Research Data Management (RDM) has become a major issue for universities over the last decade. This case study outlines the review of RDM services carried out at the University of Oxford in partnership with external consultants between November 2019 and November 2020. It aims to describe and discuss the processes in undertaking a university-wide review of services supporting RDM and developing a future road map for them, with a strong emphasis on the design processes, methodological approaches and infographics used. The future road map developed is a live document, which the consulting team handed over to the University at the end of the consultation process. It provides a suggested RDM action plan for the University that will continue to evolve and be iterated in the light of additional internal costings, available resources and reprioritization in the budget cycle for each academic year. It is hoped that the contents of this case study will be useful to other research-intensive universities with an interest in developing and planning RDM services to support their researchers.
Research data management (RDM) refers to the ways in which researchers organize, structure, store and care for the information used or generated as they carry out their research.1 Recognition of the important issues surrounding RDM has grown over the last decade, and RDM has been described as a ‘wicked’ problem2: it requires a wide range of skills and technologies, alongside collaboration and understanding across significantly different stakeholder groups.
Discussions about RDM have become increasingly important not only because data is growing rapidly in volume and complexity,3 but also due to regulatory requirements concerning data protection (e.g. the GDPR).4 Data is increasingly viewed as a critical asset for universities, and recent hacking attempts have brought institutional RDM provision to the public’s attention.5 At the same time, major research funders have developed policy requirements around RDM,6 and good data handling practices are essential for access to key datasets from partners in government, the National Health Service and industry. At the other end of the research process, data sharing plays a key role and touches on many of the above considerations: the State of Open Data 2020 report notes that, ‘over the past five years, the science ecosystem of researchers, librarians, publishers, institutions, funders, and others have embraced improving data sharing’ in the context of broader open science policies.7
It is, therefore, clear that today’s research performing organizations would struggle to deliver research to the highest standard without appropriate investment in RDM services and support. The Covid-19 pandemic has focussed attention even further on the importance of research data and software, as the ways research is carried out have been revolutionized: a large portion of academics and researchers are working from home, and the impact of cutting-edge research on people’s everyday lives is more apparent than ever.8 Institutional services and support had to adapt, too, to mirror the changing landscape of practices, ‘data professionals in academic libraries sprang into action to help. They shared resources, developed workshops, helped find alternative methods of carrying out research, and found ways of coping with the influx of Covid-related data.’9
Generally speaking, RDM is supported by digital infrastructures of varying sophistication, from standard hard drives to integrated cloud solutions.10 The FAIR (Findability, Accessibility, Interoperability and Reusability) data principles have been increasingly acting as a useful focal point to assess the maturity of research data infrastructures and have been recently described as a tool to help build campus infrastructure and change culture.11
This case study seeks to describe the review of RDM services designed and carried out at the University of Oxford in partnership with external consultants between November 2019 and November 2020.
Direct support for RDM at the University of Oxford operates at multiple levels, with researchers’ own efforts being supported (i) at the local level by their departments or institutes and divisions; or (ii) centrally by the Bodleian Libraries, IT Services and Research Services, where the Oxford-based authors of the present article are based. RDM activities are critical to enabling the quality, reproducibility and transparency of Oxford’s world-leading research, and this is reflected in Oxford’s 2018–2023 Strategic Plan12 priorities and in the University’s IT Strategic Plan 2019–2024.
In 2018, the Bodleian Libraries, IT Services and Research Services carried out an internal scoping exercise to gather preliminary information regarding current service provision and potential gaps for RDM delivery across the University. The exercise stemmed from a recognition that evolving funder mandates, including an increased emphasis on open scholarship in the UK’s research excellence framework (REF), were likely to place increasing demands on RDM support services over time.
The scoping exercise made clear that RDM was a cross-cutting issue that required input from multiple institutional support services, and that there were areas of potential overlap and duplication between these services, as well as some gaps in existing provision. The results of this exercise were summarized in a briefing paper, which informed an internal funding bid for independent consultants to undertake a more in-depth review. The aims of the review were to:
Following the preparation of the internal briefing paper, a detailed Request for Information (RFI) document was drafted in consultation with multiple stakeholders across the University. The Request for Information was issued by the University in February 2019, and the objectives of this RFI process were to:
The RFI was followed by interviews with consultancy providers. A partnership led by Research Consulting was selected as the preferred supplier, with technical lead on RDM from Charles Beagrie Ltd and on university libraries from Tracey Clarke Consulting. Such a partnership appeared to be optimal for addressing the desired scope of work, as it included experts in all the key areas of focus identified in the RFI.
The RDM review focussed on Oxford’s divisions and central provision of RDM services. In addition, the review sought to compare Oxford’s current practices in the domain of RDM with those of national and international peers. It considered national and international best practices and guidance in RDM (including the FAIR Principles),13 external approaches to charging models and recent policies and reports on RDM. A benchmarking cost survey by the Russell Universities Group IT Directors forum (to the planning of which Research Consulting and the University of Oxford have contributed) was delayed by the Covid-19 pandemic, and its findings, which were expected in 2021, could not be incorporated into the report.
To inform the preparation of a concise report and road map, the scope of work was structured around five pillars (Figure 1), which were developed in close collaboration with the University during a project scoping phase (Figure 2). Particularly, the review used the five pillars as a tool to organize and rationalize the evidence assembled, analyse the findings and summarize the actions required to meet the University’s strategic objectives.
Although the topics and areas investigated in this review were specific to the University of Oxford and relevant at a given point in time, we believe that the overarching five pillar framework developed will be more broadly applicable to other higher education institutions seeking to review their provision of RDM services.
The review was delivered as a multi-stakeholder consultation, including an online survey, interviews, focus groups and workshops (Figure 2): a total of 237 University stakeholders across the academic divisions and central services contributed to this work.
Three key milestones were included in the project plan to allow for scheduled deliberation time: University stakeholders at different levels of seniority and from different organizational units were given the chance to engage directly with emerging issues and to consider the draft outputs.
We note that this review took place during the Covid-19 pandemic. Although the project started via in-person engagement in late 2019, all subsequent engagement activities (interviews, focus groups, workshops) were delivered online using tools such as Zoom, Microsoft Teams and Mentimeter. The impact of online delivery was minimal, and project participants were able to engage effectively with the consulting team via digital tools. However, some activities had to be rearranged or rescheduled to allow for the engagement of key stakeholders who were orchestrating responses to the pandemic.
As the RDM review took shape, the breadth and depth of RDM activities carried out at Oxford quickly became apparent: the review needed to acknowledge an extremely multi-faceted and diverse community, engaging different management levels, committees, sub-committees and working groups with either primary or tangential responsibilities about RDM.
As a result of this complexity, the RDM review had to employ different tools to engage different audiences (Figure 2), as follows:
To facilitate the interactions between these stakeholder groups and the consulting team, the University appointed a project co-ordinating group, which included representatives of the Bodleian Libraries, IT Services and Research Services. The co-ordinating group acted as the first point of contact for the consulting team and received fortnightly progress updates to monitor the status of the review.
The review sought to develop actionable insights for the University. Therefore, it was essential to allow sufficient time to secure organizational buy-in for the findings and recommendations arising, and to identify and involve appropriate owners at both senior committee and operational levels.
To facilitate this, the University engaged a range of senior decision makers in the review:
These individuals and groups were engaged particularly around project milestones (Figure 2), but the Governing Board was engaged more regularly to ensure representation of the concerns of individual academic divisions.
The range of activities in the domain of RDM requires cross-service and cross-organizational working. This, combined with the range of RDM services and projects carried out in a very large research-intensive university such as Oxford, means that orchestrating resources and RDM efforts across the University, and maintaining awareness of them amongst an ever-changing academic community, is an inevitable challenge.
A mapping of RDM services was a key deliverable from the review. Our aim in preparing this was to develop an infographic (Figure 3) that could easily convey:
The mapping was based on services and projects mentioned in the survey or individual or group interviews, so it did not showcase the complete universe of services – particularly local or external services. Services were analysed and mapped into five life cycle/activity sectors (Active Data, Semi-active/Living Data, Archived Data, Catalogues and Registries, Advice, Guidance, Consultancy), and zoned as central (university-wide services provided centrally by the Bodleian Libraries, IT Services, or Research Services), local (services provided at divisional, departmental, institute or team level), or external. Services bridging more than one zone were shown on the boundaries.
Note that some services shown in Figure 3 may also be used for other purposes not identified by interviewees.
Definitions used in the study and mapping of services were as follows. ‘Archived Data’ covered both medium-term retention (i.e. beyond the life of project funding but not permanent retention) and preservation and access for the long term (potentially permanent, e.g. in the Bodleian). For ‘Semi-active/Living Data’ we noted there is no widely accepted terminology for this type of data, which is often very long-lived and worked on intermittently by individual scholars or research groups. Our working definition was ‘used data currently held for possible future re-use or further development’, e.g. corpora or databases between periods of grant funding or unfunded. ‘Active Data’ was used in its conventional sense of data in its first phase of being generated and analysed by researchers.
As the project gave rise to a complex set of information, the consulting team carried out thematic coding via NVivo to summarize and prioritize findings.14 The coding of findings was complemented by a series of workshops within the consulting team, where information pertaining to different areas of the University (e.g. academic community, Libraries, IT Services, Research Services) could be effectively rationalized and transferred between team members. The output of this process was the creation of a coherent longlist of recommendations (used as a way to organize actions by theme or area) and specific actions that could support the University’s ambition with regard to RDM. Recommendations were mapped (Figure 4) to the five pillars in Figure 1 to ensure that all strategic concerns identified at project inception had been addressed.
The development of a prioritized shortlist of actions under each recommendation was informed by the identification of underlying key issues and requirements. The benefits, impact and feasibility of emerging actions in terms of costs, dependencies and timescales were also assessed. This approach helped the consulting team build the grading matrix shown in Table 1, which underpinned the preparation of the project road map.
|Green||Actions that deliver operational improvements or efficiencies. These can be largely delivered within existing resources, or the necessary funding has already been secured.|
|Amber||Actions that contribute to achievement of the University’s strategic priorities or enhance the quality of research. Some additional investment and/or changes to institutional governance processes may be required.|
|Red||Actions that directly support achievement of the University’s strategic priorities or address strategic risks. Additional investment and/or changes to institutional governance arrangements are required.|
The findings of the RDM review were used to inform the preparation of a future road map. This was created as a dynamic working document in spreadsheet form (Table 2) and, once validated, it was turned into an infographic for internal dissemination within the University (Figure 5).
|Recommendation #||Number of the recommendation||1, 2, 3, …|
|Recommendation||High-level recommendation||Text (see Figure 4 for examples)|
|Action #||Number of the action grouped under a recommendation||1.1, 1.2, 2.1…|
|Action||Specific action grouped under a recommendation||Text|
|Oversight responsibility||Individual responsible for overseeing the implementation of the action (e.g. Chair of committee)||Text|
|Primary responsibility for implementation||Individual(s) or group primarily responsible for implementing the action||Text|
|Additional responsibility for implementation||Other individual(s) or group responsible for implementing the action||Text|
|Cost||Estimated cost of the action, if available||Currency or
|Type of cost||Likely type of cost arising from the action||Category (e.g. recurring staff costs, project staff, infrastructure and service provision)|
|Time frame||Time frame for the implementation of the action||Category (Short/Medium/Long term)|
|Priority||Priority of the action, based on the outcome of the review||Category (Low/Medium/High)|
|Implementation mechanisms||Specific implementation mechanisms, if known (e.g. ongoing project, new role within the University)||Text|
|Notes||Any other notes or details that cannot be captured in structured form||Text|
The following considerations played a key role in the preparation of the road map:
The infographic in Figure 4 represents a snapshot of the road map at a given point in time and caters to decision makers who may not need detailed information at the action level but do require a clear view of the proposed strategic priorities. Notably, Figure 4 includes a significant amount of contextual management information: actions are grouped by recommendation and time frame, red/amber/green (RAG) colour-coding is used to indicate the priority of actions (based on the gradings in Table 1) and an icon communicates whether actions require investment. In addition, Figure 4 is part of a two-page infographic, where the second page (not shared for reasons of confidentiality) provides a list of all numbered actions and acts as a legend.
As noted above, the project’s findings and road map were discussed and validated at various points throughout the review. However, the final validation and socialization stage was key to ensuring the future implementation of the road map: it allowed the consulting team to gather feedback from the stakeholder groups responsible for implementing and financing the recommendations and actions arising from the review.
Focus groups with senior University leaders, including the top administrators in IT Services, Research Services and Libraries were used to achieve the above. These meetings also allowed the consulting team to finesse the messages and language of the report to ensure it would speak to both the academic community and central and divisional support services. Some changes were made in response to the focus group findings, including an increased focus on the budgetary and resourcing implications of the road map and associated recommendations in their final form.
The report and road map in final form were presented by the consulting team to the Research Information Management and Technology Sub-Committee and to the Curators of the University Libraries. They were then taken over by the University for further discussion and implementation.
The road map provides a recommended RDM action plan for the University that will continue to evolve and be iterated in the light of additional internal costings, available resourcing and reprioritization.
At present, the road map is owned by the University’s Research Information Management and Technology Sub-Committee, who have commissioned an RDM review Task and Finish group to develop a costed business case for a programme of work to implement the road map. In order for the original aims of the review to be realized, it is seen as important to maintain a coherent programme with a clear narrative and sense of strategic direction.
Academic awareness and engagement are essential to the success of the road map. The Task and Finish group members have made a concerted effort to ‘socialize’ the review outcomes at a broad range of committee meetings, and to link up with local expert research groups such as Reproducible Research Oxford and FAIRsharing.
A key area of the review will be focussed on joining up services in alignment with the research data life cycle and developing local repository offerings in a manner that facilitates this. The RDM landscape at Oxford is complex – but this should prove to be one of its greatest strengths.
Reflecting on the review process, we would make the following recommendations to other institutions seeking to enhance their support for research data management:
The authors would like to thank all project contributors who completed our online survey and/or participated in interviews, focus groups and workshops. In addition, we are grateful to all members of the project’s Governing Board for their insightful comments and guidance. Finally, we thank other members of the consulting team for their important contribution to this process, including Daphne Charles, Tracey Clarke and Lucia Loffreda.
A list of the abbreviations and acronyms used in this and other Insights articles can be accessed here – click on the URL below and then select the ‘full list of industry A&As’ link: http://www.uksg.org/publications#aa.
Neil Beagrie, Andrea Chiarelli and Rob Johnson completed paid consultancy work for the University of Oxford as part of the project described in this study. Rob Johnson is a trustee of UKSG. All other authors have declared no competing interests.
“Research Data Oxford – About RDM,” The University of Oxford, https://web.archive.org/web/20210215163407/https://researchdata.ox.ac.uk/home/introduction-to-rdm/ (accessed 11 January 2022).
Andrew M. Cox, Stephen Pinfield, and Jennifer Smith, “Moving a Brick Building: UK Libraries Coping with Research Data Management as a ‘wicked’ Problem,” Journal of Librarianship and Information Science 48, no. 1 (May 15, 2014): 3–17, DOI: https://doi.org/10.1177/0961000614533717 (accessed 11 January 2022).
David Martinsen, “Primary Research Data and Scholarly Communication,” Chemistry International 39, no. 3 (May 24, 2017): 35–38, DOI: https://doi.org/10.1515/ci-2017-0309 (accessed 11 January 2022).
Miranda Mourby et al., “Governance of Academic Research Data Under the GDPR – lessons from the UK,” International Data Privacy Law 9, no. 3 (July 15, 2019): 192–206, DOI: https://doi.org/10.1093/idpl/ipz010 (accessed 11 January 2022).
Joe Tidy, “Blackbaud hack: More UK universities confirm breach,” BBC News, July 24, 2020, https://www.bbc.com/news/technology-53528329 (accessed 11 January 2022).
Rosie Higman and Stephen Pinfield, “Research Data Management and Openness,” Edited by Dr Andrew Cox, Program: Electronic Library and Information Systems 49, no. 4 (September 1, 2015): 364–381, DOI: https://doi.org/10.1108/PROG-01-2015-0005 (accessed 11 January 2022).
Digital Science et al., “The State of Open Data 2020,” December 2020, DOI: https://doi.org/10.6084/m9.figshare.13227875.v2 (accessed 11 January 2022).
Mattia Fosci et al., “Emerging from uncertainty: International perspectives on the impact of COVID-19 on university research,” November 2020, DOI: https://doi.org/10.6084/m9.figshare.13130063.v3 (accessed 11 January 2022).
Alexandra Cooper et al., “Data in the Time of COVID-19: How Data Library Professionals Helped Combat the Pandemic,” Partnership: The Canadian Journal of Library and Information Practice and Research. University of Guelph 16, no. 1 (2021) DOI: https://doi.org/10.21083/partnership.v16i1.6462 (accessed 11 January 2022).
Christoph Wulf et al., “A Unified Research Data Infrastructure for Catalysis Research – Challenges and Concepts,” ChemCatChem 13, no. 14 (March 10, 2021): 3223–3236, DOI: https://doi.org/10.1002/cctc.202001974 (accessed 11 January 2022).
Danuta A. Nitecki and Adi Alter, “Leading FAIR Adoption Across the Institution: A Collaboration Between an Academic Library and a Technology Provider,” Data Science Journal 20, no. 1 (2021): 6, DOI: https://doi.org/10.5334/dsj-2021-006 (accessed 11 January 2022).
“University of Oxford Strategic Plan 2018–23,” The University of Oxford, https://web.archive.org/web/20201219140714/https:/www.ox.ac.uk/sites/files/oxford/field/field_document/Strategic%20Plan%202018-23.pdf/ (accessed 11 January 2022).
Mark D. Wilkinson et al., “The FAIR Guiding Principles for Scientific Data Management and Stewardship,” Scientific Data 3, no. 1 (March 15, 2016), DOI: https://doi.org/10.1038/sdata.2016.18 (accessed 11 January 2022).
Virginia Braun and Victoria Clarke, “Using Thematic Analysis in Psychology,” Qualitative Research in Psychology 3, no. 2 (2018): 77–101, DOI: https://doi.org/10.1191/1478088706qp063oa