About Robin Rice

Data Librarian and Head, Research Data Support Library & University Collections

Edinburgh Open Research Conference Proceedings

EOR logoOne of the ambitions for the EOR conference held in March, 2022, when we first started planning it was to make it as open and accessible as possible. To achieve this we made the whole event hybrid so that plenary talks, posters, and workshops were all accessible on the day to both in person and remote attendees. While this generally worked very well for both remote and in-person attendees, we also wanted to make it available to people who couldn’t attend on the day – so we recorded everything, and the recordings of the talks and posters can now be openly accessed through our Edinburgh Open Research journal at http://journals.ed.ac.uk/eor.

Kerry Miller
Research Data Support Officer & Open Research Co-Ordinator
Library Research Support

It Is Our Mantra

Last week I was honoured to accept an invitation to speak at the Library Technology Conclave at Somaiya Vidyavihar University in Mumbai, India, organised by Informatics Limited and the University. A prelude the day before the event included a half-day “Research Data Management (RDM) Basics” tutorial for about 50 attending librarians, which I delivered based on adaptations of our Research Data Support team’s training materials for PhD students and staff. The training exercises, developed from a few other external librarian training sessions I’ve done, focused on building librarians’ confidence in supporting researchers with data management planning and data sharing. Doing the training in person helped me to overcome communication barriers and foster deeper engagement than could have happened online only.

Lighting the flame of the conference

Lighting the flame of the hybrid conference

The conference was on the theme of “Research Data Management and Stewardship: Building Blocks for Open Science,” with a number of eminent librarians, scientists, and educators speaking in keynotes and on panels in six thematic sessions, in-person and remotely. There was a palpable sense of urgency to the proceedings, as those in the room were concerned that India’s scientific institutions, without funder mandates, national open infrastructure, nor observable changes in cultural norms for RDM and Open Science, might be left behind, given this emerging new, more transparent way of conducting research. Questions focused not on the What or Why of Open Science, but how to instigate behavioural change of scientists and researchers, and how librarians could create demand for new services such as data repositories and quickly skill themselves up.

I have some empathy for their position. A decade or so ago I attended conferences which felt more like hand-wringing than change-making, with endless talk of carrots and sticks (and carrot-stick jokes), with researchers explaining over and again their reluctance to be ‘scooped’ by giving access to their data. I am not sure what caused the tipping point to talking about the potential of data sharing and open science to the exciting reality of it happening, but it seems to have come round (more or less). I do still harbour concerns that our own researchers will be left out of participation in the shared infrastructure that is the European Open Science Cloud because of Brexit-related barriers here.

Robin with attendeesOne talk that piqued my interest involved a survey of librarians in Gujarat about RDM and their capacity to deliver new types of service, by Dr. Bhakti Gala. As the Indian LIS (library and information science) curriculum was apparently seen to not be delivering RDM training to any great extent yet, the researcher had asked how the librarians had acquired knowledge of RDM. She said that about half the librarians who had pursued self-training had learned from the free, online MANTRA course (which stands for Research Data Management Training), offered by the University of Edinburgh.

The Chair of the panel, Prof Shalini Urs, with whom I had had a conversation over dinner with about the name of the course, said [naming me, as I sat in the audience] that I would be happy to hear that was the case, to which I of course smiled and nodded. Alluding to our prior conversation about whether the name was a cultural [mis-]appropriation or not, she looked me in the eye and said, “It is Our MANTRA, now.” Which is, of course, the great thing about Openness.

Simon Smith joins the Research Data Support Team

It has been a long pandemic, and some bright spots are beginning to appear on the horizon. One of them is that we have a new professional joining our team, to work with Kerry Miller in the role of Research Data Support Officer – Simon Smith.

The University’s Digital Research Services programme makes it possible to fund this post for the Research Data Service – deemed an essential addition following a period of reduced resource, because of the need to increase outreach, training and awareness, and take-up of services in the light of the new Research Data Management Policy.

portrait of Simon SmithSimon has worked in Research Data Management since 2015, when he joined the Open Research Team at the University of Surrey. He has spent his time helping to develop a range of research data management (RDM) services, implementing two repositories, and learning to love data management planning. He is genuinely interested in issues around data licencing and sensitive/personal data. His teaching and research background is in philosophy, in the service of which he edited a scholarly journal. Now, however, he is slightly obsessed with James Joyce’s Ulysses.

Simon has been in post for nearly 2 weeks, and is keen to meet researchers and their supporters from all corners of the university – please send any and all invitations to come chat about RDM to data-support@ed.ac.uk! We look forward to gaining from Simon’s insights and experience.

Robin Rice & Simon Smith
Library & University Collections

University of Edinburgh’s new Research Data Management Policy

Following a year-long consultation with research committees and other stakeholders, a new RDM Policy (www.ed.ac.uk/is/research-data-policy) has replaced the landmark 2011 policy, authored by former Digital Curation Centre Director, Chris Rusbridge, which seemed to mark a first for UK universities at the time. The original policy (doi: 10.7488/era/1524) was so novel it was labeled ‘aspirational’ by those who passed it.

"Policy"

CC-BY-SA-2.0, Sustainable Economies Law Centre, flickr

RDM has come a long way since then, as has the University Research Data Service which supports the policy and the research community. Expectation of a data management plan to accompany a research proposal has become much more ordinary, and the importance of data sharing has also become more accepted in that time, with funders’ policies becoming more harmonised (witness UKRI’s 2016 Concordat on Open Research Data).

What has changed?

Although a bit longer (the first policy was ten bullet points and could fit on a single page!), the new policy adds clarity about the University’s expectations of researchers (both staff and students), adds important concepts such as making data FAIR (explanation below) and grounding concepts in other key University commitments and policies such as research integrity, data protection, and information security (with references included at the end). Software code, so important for research reproducibility, is included explicitly.

CC BY 2.0, Big Data Prob, KamiPhuc on flickr

Definitions of research data and research data management are included, as well as specific references to some of the service components that can help – DMPOnline, DataShare, etc. A commitment to review the policy every 5 years, or sooner if needed, is stated, so another ten years doesn’t fly by unnoticed. Important policy references are provided with links. The policy has graduated from aspirational – the word “must” occurs twelve times, and “should” fifteen times. Yet academic freedom and researcher choice remains a basic principle.

Key messages

In terms of responsibilities, there are 3 named entities:

  • The Principle Investigator retains accountability, and is responsible as data owner (and data controller when personal data are collected) on behalf of the University. Responsibility may be delegated to a member of a project team.
  • Students should adhere to the policy/good practice in collecting their own data. When not working with data on behalf of a PI, individual students are the data owner and data controller of their work.
  • The University is responsible for raising awareness of good practice, provision of useful platforms, guidance, and services in support of current and future access.

Data management plans are required:

  • Researchers must create a data management plan (DMP) if any research data are to be collected or used.
  • Plans should cover data types and volume, capture, storage, integrity, confidentiality, retention and destruction, sharing and deposit.
  • Research data management plans must specify how and when research data will be made available for access and reuse.
  • Additionally, a Data Protection Impact Assessment is required whenever data pertaining to individuals is used.
  • Costs such as extra storage, long-term retention, or data management effort must be addressed in research proposals (so as to be recovered from funders where eligible).
  • A University subscription to the DMPOnline tool guides researchers in creating plans, with funder and University templates and guidance; users may request assistance in writing or reviewing a plan from the Research Data Service.

FAIR data sharing is more nuanced than ‘open data’:

  • Publicly funded research data should be made openly available as soon as possible with as few restrictions as necessary.
  • Principal Investigators and research students should consider how they can best make their data FAIR in their Data Management Plans (findable, accessible, interoperable, reusable).
  • Links to relevant publications, people, projects, and other research products such as software or source code should be provided in metadata records, with persistent identifiers when available.
  • Discoverability and access by machines is considered as important as access by humans. Standard open licences should be applied to data and code deposits.

Use data repositories to achieve FAIR data:

  • Research data must be offered for deposit and retention in a national or international data service or domain repository, or a University repository (see next bullet).
  • PIs may deposit their data for open access for all (with or without a time-limited embargo) in Edinburgh DataShare, a University data repository; or DataVault, a restricted access long-term retention solution.
  • Research students may deposit a copy of their (anonymised) data in Edinburgh DataShare while retaining ownership.
  • Researchers should add a dataset metadata record in Pure to data archived elsewhere, and link it to other research outputs.
  • Software code relevant to research findings may be deposited in code repositories such as Gitlab or Github (cloud).

Consider rights in research data:

  • Researchers should consider the rights of human subjects, as well as citizen scientists and the public to have access to their data, as well as external collaborators.
  • When open access to datasets is not legal or ethical (e.g. sensitive data), information governance and restrictions on access and use must be applied as necessary.
  • The University’s Research Office can assist with providing templates for both incoming and outgoing research data and the drafting and negotiation of data sharing agreements.
  • Exclusive rights to reuse or publish research data must not be passed to commercial publishers.

Robin Rice
Data Librarian and Head, Research Data Support
Library & University Collections