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How FAIRsharing enables professional services to assist Oxford researchers: completed, ongoing and planned activities

The widespread requirement to make data findable, accessible, interoperable and reusable (according to the FAIR Principles) means we must better prepare at local level to assist Oxford researchers to enable FAIR in practice, e.g. by automating guidance, improving tools and services, and enhancing education. The need is clear, both in the context of defining good Research Practices at organizational level, and to respond to funders requirements, as exemplified in the upcoming pan-UKRI research data policy framework, which has FAIR at the core of its Research Data Management (RDM) requirements.

In this blog, the professional staff from across the University who are also FAIRsharing Community Champions, summarise the collaborative initial work done to connect FAIRsharing, as a service and an educational resource,at local level. They also elaborate on the additional work needed on and around FAIRsharing to better support Oxford researchers in delivering FAIR in practice. 

In addition, two of the Champions bring their view as individual researchers, explaining how this role has helped in their work.

  • David Tomkins, Curator, FAIRsharing, Oxford e-Research Centre
  • Timothee Aubourg, Senior Data Scientist, Nuffield Department of Clinical Neurosciences

The Oxford Research Archive (ORA)

Jason Partridge, FAIRsharing Community Champion

The Oxford University Research Archive (ORA) is the institutional repository for the University of Oxford; it collects, preserves, and shares a variety of digital research objects created by the University’s collegiate members, and is managed on behalf of the University of Oxford by the Bodleian Libraries. The collaboration between FAIRsharing and ORA began in 2017 with the registering of FAIRsharing’s DOIs via the Libraries’ DOI service. ORA also supports FAIRsharing with its preservation and disaster recovery plan (see: FAIRsharing – ORA – Oxford University Research Archive and FAIRsharing’s Sustainability and Preservation Plan). With this strong foundation, the two resources are now strengthening their connections to jointly contribute to training and educational material provided by ORA to Oxford researchers. 

Oxford students and researchers are creating a wide variety of research digital objects and depositing them in ORA, including standards, databases, and policies as well as datasets, software, and documentation. For these objects, we are encouraging the creation of FAIRsharing records, and advocating the benefits of these registrations (i.e. to maximise sharing and discoverability) in talks and in discussions with Oxford researchers, groups, and communities. We are discussing how to develop documentation that will describe how to link to FAIRsharing content within ORA metadata and also how to register any relevant resources held by ORA within FAIRsharing. There are a number of locations where such jointly-created guidance could be useful:

  • within role-specific factsheets and educational material for e.g. students depositing theses and researchers depositing data, and
  • within ORA webpages or LibGuides, where details of how FAIRsharing and ORA interact could be provided.

We are looking to further develop this collaboration to undertake a FAIR assessment of ORA content. The ideal scenario would be for ORA to leverage the work FAIRsharing is undertaking within the FAIR Assessment Framework to specify how FAIRness could be assisted within ORA. Part of a project of the European Open Science Cloud (EOSC), which aims to develop a ‘Web of FAIR Data and services’ for science in Europe, this framework will involve the creation of a reusable set of benchmarks and metrics that specify the particular ways in which the FAIRness of ORA content can be improved upon and tested. While designed to fit ORA digital objects and needs, these FAIRness benchmarks and metrics would likely have a much wider impact, being applicable to other institutional repositories, establishing Oxford leadership in this area. Assessing the FAIRness of content within ORA is intended to support and improve sharing of FAIRer research digital objects, as required by funders and publishers, but broadly also to support the impact measures of the research content being shared.

The Sustainable Digital Scholarship (SDS) Service

Mark McKerracher, FAIRsharing Community Champion for RDM

Alexandra Rooney, FAIRsharing Community Champion for RDM

Catherine Conisbee, FAIRsharing Community Champion for RDM

The Sustainable Digital Scholarship (SDS) service is one of the Bodleian Libraries’ RDM services, supporting researchers and projects across the University to store, publish, and sustain their research data outputs. The SDS service places FAIR Principles at the heart of everything we do, providing the online SDS platform that aligns with FAIR principles for hosting Oxford research data of all kinds. While based in the Bodleian, we work with researchers from all disciplines, providing tailored support to meet their diverse needs, offering face-to-face consultations for research at all stages—from the initial planning of grant applications to the final wrapping-up of project data.

These advisory sessions are complemented by a growing library of self-help videos, including a video on FAIR and featuring FAIRsharing. SDS not only provides advice on the SDS platform, but also the wider RDM ecosystem within Oxford, and beyond Oxford, especially where researchers have partners in other institutions or are themselves moving between institutions.

The SDS team is committed to supporting researchers in navigating the expanding RDM landscape to find the resources that best suit their needs. As part of this, we increasingly signpost researchers to FAIRsharing as a resource for standards, repositories, and services. Given the growing complexity of research data management, directing researchers to FAIRsharing as a comprehensive reference point supports our goal of promoting FAIR principles while ensuring that they can access the most relevant guidance for their specific disciplines and projects.

Research Data Oxford (RDO)

Laurence Brown, FAIRsharing Community Champion for Circadian Biology and RDM

Tim Gamble-Turner, FAIRsharing Community Champion for Research Technology

Meriel Patrick, Research Technology Specialist, IT Services Research Support Team

Research Data Oxford (RDO, https://researchdata.ox.ac.uk/) is a cross-departmental group providing support for all aspects of research data management, and developing and delivering RDM infrastructure and services. We are currently collaborating with FAIRsharing to integrate FAIRsharing content within the RDO website as relates to policy, standard, and database advice. FAIRsharing helps us by providing valuable content that we plan to use within induction materials for all new researchers (students and staff). Including information about how FAIRsharing can help enable FAIR within the Oxford research community is a valuable tool in creating change in RDM practices. Divisional-level resources are the ones most likely to be delivered first (in Oxford there are four academic divisions, versus in excess of 60 academic departments, institutes, and research centres). FAIRsharing content and service features are core to the creation of this material, as well as to creating and maintaining greater links among us, the professional services (centrally, as well as at division level, and beyond) and the team behind FAIRsharing.

The next phase of this collaboration between RDO and FAIRsharing plans to investigate how to (semi)automate and scale the guidance to researchers to enable FAIR and good RDM practices. In particular, collaboratively we want to investigate the use of Large Language Models (LLMs) and Artificial Intelligence (AI) helpers, e.g. to (i) make it easier for the research community to find the standards, databases and policies they need; and (ii) provide filtered FAIRsharing content (alongside other RDO  information) for services supporting live and archival data. Use of GenAI and LLMs on FAIRsharing and RDO content hold the potential to automate recommendations to researchers (e.g. recommending the appropriate repository and related standards for their Data Management Plans (DMPs). If realised, ultimately the benefits to the researchers (and we who assist them) will be measurable in terms of speed, precision and clarity of responses.

Similarly, long-term support from Oxford will allow our collaboration to focus also on delivering decision pathways for FAIR RDM, by improving and expanding on existing services, such as the FAIRsharing Assistant, a decision tree system that can be tailored with the addition of pathways for particular research communities to inform DMP decisions. Furthermore, we could connect such tools with local resources like the Data Pathfinder, improving how we present these services to our researchers. The successful provision of these FAIR RDM decision pathways requires scaling up the collaboration between RDO and FAIRsharing to address a number of technical steps and general considerations. In particular, enabling co-development and realisations of the plans (collectively described in this blog post) will require placing FAIRsharing on an institutionally supported cloud service. Furthermore, it will be essential for us to keep abreast with the fast evolving landscape of research infrastructures, especially outside Oxford, such as those emerging in the EOSC, which FAIRsharing is embedded in.

Individual Perspectives

David Tomkins, FAIRsharing Community Champion for RDM

I am currently enhancing the curation of FAIRsharing’s database registry to provide 100% coverage of each repository’s identifier schemas as well as the type of research object (e.g. data, software, documents) each one stores. This work is invaluable to improving reproducibility and FAIRness within the research community by helping researchers make informed decisions when choosing repositories, and by aiding FAIR assistance and evaluation tools. Furthermore, there is scope for expanding FAIRsharing’s coverage of the University’s extensive digitized collections, particularly those relating to the Arts and Humanities. As noted by the SDS colleagues, at Oxford and  in general, the Humanities community has traditionally been slower than its science-related counterparts to engage with FAIR Principles, not least because of uncertainty about what actually constitutes research data in a Humanities context.  FAIRsharing curators have already instigated preliminary discussions about such expansion with representatives from the University’s Gardens, Libraries and Museums (GLAM) Division, most notably the Bodleian Libraries and the Ashmolean Museum, along with the Research Data Alliance (RDA) ‘Collections as Data’ Interest Group and the RDA FAIRsharing Working Group (WG). Curating GLAM collections accurately within FAIRsharing is a key ongoing area of collaborative development. In GLAM, discrete collections are often hosted and delivered via the same platform as other such collections, even though they are perceived as having a distinct identity and their policies and metadata standards may differ.  FAIRsharing will therefore continue to explore how best to adapt its curatorial practices in order to ensure that the discoverability and visibility of these individual resources can be maximized.

Timothee Aubourg, FAIRsharing Community Champion for Data Science, Experimental Methods and Digital Health

One well-known challenge in reproducible research is the lack of universal standards, compounded by the diverse backgrounds and skill sets of researchers in science-related projects. As software development becomes increasingly integrated into scientific projects, researchers often find themselves balancing both data analysis and software development tasks independently. This independence can make it difficult to adopt consistent best practices, especially in fields where data science methodologies evolve rapidly and interdisciplinary collaboration is common. In this context, the FAIRsharing stands out for its efforts to provide a shared knowledge base of research software policies and standards. A notable example is the collaboration of the RDA FAIRsharing WG with the ReSA/RDA PRO4RS WG, which collects and disseminates institutional policies on research software practices across various institutions and publicly.  As a FAIRsharing Community Champion, I am currently curating the FAIR-enabling attributes of these policies within FAIRsharing. FAIRsharing plays a pivotal role in integrating best practices across research projects, thereby promoting more reproducible workflows across disciplines. Looking ahead, FAIRsharing has the opportunity to expand its impact by leveraging its collected resources to develop materials and guidance for research teams. This could include training materials for students and junior researchers that could help teams more effectively incorporate FAIR Principles into the lifecycle of both software and data analysis projects.