Because good research needs good data

Our Consultancy Work at SnT - Interdisciplinary Centre for Security, Reliability and Trust

In this blogpost, DCC Research Data Specialist Ryan O'Connor gives an overview of the work the DCC has done over the last year on behalf of a University of Luxembourg research centre

Ryan O'Connor | 16 December 2022

Consultancy is one of the core services that DCC offers. We assist organisations in the creation of data management policies, the evaluation of existing data management procedures and data assets, and we support those in their journey to making data more Open and FAIR.

In my time at the DCC, I’ve been able to devote effort to different projects as part of our consultancy services, getting the chance to learn about how different organisations curate their data and how researchers in a wide range of disciplines approach data management on a day-to-day basis. The most recent project I worked on was for the SnT - Interdisciplinary Centre for Security, Reliability and Trust based at the University of Luxembourg. Research at the SnT centres on information and communication technology (ICT). The centre is home to 17 research groups with specific focuses on cybersecurity, space systems, fintech, and Internet of Things and autonomous vehicles, among others. One thing that distinguishes the SnT’s work, especially in comparison to other organisations of similar size that we have worked with before, is the emphasis on translating research results into intellectual property and real-world innovation. This is carried out through its Partnership Programme and Technology Transfer Office, with collaborations with external organisations - industrial and public sector - resulting in a number of spin-off companies and new technologies.

Initial preparation

SnT approached us here at the DCC in the first half of 2021, interested in engaging our consultancy service. Part of the motivation for this was that the Luxembourg National Research Fund (FNR) was implementing a new policy on Research Data Management which required all funded research to abide for data management best practices - producing data management plans, adhering to the FAIR principles, and committing to long-term preservation of data. Another part of the motivation for contacting DCC was the general recognition amongst researchers and staff at SnT of the need for developing RDM practices at the centre.

After some initial discussions, it was decided that the work DCC would carry out on SnT’s behalf would consist of three main pillars of activity: developing an RDM policy, carrying out a Gap Analysis of existing RDM services, and providing training and awareness raising to promote the RDM policy. Following initial discussions led by DCC’s former Consultancy Lead, Thordis Sveinsdottir, I took over as the DCC lead on this work, liaising on the SnT side with Dr Carlo Duprel, Head of Technology Transfer and Partnerships, Pierre Fuhrer, Deputy Head of Office, and Jonathan England, then a Librarian Specialist in Scholarly Communication and Research Process at the University of Luxembourg Library.

The first stage of the work was to gain a better understanding of how researchers and research support staff at SnT and the wider University of Luxembourg approach research data management - what their motivations were, what services or tools they used, and where they felt support would be of benefit. What linked each of the dozen or so people I spoke to was an appreciation of the value that an centre-level policy could have in bringing a level of coherence to the various approaches to RDM in operation at SnT. Though researchers, in particular, displayed good instincts when it came to managing data, there was a recognition that more focused support would be needed when it came to fulfilling the mandates of funders like FNR and Horizon Europe.

Our work

The RDM policy was drawn up based on these interviews - this initial information-gathering phase also included desk research on University of Luxembourg and funder policies to identify most salient aspects relevant for SnT research. We were conscious not to overburden researchers and other actors with a large amount of tasks or responsibilities that they may be unequipped to deal with; rather, the focus was on keeping these down to the essential tasks necessary for good data management, aligning with existing approaches. The policy also took into account the specific nature of the research conducted at SnT with the centre’s external partners, with the RDM expectations in the policy complementing the valorisation of research results.

The Gap Analysis we carried out for SnT was structured mainly around the DCC’s Research Infrastructure Self-Evaluation (RISE) framework, supplemented with the Australian National Data Service's ‘Checklist for assessing IT Infrastructure capability for Data Management’. In this activity, we evaluated 23 capabilities; for each we summarised the level SnT was at, made recommended actions where necessary, outlined what stakeholder(s) would be responsible for each, and set out priority levels and timelines. The implementation advice we provided here was rooted in the DCC’s experience of carrying out similar exercises for other organisations. As those of you who have operated in this area will know, there is rarely a ‘magic bullet’ solution to developing services - rather, improving the RDM service offering in an organisation is an ongoing, collaborative effort. The more people that can be brought along on this journey, from postgraduate students to senior professors, the better the chance of a successful implementation of a service.

The final activities for this project were to present the policy to senior researchers and managers at SnT and to provide training to all target stakeholders on the skills needed to fulfil the expectations outlined in the RDM policy. The latter of these took place online over four sessions in October, where I was joined by my colleagues Joy Davidson and Dominique Green in facilitating the presentations and practical exercises, while the former was a brief presentation I gave back in July of this year. As with all our training activities, we tailored the material to suit the audience. In cases where there is more of tradition of data management and open research, it is easier to find examples of good practice compared to domains where uptake for data management practices is at a more nascent stage; in these cases the focus is more on making the case for the benefits of RDM and providing participants with the motivation to pursue it in their own work.

Ongoing institutional engagements

This project took place approximately 10 years after the DCC’s Institutional Engagement programme, which provided support for digital preservation and data management to 20 universities in the UK. As RDM practices and methods have evolved in that time, so have our methods of helping organisations develop their capabilities (well, so as I’ve been told, the Institutional Engagement programme long pre-dating my arrival here!) and the media through which we can deliver our support. What is positive to see is that researchers and support staff are still so motivated to adapt RDM practices to their specific areas of expertise.