CREDS/UKERC Data Sharing in Energy Consortia workshop

CREDS: Michael Fell, Sarah Higginson, Gesche Huebner and Marina Topouzi

Workshop Facilitation: Mike Colechin

Open, accessible research data has great value. It helps to make science more efficient by allowing researchers to reuse and build on existing data, and makes it easier to spot mistakes in data analysis.

CREDS/UKERC Data Sharing Workshop in Autumn 2023, gathered system stakeholders together to discuss how to improve data sharing in the energy research community. This blog outlines some of the main background and takeaway points, and you can read more in the initial briefing note and detailed workshop report.

The workshop arose out of a collaboration between CREDS and UKERC. CREDS was running a Data Transparency Project which shared tools aimed at promoting transparency, reproducibility and quality (TReQ) in energy research. This included increasing the awareness and knowledge of researchers around data management practices and improving data archiving rates. In UKERC, research data management was identified as an important facet of the project for Phase 4 and the UKERC Energy Data Centre provided guidance and expert support for data management planning, both for projects and UKERC themes, as well as a repository for research data for UKERC researchers.

Publishers, data managers, research centre managers, funders and researchers were invited to the expert workshop to reflect on the lessons learned by CREDS and UKERC, add their own lessons and make a series of recommendations. Three talks set the scene: Rachel Bruce, Head of Open Research at UKRI and lead for the Pan UK Research Policy for Open Access, provided the context for data sharing from a funder perspective. She was followed by Sarah Higginson and Catherine Jones, who spoke about the lessons learned by CREDS and UKERC respectively as they have tried to improve data management practices over the last five years.

The following headline recommendations arose out of the workshop:

• Learn from the data sharing experience of others - make access to data easier, and ensure that methods, tools and guidance for this are available. Energy consortia have a role in setting data sharing expectations and developing/pointing to resources.
• Providing metadata and good quality data indicators takes time. Managing data across multiple institutes, ethics teams and collaboration agreements can be complex. The different disciplinary domains common to energy consortia may have different standards that need to be met. All of these require expertise, attention and resourcing.
• Creating better datasets requires them to be more highly valued. Institutions need to take the value of data more seriously, funding activities effectively, rewarding individuals for taking an active role, and recognising the importance of workload management. Energy consortia should help to set this framework as part of their culture.
• Data Management Plans are an essential starting point and should be in place at the beginning of projects, with appropriate research centre support for creating them. However, to make most effective use of them, they should also be flexible, with appropriate mechanisms in place to reflect and learn as changes occur.
• For large energy research centres in particular, proposals need to budget for a data manager, recognising that this is an important role requiring appropriate remuneration to secure quality personnel.
• Not all data are equal. The skills of the data manager should provide guidance and support to help discriminate between the value of different data sets and prioritise management effort accordingly.
• Skills and knowledge in the area of data management vary widely across the energy community, partly because of the involvement of so many different domains. Training is required to improve researcher awareness of the value of data sharing and to improve their data management skills. Energy consortia can provide/host this training and have a role to play here, emphasising the domain aspects of the data being managed.
• A peer network for data managers would be useful so they could share best practice and identify areas to work on together to embed FAIR data and Open Research practices within researcher’s activities. Building on existing Energy Consortia collaboration activities, such as the Cross-Consortium Engagement Meeting (CCEM), would get this process started.
• The energy community is a large producer and user of models in a wide variety of areas and common standards for what to archive to enable FAIR data and reproducibility have not yet been agreed. Such protocols would be helpful to discuss. The energy research specific issues for sharing the outputs of energy models should continue to be highlighted.

The Energy Data Centre will be taking some of the recommendations forward, and welcome contributions from anyone who is interested in this area.