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

The big 3-0-0-0: DataShare reaches three thousand datasets

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Confetti banner says "3,000th deposit!!!" 2021-08-02

Timestamp showing the accession of the deposit on the 2nd of August.

We’re thrilled Edinburgh DataShare has just ingested its 3,000th deposit:

Davey, Thomas; Draycott, Samuel; Pillai, Ajit; Gabl, Roman; Jordan, Laura-Beth. (2021). Wave buoy in current – experimental data, [dataset]. University of Edinburgh. School of Engineering. Institute for Energy Systems. FloWave Ocean Energy Research Facility. https://doi.org/10.7488/ds/3105.

The depositor was Dr Tom Davey, Senior Experimental Officer in the School of Engineering, who said:

“It is a pleasure for us all in FloWave to see one of our datasets achieve this milestone for Edinburgh DataShare. This is also the tenth DataShare upload making use of experimental outputs from the FloWave Ocean Energy Research Facility. Providing a reliable and accessible repository of our project outputs is not only important for our funders, but also promotes new research collaborations and builds lasting impact for our experimental programmes. This particular project will aid in the understanding measuring wave and currents at deployment sites for offshore renewable energy technologies, and adds to the existing FloWave portfolio of datasets in the field of wave energy, tidal energy, advanced measurement, and remote operated vehicles.”

You can explore more data generated at FloWave in the IES DataShare Collection:

Collection – The Institute for Energy Systems (IES) (ed.ac.uk)

Although the ‘wave buoy in current’ dataset is under temporary embargo, currently set to expire on the 5th of September, it is possible to request the data using DataShare’s request-a-copy feature in the meanwhile. Embargoes may be extended, or lifted early, usually reflecting publication dates.

You might also enjoy this hilarious and very popular video about FloWave:

 

Pauline Ward

Research Data Support Assistant

Library & University Collections

University of Edinburgh

Research data management in a time of quarantine

Covid-19 has shaken up our world, and disrupted University life as we know it. But in terms of a silver lining, it has provided opportunities for open data / open research to prove their worth, in the search for a vaccine and other approaches to managing and treating the complications of the virus. SPARC Europe have collected a number of case studies on Open Science and the Coronavirus. If you’ve been working on Coronavirus research here at Edinburgh, we’d love to hear from you, especially if there is anything we might be able to do to help. So far we have engaged with researchers in all three Colleges studying, or hoping to study, an aspect of COVID-19; about handling sensitive data, archiving or sharing relevant data, or bidding for new research.

How has it affected us in Research Data Support?

  • We are all working from home, although some of us have unavoidable childcare responsibilities which may slow down responses;
  • In terms of answering Research Data Management (RDM) enquiries it’s business as usual. UniDesk has been a little quieter than usual, but we are receiving more complex queries as researchers adjust to the new reality;
  • Data Management Plan (DMP) assistance is business as usual, and we are now set up on Teams for video consultations – let us know if you’d be interested in one of these;
  • During the lockdown we will be refreshing our existing Research Data MANTRA training and directing research staff and students to this resource in place of our face-to-face training, which has been temporarily suspended. If you have a question or would like to discuss any aspect of RDM or Data Management Planning please contact the team using data-support@ed.ac.uk to setup an online consultation.

From the researcher’s point of view, in some cases collecting and processing or analysing new data may be more difficult than it usually is, and in many cases impossible without access to lab equipment or direct contact with research subjects. So why not turn your attention to other elements of RDM, such as preparing older data for deposit, and linking it with your published research papers to fortify the scholarly record?

What can you do?

  • Use the time away from the lab or the field to tidy up data you’ve already collected or created (and don’t forget to attach metadata/contextual information!);
  • Deposit completed data in DataShare (or a disciplinary repository, with metadata recorded in Pure);
  • If you have deposited in DataShare before, check the usage stats and AltMetrics feed to see whether it has been used by others;
  • Create an ORCID (unique, persistent global researcher’s ID), and link it with your Pure account to ensure you stay linked with your outputs throughout your career;
  • Invite us to comment on your DMP, or get in touch about anything else RDM-related;
  • Let us know if you’d like to arrange any bespoke training or awareness-raising sessions;
  • Take some or all of the MANTRA course and let us know if you have any comments.

Martin Donnelly
Research Data Support Manager
Library and University Collections

A visit from the data jungle: My internship in research data management

This is a guest post from Dr. Tamar Israeli, who completed a work/study internship with the Research Data Support team last Autumn. A link to her report is available below.

Recently, there has been a rumor in Israel that research data should be managed. As a librarian and information specialist working in an academic institution, I decided to check if this was true.

When looking for a place for an internship on the role of the library in research data management (RDM), I was happy to find out that the University of Edinburgh RDM support team has a good reputation. I remember enjoying very much my visit to Edinburgh 30 years ago so I was very happy to get Robin Rice & Martin Donnelly’s kind invitation so I could boldly go where… I had already been before.

During September 2019, I worked with the RDM support team, attended some of the staff meetings and participated in one of the RDM trainings.  As part of my internship we carried out a small scale study. The purpose of the study was mainly to understand what are the barriers that prevent researchers from using tools and services provided to them by the university when collaborating with data.

For that purpose, I interviewed six researchers from different schools and disciplines. The researchers were open and cooperative and the interviews were very interesting and insightful. If you’d like to learn about the way researchers collaborate and what influences their decision to use a particular tool or service, here is a link to our report: http://dx.doi.org/10.7488/era/2

Many thanks to the support team for their invitation and warm hospitality. It was one of the most pleasant months of my life.

Tamar Israeli
Librarian and information specialist
Western Galilee College