Demand management
Demand management is not currently being applied to this funding opportunity. However, should the level of interest exceed what can be managed within the assessment process, UK Research and Innovation (UKRI) may introduce limits on the number of applications that can be submitted. Further details will be clearly communicated where this is the case. UKRI encourages organisations to support applicants in preparing well-planned, high-quality applications that are competitive for funding relative to the funding opportunity.
About the sandpit
We are seeking expressions of interest to attend a four-day hybrid sandpit. The sandpit will take place on 12 (in-person, London), 14, 19 and 23 October (virtual). Attendance for the full four days will be mandatory.
The sandpit will bring together approximately 40 applicants from across ESRC’s social science data service infrastructures, data users, and experts in data management, curation, discovery and access as well as individuals with background and experience in developing and applying technological solutions to deliver discovery and access. The focus will be to co-develop project proposals to enhance ESRC’s social science data service infrastructures, and to explore the opportunities in this area.
The overall aim of this sandpit is to develop projects that:
- will make a step change in how researchers can discover, access and use social science data
- advance the transition to technology-enabled data pipelines that support data management, curation, discovery and access
- in turn, will develop and upskill data service infrastructure workforce to support the research community in the future
This funding opportunity arises out of the Future Data Services (FDS) Review which investigated the challenges for accessing and using data and the opportunities for future data infrastructure provision. This sandpit will therefore support the delivery of the FDS recommendations and its vision for the future of data services:
“A seamless, connected, user-centred and federated data service landscape, driven by curiosity, collaboration and coordination, and making use of the new technologies that present boundless possibilities for researchers to use data for public good.”
In line with the FDS review this opportunity is agnostic of data types. We encourage applicants with expertise of delivering discovery and access to various data types to submit an expression of interest, including quantitative, qualitative, longitudinal and cross-section survey data, smart data, administrative data, consumer loyalty data and other types of data generated and used in the social sciences. Throughout the sandpit process we will encourage selected participants to consider delivery of discovery and access to all data types when developing their projects and welcome projects across data types.
Expected outcomes
Through investment in transforming discovery and access to social science data, the following outcomes are expected:
- researchers use transformational technologies to more easily find data and can access consistent harmonised information about data
- data services staff use transformational technologies to more easily manage and curate data
- researchers experience a consistent and efficient journey which is easy to understand when applying to access data
- data owners can more easily deposit their data with data services for onward use by researchers
- data services staff are equipped to deliver transformational services and support researchers, and have the technical skills to develop and implement new technologies and systems
Scope
This funding opportunity will fund projects with a focus on improving how researchers, users and data depositors engage with data services, improving their experience in discovering, accessing and using data. It will also fund projects with a focus on improving the backend process to transition to technology-enabled data pipelines (particularly those that deploy AI) that support data management, curation, discovery and access.
During the FDS review, the research and infrastructure community highlighted the challenge of proliferation in the landscape. ESRC therefore aims to fund improved data services rather than more data services. As such, this funding opportunity will only consider projects which enhance one or more ESRC social science data service infrastructure investments. Therefore, all projects developed at the sandpit must partner with an existing ESRC social science data service infrastructure investment, though the infrastructure does not have to lead the project. For example, the project lead can come from a different research organisation to the data service and not have previously worked with them. Please see ‘Additional information’ for a list of ESRC social science data service infrastructure investments.
Proposed activity must not duplicate existing data infrastructure services and functionalities but rather should enhance, develop and improve existing infrastructures to resolve challenges experienced by researchers, users and data depositors in their journey. Projects will not propose any new data service infrastructures, any new provision should build on existing services, platforms and approaches, and de-complexify the landscape. Funding will only be available for new tools and services that are supported by plans for adoption by ESRC social science data service infrastructures (including ‘pilot’ projects).
The projects developed at the sandpit should advance at least one, or a combination of the following priority areas identified in the FDS review:
- data discovery
- access to sensitive data
- technology
- upskilling and supporting staff
Projects are not expected to address every objective under the associated priority area; a minimum of one objective must be addressed. Projects must also include a work package on upskilling and supporting staff. Activities, timelines and outputs must be feasible within the resource available. Details on each priority area are outlined below.
Data discovery
The FDS review highlighted a clear challenge for users in discovering data and accessing high quality and consistent information about data, due to proliferation of curation standards and discovery search tools. Some tools, and the standards of curation, and available metadata, do not always meet the needs of the research community. ESRC’s ambition for this area is that future initiatives will both enable the development of new tools while simultaneously building on existing capability to improve curation and discovery services and capability.
Our objectives for successful awards with a focus on improving the experience of researchers, users and data depositors in discovering data are to:
- improve data discovery and curation practices so that they meet the needs of the research community
- create and develop guidance, resources and support for:
- better data documentation
- better metadata, including support for investments to know the appropriate level of metadata to implement
- curation of data generated by government agencies
- data depositors to deposit data with data services
- making datasets more visible and improved signposting of where to access data
- routine production of synthetic data
- support harmonisation and consistency in approaches to data discovery and curation, such as in metadata, documentation and standards. Supporting interoperability and progression to federation of data discovery
Synthetic data is a growing area for investment, aiding researchers in their understanding of data sources. ESRC has identified specific areas requiring support:
- production of low fidelity synthetic data of non-administrative secure data with associated documentation and privacy assurance
- testing how high-fidelity synthetic data could be produced and utilised outside of Trusted Research Environments
- testing different use cases of synthetic data to establish a sound evidence base for routine synthetic data provision and its utility
- effectively documenting synthetic data and creating training resources to ensure their effective use
ESRC and ADR UK, with support from UKRI Digital Research Infrastructure Programme, have previously funded projects in this area (please see the FDS report for further details on these projects). Projects focused on synthetic data should review and align to the ADR UK Synthetic Data Working Group guidance on the provision of synthetic forms of secure data.
Access to sensitive data
The FDS review highlighted that users experience uncertainty and delays when trying to access sensitive data for research. ESRC’s ambition for this area is that the processes to access data are proportionate, transparent and visible and minimise waiting time for users. Data access forms are easy and unambiguous to understand and complete, and researchers have clarity about their journey to access data.
Our objectives for successful awards with a focus on improving the experiences of researchers and users in accessing sensitive data are to:
- improve access to sensitive data, ensuring processes are proportionate, transparent and visible, and minimise waiting times for users
- create and develop guidance, resources and support for researchers to apply for and access data, such as the provision of templates and examples, training on feasibility assessments and ethical approval, and the publication of the entire data access cycle outlining the researcher journey
- support consistent and harmonised data sharing practices to enable interoperability and progression to federated data access
- ensure data service infrastructure staff are knowledgeable about data, and the use of data for research
Technology
Technology is an underlying theme across FDS, which supports better data discovery and data access, and relies on an upskilled workforce to deliver it. It is therefore an essential element to funding in this area and should be considered for inclusion across all projects.
Our objectives for successful awards with a focus on advancing the transition to a technology-enabled data pipelines that supports data management, curation, discovery and access are to invest in:
- automated processes (including development and adoption of AI) to remove backend data access processing friction and improve data ingest, curation and discovery
- technology (including cloud services, if appropriate) to enhance services or additional tools for the research community
Upskilling and supporting staff
Upskilling staff is a priority area for UKRI. Ensuring staff have the necessary skills to deliver enhanced data services, is essential across all projects. Therefore, each project must include an upskilling staff work package, which address the objectives outlined below and is designed to support the careers of staff working within data service infrastructures. The aim of this is to ensure that researchers and data depositors benefit from interactions with expert service providers, leading to better data services for research. It will also ensure sustainability of the value from this one-off funding. Projects will be required to demonstrate the training, skills development and learning support they will provide to new and existing staff.
Our objectives for this work package in each successful award will be to:
- invest in teams, resources, training and leadership, across a range of roles, to upskill the data service workforce to deliver better data service provision
- where applicable, provide resources and training to upskill data service workforces to support and adopt new technologies and technical skills
- define career pathways with training and skills matrix which encompasses actual job activities, particularly with reference to non-technical skills such as management and leadership
- enable data service staff to have good familiarity with research, and a thorough understanding of the needs of researchers, for example why they need to discover and access data, to ensure enhancement support researchers in their journey
Data services are made up of diverse roles, with skills and training needs varying. This will need to be considered in project development. Priority skill areas identified (including through the recent UKDS Computational Skills Survey), but not limited to, are:
- understanding social science data and research and in turn why people want to use data
- artificial intelligence (AI) and machine learning, its application and implementation, such as agentic AI
- prompt engineering and use of AI tools
- programming skills and coding
- database and data architecture skills
- workflow automation and reproducibility
- data visualisation and user experience
- leading effective data science and engineering teams working in the social sciences
- creating and curating data
- providing expert support to help researchers make the most of data
- statistical disclosure control and other key skills to support the operation of Trusted Research Environments
Across these priority areas, participants will be encouraged to interact with the existing resources, learning and recommendations developed in this area. Notably, ESRC and UKRI funded a series of pilots as part of the FDS programme focused on:
- federation of data services
- data discovery using machine learning or other AI technologies
- increasing skills capacity for data service professionals
Further details can be found on the FDS webpage. Through this work ESRC hope to adopt and develop the learning and recommendations of previously funded FDS pilots.
Collaboration and engagement
Collaboration refers to the activity which creates, enables and maintains connections between researchers, policymakers, organisations, infrastructures and communities to maximise impact and innovation. Engagement is the mechanisms you use and actions you take to realise and share your intended collaborative outputs and impacts of the project. Collaboration and engagement are essential at all stages of the project.
Collaboration across the data services landscape is key to deliver a seamless, connected, user-centred and federated data service landscape, driven by a ‘whole system’ outlook which enables ESRC’s data infrastructure investments to connect and co-deliver consistent and improved service to help researchers.
Although there are examples of collaboration, the review noted the need for data services to interconnect with each other more often, for example, to overcome the challenges (such as variation in processes, or quality of metadata) that researchers face when they interact with different data services to access different data. This creates a burden on their time and research productivity.
The FDS review highlighted the importance of co-design, whereby data services are designed with researchers by default. Projects therefore must engage with the external user and research community throughout the project to understand and anticipate their needs and ensure enhancements support the intended impact for the community on how they discover, access and use data. Projects should clearly articulate their engagement plans for the development and delivery of projects. We encourage users and data depositors who would benefit from the outputs of this opportunity to apply and engage with ESRC’s social science data service infrastructures.
This process is built around fostering collaboration, to co-design, co-create and co-deliver projects that will support a more effective and efficient federated data service landscape, reducing the bureaucracy experienced by researchers when accessing and using data services and ensuring services meet community needs. Supporting collaboration and engagement through this process and the subsequent awards brings us closer to accomplishing our vision of a federated data landscape designed with researchers by default.
This funding opportunity, and planned future FDS opportunities, are being funded as a programme. Successful projects will be expected to engage and collaborate with each other, ESRC-supported data infrastructures and the wider social science community including users where activities and learning may overlap and where this can add value. Successful projects will outline collaborations and related benefits.
Sandpit process
Following the expression of interest (EOI) process outlined under the ‘How to apply’ and ‘How we will assess your application’ sections, the process described below will be followed.
Details of the sandpit
The sandpit will be an intensive, interactive workshop bringing together a diverse group of participants from a range of disciplines and backgrounds to work together over four days.
The sandpit will be led by the ESRC Data Strategy and Infrastructure Programme, who will be supported by a team of mentors, and colleagues from across UKRI including, UKRI Digital Research Infrastructure Programme and ESRC Administrative Data Research UK and Smart Data Research UK hubs.
The mentors and a number of stakeholders will attend the sandpit but will not be eligible to receive funding. Instead, their role will be to assist participants in defining and exploring solutions in this area. The mentors will act as independent reviewers, making a funding recommendation on the emergent projects.
Attendance at the sandpit does not guarantee UKRI funding. It is our intention that this sandpit will be a valuable experience for all attendees irrespective of whether funding is secured.
Participants must make their own travel arrangements. Travel and subsistence costs will be reimbursed.
Since this sandpit is in-person for one day and, where employers cannot help, ESRC, in line with UKRI policy, will cover the costs of any additional childcare or caring responsibilities which are deemed necessary during this period.
Before the sandpit
Successful EOI applicants will be required to attend a webinar where the key challenges identified via the FDS report will be presented. Briefings will also cover logistics and aims for each step of the sandpit process, ensuring clarity on expectations for the sandpit. A resource pack will also be provided for the sandpit process to support participants throughout the process.
The ‘Future Data Services Phase 1: Fixing the Data Pipeline’ report will be the primary reference document for this sandpit. It sets out the challenges for accessing and using data, the opportunities for future data infrastructure provision and ESRC’s vision for the future of data services. We expect you to read it before submitting an expression of interest. We advise successful EOI applicants to familiarise themselves with the report.
During the sandpit
The sandpit will involve several activities:
- sharing understanding of the opportunities for enhancing ESRC’s social science data infrastructures and draw upon perspectives from relevant stakeholders and the expertise brought by the participants
- addressing the challenges for discovering, accessing and using social science data, realising the opportunities identified, and implementing the FDS recommendations
- identifying themes and potential project avenues to develop and capture ideas that could form the basis for highly innovative team research project proposals
- form teams and develop project proposals that clearly articulate a theory of change, supported by peer and mentor advice and guidance
- capture the outputs of the process in the form of highly innovative project proposals
- ‘real-time’ peer review to support funding decisions
More information, including a day-by-day agenda, will be provided in due course.
Please note we do not require participants to develop specific plans or teams for research activities prior to the sandpit. Ideas for activities will be developed collaboratively during the process. Projects developed through the process will pitch for funding on the final sandpit day.
At the sandpit, projects will be assessed by expert review and recommended for funding.
After the sandpit
Participants will be invited to submit a full project proposal document, to include a theory of change approach, detailing their intended activities as identified at the sandpit.
It is planned that participants involved in projects identified for funding will be informed within one week of the sandpit. Funding will be conditional on receipt of a full proposal and the proposal passing the appropriate checks.
The submissions should accurately represent projects and teams assembled at the sandpit. Where skills gaps were identified and discussed at the sandpit, researchers or other parties, including non-academic project partners, can be added to successful projects with approval from the mentors at the sandpit.
The deadline for submission of full proposals is expected to be 3 December 2026.
Proposals will be submitted through the UKRI Funding Service. Further guidance on this part of the process will be available to the successful project teams.
Awards
Funding available
It is expected that around five to 10 projects will be funded, sharing up to £21.6 million of total funding at 100% full economic cost (FEC). ESRC will fund 80% FEC.
Duration
Awards aim to be issued in January 2027, and awarded projects must start by 1 April 2027. Projects must end by 31 March 2031. The duration of the award is a minimum of 24 months and a maximum of 48 months.
Investment monitoring
ESRC will set out the investment monitoring process with successful projects in the specification for full proposals. Further monitoring and reporting requirements will be outlined in the terms and conditions of awards.
For more information on the background of this funding opportunity, go to the ‘Additional information’ section.
What we will fund
We seek to support project proposals that:
- are co-created, co-designed and co-delivered, supporting a federated data service landscape
- demonstrate the ability to transform discovery and access to data via existing ESRC social science data services infrastructures, preventing proliferation and duplication in the landscape
- enable the delivery of better research, supporting the needs of the whole community and taking into consideration the views of users
- will make a step change in how researchers can discover, access and use social science data
- advance the transition to technology-enabled data pipelines that support data management, curation, discovery and access
- support the upskilling of the social science data services workforce to ensure that researchers and data depositors benefit from interactions with expert service providers, resulting in better delivered services
What we will not fund
We will not fund:
- the creation of a new infrastructure
- work that duplicates existing data infrastructure services and functionalities
- work conducted in isolation and that does not enhance an existing ESRC social science data service infrastructure
- standard research projects
- writing up previous research
- preparation of books and publications
- literature surveys
- general conference attendance that is not related to conducting the proposed work
- studentships
- new tools and services that are already supported by plans for adoption by ESRC social science data service infrastructures (including ‘pilot’ projects)
Trusted Research and Innovation (TR&I)
UKRI is committed in ensuring that effective international collaboration in research and innovation takes place with integrity and within strong ethical frameworks. Trusted Research and Innovation (TR&I) is a UKRI work programme designed to help protect all those working in our thriving and collaborative international sector by enabling partnerships to be as open as possible, and as secure as necessary. Our TR&I Principles set out UKRI’s expectations of organisations funded by UKRI in relation to due diligence for international collaboration.
As such, applicants for UKRI funding may be asked to demonstrate how their proposed projects will comply with our approach and expectation towards TR&I, identifying potential risks and the relevant controls you will put in place to help proportionately reduce these risks.
See further guidance and information about TR&I, including where applicants can find additional support.
