Open Research Support at Russell Group Universities

As part of my work as Research Data Steward, I was asked by our Open Research Co-ordinator to investigate the open research support available at Russell Group universities and how the University of Edinburgh compares.[1] Open research, which is also known as “open science” or “open scholarship”, refers to a collection of practices and principles around transparency, reproducibility and integrity in research. To understand to what extent Russell Group universities have adapted to the ongoing development of open science, we have conducted analysis in terms of four areas. Do they have a published policy around Open Research? Do they have an Open Research Roadmap? Do they mention any training or specific support for researchers in achieving Open Research? What services do they provide to support Open Research?

Firstly, we checked whether those universities have a policy/statement that outlines the university’s approach to support open research and key principles for researchers. Less than 30% of these universities have a clear policy or statement for Open Research. Good examples include the University of Cambridge,[2] University of Sheffield,[3] and Cardiff University.[4]

Secondly, we checked whether they have a Roadmap that provides a set of questions that universities can use to monitor their progress in implementing Open Science principles, practices and policies at a local level. Among the Russell Group members, University of Edinburgh and University College London – two members of the League of European Research Universities (LERU) [5] provide a roadmap/page dedicated to monitor their progress. (Ours can be found on this Open Research page.)

Facets of open researchThirdly,what services are provided to researchers to make their work public? Most universities provide support like a data repository (except for LSE), Research Data Management support, Open Access to publications and thesis and guidance on sharing research software. A few provide support on protocols sharing. Some universities have started hosting an open research conference. For example, UCL Open Science Conference 2021, 2022,[6] Open Research Symposium hosted by the University of Southampton,[7] and University Open Research Conference, June 2021, at the University of Birmingham.[8] As an active member of LERU, our university also joined in to launch our first Edinburgh Open Research Conference in May, 2022.

Lastly, we have found all universities have training relevant to open research, with around half of them clearly advertising their training. Some good examples which we could learn from include the “Open Research education for doctoral students” from Imperial College[9]  and a practical libguide for open research provided by the University of York[10].

We are glad to see that Russell Group members have started adopting actions to support Open research, which is considered part of the new normal for research-intensive universities. However, this is a long and ongoing process. We have seen that many universities are still in the early stages of the implementation process and more can be done to advance their practice, including ours.

Yue Gu
Research Data Steward

Footnotes
[1] https://russellgroup.ac.uk/about/our-universities/
[2] https://osc.cam.ac.uk/open-research-position-statement
[3] https://www.sheffield.ac.uk/openresearch/university-statement-open-research
[4] https://www.cardiff.ac.uk/documents/2519297-open-research-position-statement
[5] https://www.leru.org/publications/implementing-open-science
[6] See the UCL Blog post for more information. https://blogs.ucl.ac.uk/open-access/2022/03/15/bookings-now-open-for-ucl-open-science-conference-2022/
[7] https://library.soton.ac.uk/openaccess/Plan_S_open_research_symposium
[8] See https://intranet.birmingham.ac.uk/as/libraryservices/library/research/open-research.aspx
[9] https://www.imperial.ac.uk/research-and-innovation/support-for-staff/scholarly-communication/open-research/open-research-education/
[10] https://subjectguides.york.ac.uk/openresearch/home

Data Mindfulness – learning the basics of good research data management

When planning a research project, whether this involves carrying out interviews for a first dissertation project or analysing secondary data for a PhD, it is important to ensure that you are handling your research data safely and effectively. Taking time to think about where and how you will store and organise your files, how your data can be backed up to protect against accidentally losing your work, and what to consider if working with sensitive information, will help make the research process simpler and help you become a better researcher.

The Research Data Service provide a range of training materials to help both new and experienced researchers to work with their research data more effectively. For students planning a dissertation project we have developed the online Data Mindfulness: Making the most of your dissertation data course (available as part of the Library’s LibSmart II course). This short introductory course is designed to be accessible and engaging, and incorporates videos, quizzes and reading materials to provide helpful tips and guidance for those preparing to undertake their first dissertation project.

Data Mindfulness is available online as part of the library’s LibSmart II research skills course

We are happy to share some of the positive feedback we have received from students who recently completed the Data Mindfulness course:

“It was clear and easily accessible, especially for someone who is an online student”

“A lot of information that I had no idea about but feel better having received it”

“It provides useful tips about organizing and storing data and files”

“Every SSPS student should be aware that they have access to this course before starting their dissertation”

For post-graduate students and those with previous experience working with research data we recommend checking out MANTRA, our well-established online training course which provides more in-depth training on key research data management topics.

Dr Bob Sanders
L&UC Research Data Support

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

Two new Quick Guides for good Research Data Management

The Research Data Support team have recently published two new Quick Guides, the latest in a series of short, user-friendly documents intended to help our research staff and students plan, manage and preserve their data effectively, safely, and for the long-term.

Quick Guide 5 takes the topic of “Open Research” – also known as Open Science, particularly in a European context. The drive towards research transparency and the removal of barriers to accessibility has gathered a great deal of momentum over recent years, to the extent that “Open by default” is an increasingly common approach. Open research enables scientific findings to be tested, reproduced and built upon far more quickly than traditional approaches allowed. The benefits of Open Research are being demonstrated in real time, right in front of our noses, as researchers at Edinburgh tackle various aspects of the Covid-19 pandemic. We recently tweeted about one such project which examined the effectiveness of face coverings in reducing the range travelled by breath, which of course helps transmit the virus. The data underpinning this research is freely available to everyone via Edinburgh DataShare.

The latest Quick Guide, the sixth in the series, addresses the ‘FAIR’ principles, which state that research data should – so far as possible, and appropriate – be Findable, Accessible, Interoperable and Reusable. These principles emphasise machine-actionability (i.e. the ability of automated computational systems to find, access, interoperate, and reuse data with minimal or no human intervention) as humans increasingly rely on computational means to discover and work with data as a result of the increase in volume, complexity, and creation speed of data.

These two new publications join our existing guidance on topics such as the basics of Research Data Management (RDM), RDM and data protection, and research data storage options at the University. Future topics planned include conducting research safely online, FAIR approaches to research software, and an overview of the systems and services available at Edinburgh in support of Open Research. If there is a particular topic you would find useful, please get in touch with us via data-support@ed.ac.uk or the IS Helpline.

All of our Quick Guides can be found at https://www.ed.ac.uk/information-services/research-support/research-data-service/guidance

Martin Donnelly
Research Data Support Manager
Library and University Collections