director, NIH
- Blue button
- Rehabilitation Act, Section 508
- NIH Public Access Policy (mandatory since April 2008)
- supported by dedicated infrastructure, in particular PubMed Central
- FAQ
- NIH Data Sharing Policy
- A vision for open data at NIH
- The Commons
- Data citation
- Data discoverability
- also for software and other research outputs
- intramural/ extramural
- 27 of them, e.g. the National Library of Medicine (NLM), where I am an intramural researcher
- The report on the strategic vision for the National Library of Medicine recommends that NLM should
- "be a leader and innovator in open science efforts worldwide"
- "lead efforts to support and catalyze open science, data sharing, and research reproducibility, striving to promote the concept that biomedical information and its transparent analysis are public"
- and, in particular, "lead efforts to promulgate and implement best practices in open source, open science, standards, and data harmonization, forming partnerships across communities, stakeholder organizations, agencies, and countries" as well as "be an active participant in the design and oversight of programs that incentivize and celebrate the open sharing of data and resources."
- My comments on how to do this in practice.
- for every collaborator on a project
- discipline-specific policies
- journal-specific policies
- policies regarding the sharing of data, databases, code, text, multimedia, patient information, sensitive information etc.
- institution-specific policies
- funder-specific policies
- platform-specific policies
- ethics
- special circumstances, e.g. public health emergencies
- Summary of Open Data Policy Harmonization Workshop
- How to write a good open data policy
- Anyone here ever booked an organized travel? What did your travel agency provide you with?
- Now imagine it's not people that travel, but data.
- Data management plans at NIH
- Ten Simple Rules for Creating a Good Data Management Plan
- OA Compliance Checking for Wellcome Trust
- Making DMPs actionable and public