UKRI research data policy

Purpose of this policy

Policy statement

This policy sets out UKRI’s expectations for managing and sharing research data and other research-relevant digital objects arising from UKRI-funded research.

Good data management and sharing supports the quality and integrity of publicly funded research data and findings, and enhances their value for advancing knowledge, improving lives and driving growth.

Responsibly sharing data, following practices that enable it to be findable, accessible, interoperable and reusable (the FAIR principles), supports:

research transparency, verification and reproducibility
research that is more collaborative, efficient and sustainable
opportunities for new research and innovation

This policy provides a high-level framework of good practice expectations applicable to most research contexts. Research teams can tailor implementation to their research context, drawing on domain-specific best practices and standards, and supported by their research organisations and relevant community infrastructures and resources.

Who this policy is for

This policy is for individuals and organisations undertaking activities funded by UKRI, as set out under ‘What this policy covers’ and ‘Roles and responsibilities’.

Applicants for UKRI funding will normally be asked to explain how they will manage their research data and should note this policy’s requirements.

Policy objectives

This policy aims to promote a research culture and environment where:

UKRI-funded research data is made as open as possible, and as closed as necessary, and FAIR, maximising its use and value for the benefit of society
data management and sharing are recognised as an important part of the research process, and there are policies, activities and resources to support good practice
data sharing is conducted fairly, ethically, legally, safely and transparently
everyone involved in research can adopt, develop and implement good data practice and receive recognition for doing so
unnecessary barriers to data discovery, access and reuse are recognised and minimised

What this policy covers

In-scope research activities

This policy applies to research activities funded by:

UKRI’s research councils
UKRI-wide funding schemes
specific Innovate UK and Research England funding

It applies to in-scope funding opportunities launched on or after 1 April 2027. For requirements relating to funding opportunities launched before this date, and awards arising from these, see our guidance on managing your award.

Further information is provided in ‘Annex 1: supplementary information on scope’.

In-scope research objects

Research data

This policy applies to research data (or ‘data’), defined as recorded information that is collected, created, generated, observed or derived from existing sources through any research method, and used to support, validate or inform research findings.

We recognise that what constitutes research data, and terminology used, can vary across different domains and research contexts. Illustrative examples include but are not limited to:

creative practice process data and analysis materials
digitised records and digital representations of physical objects
image, sound and video files
interview transcripts and survey data
manuscript translations
measurements or observations from experiments or fieldwork
model and simulation inputs and outputs
software-generated outputs
statistics
synthetic data

This policy does not apply to the management and sharing of physical samples, specimens and objects. However, due consideration should be given to their documentation and retention, as appropriate to the research and any applicable policies.

Research-relevant digital objects

This policy also applies to the following research-relevant digital objects:

algorithms, code, models and software resulting from research and needed to understand and validate research data or findings
metadata about data and other research-relevant digital objects
supporting documentation about data and other research-relevant digital objects (for example, workflows, interview and survey questions, README files and other descriptive or contextual documentation)

Algorithms, code, models and software are defined separately to data because in some research contexts they may be treated as distinct from data, and practice may differ to some specific requirements for data in this policy.

Data and research-relevant digital objects include artificial intelligence artefacts arising from in-scope research activities.

Definitions

These objects and other terms used in this policy are defined in ‘Annex 2: definitions’.

In this policy:

‘must’ denotes a mandated requirement, which when not fulfilled, and in the absence of a reason acceptable to UKRI, is a breach of this policy
‘should’ and ‘encourage’ are used with principles and actions that represent best practice and form part of this policy but are not mandated requirements

Supplementary documents

This policy must be read with the following documents, if relevant to your research activity:

Annex 3: economic and social science data deposit requirements
Annex 4: environmental science data deposit requirements
guidance on sharing data about people as a research output

Other relevant policies and resources can be found at UKRI’s good research resource hub.

Information about resources that are being developed to support this policy, including for arts and humanities and research software, is available at Developing UKRI’s research data policy (UKRI Engagement Hub).

Roles and responsibilities

Following this policy is one of UKRI’s funding terms and conditions.

Individuals and project teams undertaking research activities in scope of this policy must manage and share their data in line with this policy and follow any associated institutional policies and processes.

Research organisations in receipt of UKRI funding for activities in scope of this policy must ensure their research staff and research students follow this policy, and provide adequate support and resources to enable them to do so.

This policy complements the shared principles, roles and responsibilities set out in the concordat on open research data and the concordat to support research integrity.

Key principles

UKRI’s requirements are detailed in subsequent sections of this policy. They embrace the following principles, which are broadly relevant to data and other research-relevant digital objects.

Data management is an essential part of doing research

Data management needs to be considered throughout the research lifecycle, including when planning research. This needs to be supported by appropriate project and organisational data management plans, processes, policies and governance.

See requirements under ‘Planning research’.

Sharing data is vital to the quality, integrity and value of publicly funded research

Data that underpins research findings, or that has potential long-term reuse value for the research and innovation community, needs to be shared with as few restrictions as possible and in a timely manner. UKRI also recognises that research teams should normally be entitled to a limited and defined period of exclusive data use, to realise the benefits of their research.

See requirements under ‘What to share’ and ‘When to share’.

Responsible data sharing is as open as possible, and as closed as necessary

Data needs to be shared and reused responsibly, in line with applicable legal, regulatory, security, ethical, contractual or commercial considerations. UKRI recognises this means some data needs to be restricted. Data needs to be as open as possible, and as closed as necessary, and any delays or restrictions on sharing justified and justifiable.

See requirements under ‘Responsibly managing and sharing data’.

Good research is supported by FAIR data

Data needs to be shared in line with domain-specific best practices, formats and standards that support it to be findable, accessible, interoperable and reusable (FAIR). This includes sharing data with adequate metadata and supporting documentation, unique and persistent identifiers, clear information about how it can be reused, and depositing it in an appropriate repository.

See requirements under ‘What to share’ and ‘Where to share’.

Data needs to be appropriately retained and preserved

Good data management includes ensuring data is preserved and retained for an appropriate period of time, giving due consideration to factors such as data value, legal requirements, domain-specific standards, environmental sustainability and relative costs of regenerating data.

See requirements under ‘Preserving and retaining data’.

All contributors deserve acknowledgement and recognition

It is important all those involved in generating, curating, analysing and sharing data receive appropriate acknowledgement and recognition.

See requirements under ‘Providing acknowledgement and recognition’.

Public funds can be used to support good data management

It is appropriate to use public funds to support publicly funded research data to be well managed and shared for public benefit.

See requirements under ‘Planning research’.

Planning research

Research data management, stewardship, curation and sharing must be adequately considered when planning research and throughout the research lifecycle, in line with:

this policy and its supplementary documents
relevant legal, ethical, security and intellectual property requirements and standards, including considering any consents, licences or agreements needed to enable data sharing (see ‘Responsibly managing and sharing data’)
domain-specific best practices, formats and standards that support making data FAIR

Data management plans

Our approach to data management plans is intended to support implementation of good practice, monitoring and making effective funding decisions.

Funding applications

UKRI applicants will normally be required to provide an outline of how they plan to manage and share their research data, in line with this policy.

For some data-intensive funding opportunities, a full data management plan may be required and assessed.

Funded research

If funding is awarded, a full project data management plan that builds on the outline provided at application must be in place within six months of the start of the award, or in the case of training grants within six months of the start of individual studentship projects. The plan must be in line with this policy and kept under review throughout the project.

UKRI reserves the right to request a copy of the data management plan for the purposes of policy monitoring and evaluation.

As part of the implementation of this policy, UKRI will develop updated funding application questions and guidance. See Developing UKRI’s research data policy for more details.

Support for costs

Funding applications should include expected costs for managing and sharing research data, proportionate to the intended activities.

To support this, researchers should engage with any relevant domain, institutional or third-party data repositories and services or data providers as early as possible.

We will develop updated guidance on costing data management and sharing in funding proposals. See Developing UKRI’s research data policy for more details.

Data reuse

Researchers should consider if there are existing sources of data that could be used before committing to primary data collection.

The following research data must be shared in a timely and responsible manner, with as few restrictions on access and reuse as possible:

data necessary to understand and validate published findings or other research outputs
data with potential long-term reuse value for research and innovation

Domain-specific best practices and standards should be used to determine which data, and which versions of those data, are needed to support published findings or may have long-term value.

UKRI has specific deposit requirements for environmental science data and economic and social science data, to facilitate identifying and sharing data of long-term value (see ‘Where to share’).

Data must be:

shared within a reasonable period (see ‘When to share’)
shared using an appropriate repository (see ‘Where to share’)
appropriately managed, documented and prepared in line with domain-specific best practices, formats and standards that support data to be FAIR

Data must be made as open as possible, and as closed as necessary. UKRI recognises some data requires more restricted access, or cannot be shared beyond the primary research team, for legal, regulatory, security, ethical, contractual or commercial reasons. Requirements for managing these restrictions are set out under ‘Responsibly managing and sharing data’.

Metadata and supporting documentation

Data must be curated and shared with adequate descriptive metadata and supporting documentation to enable others to understand, validate and reuse the data. This may include information on its format, provenance, methods of collection or generation, and subsequent processing.

Data formats

Data and metadata should be shared in formats that enable easy reuse. Where possible and appropriate, widely accepted non-proprietary formats should be used.

Machine-readable and machine-actionable formats should be used so that data and metadata can be automatically read and processed by computer systems.

Persistent identifiers

Data must be assigned a unique and persistent identifier (for example, a Digital Object Identifier).

Metadata records and supporting documentation published separately to the data should be assigned their own identifiers and reference the persistent identifier of the associated dataset.

Data access statement

In line with the UKRI open access policy, research publications must include a data access statement. This must include sufficient information to allow others to understand how to access the underlying data. This could include linking to a metadata record that provides this information.

The data access statement must cite the persistent identifier associated with the data or metadata record. Providing this in the list of citations is permitted, if that is the publication venue’s practice.

Licences

Data and metadata must be shared with a clear and accessible usage licence that specifies the conditions under which the data can be reused.

A machine-actionable licence that permits free reuse should be used wherever possible, for example:

More restrictive licences, such as share-alike, no derivatives and non-commercial licences, should only be used where justified by the nature of the data, to minimise barriers to legitimate reuse of publicly funded data.

Restricted data may need an End User Licence Agreement or data sharing agreement, instead (see ‘Responsibly managing and sharing data’).

Research-relevant digital objects

Algorithms, code, models and software arising from in-scope funding that are necessary to understand and validate published research data or findings must also be:

shared in a responsible and timely manner and with as few restrictions as possible, in accordance with the open as possible, and as closed as necessary principle
shared in line with best practices formats and standards that support them to be FAIR, including, as appropriate to the object, provision of adequate metadata and supporting documentation, persistent identifiers and clear usage licences

All research-relevant digital objects needed to understand and validate published data and findings must be documented, including third-party software and objects arising from the research that cannot be openly shared.

Data and associated metadata and supporting documentation must be shared within a reasonable period. We encourage sharing data as early as possible.

Exclusive use

Data sharing should not unreasonably impede the primary research team from realising the benefits of their research, such as publishing findings and patenting. A limited and defined period of exclusive data use is reasonable according to the nature and value of the data.

Any anticipated period of exclusive use must be described and justified in the funding application and data management plan.

Any period of exclusive use should be balanced against the public interest in making data available, taking into account:

the wider value of the data
the research methodology
domain-specific best practices and standards
any applicable regulations such as Freedom of Information and the Environmental Information Regulations

Maximum embargoes on sharing

To ensure publicly funded research data is shared, data and associated metadata and supporting documentation must be shared:

no later than the time for publication, if it’s necessary to understand and validate published findings or other types of research output
no later than two years from the end of UKRI funding, if it has potential long-term reuse value, and has not been published

We will provide guidance to assist decision-making about periods of exclusive use, including when exceeding these maximum embargoes may be justifiable, in due course.

Researchers should allow adequate time to prepare data for publication, and for their chosen repository to curate and make the data available and provide a persistent identifier.

Supporting discoverability and transparency

To support curation, transparency and discoverability of embargoed data:

a FAIR metadata record describing the dataset must be shared using an appropriate repository or registry no later than the time of publication
the metadata record, and data access statements in associated publications, must explain the reason for the embargo, its duration and how access can be requested
data should be curated and prepared ready for sharing, which may include depositing it in a repository under an embargo as early as possible

We recognise it may be necessary to also delay or restrict sharing of metadata and information about a dataset in some circumstances.

Research data and associated metadata must be shared using an appropriate repository that supports data curation, discovery and access, and enables appropriate preservation arrangements for the type of data. This includes using repositories that provide managed access or trusted research environments, where necessary (also see ‘Responsibly managing and sharing data’).

Where available, data should be deposited in a domain-specific repository. Where no suitable domain-specific repository exists, an institutional repository should be used. If neither is available, a generalist repository should be used.

Institutional policies and domain-specific best practices and standards about where to deposit data should also be observed.

Specific requirements on where to deposit research data and metadata apply to:

economic and social science data arising from ESRC and other UKRI funding, as detailed in ‘Annex 3: social science data deposit requirements’
environmental science data arising from NERC and other UKRI funding, as detailed in ‘Annex 4: environmental science data deposit requirements’
other funding opportunities, if specified in the information for the opportunity

Preserving and retaining data

Project teams and research organisations must adequately consider how long data and its associated metadata needs to be retained for, and how it is preserved to remain accessible, understandable and usable for as long as needed. This should take into account relevant factors, including:

legal requirements
domain-specific best practices and standards
the value of data and its research utility: for example, data with long-term value that cannot be reproduced, or are hard to reproduce (such as observational and time-series data) may warrant indefinite retention and preservation
if the data underpins published findings: such data should normally be retained for a minimum of 10 years after publication
relative costs of retaining versus regenerating data
potential historical significance
organisational or repository policies
environmental sustainability

Decisions about retention must involve all relevant stakeholders and be informed by an appropriate and proportionate appraisal that balances the benefits and risks of retaining data against those of disposal. Retained data should be actively curated and preserved, including documented review points.

Provided that an appropriate and documented decision-making process has been followed, justified disposal of data is permitted.

Metadata records referring to deleted datasets should be retained and explain the data has been deleted and why.

Providing acknowledgement and recognition

To support recognition, visibility and citation, the contributions of those involved in generating, processing, analysing and curating data and research-relevant digital objects must be appropriately acknowledged and recorded in dataset metadata, research publications and other research outputs.

Clear and permanent references to contributions should be provided in publications, for example using a recognised taxonomy such as the Contributor Roles Taxonomy (CRediT).

The metadata record for a dataset should include persistent identifiers for individual contributors, research organisation affiliations and funders where available, for example using:

Citing and reusing data

Data users must appropriately cite data sources using the citation information and persistent identifiers provided by the data providers.

Data users must follow legal, ethical or regulatory frameworks and observe any other policy or licensing restrictions that apply to data they are using.

This section details expectations for responsibly managing and sharing data and research-relevant digital objects, including managing restrictions on data sharing. Also see:

UKRI’s guidance on sharing data about people as a research output
the good research resource hub

Ethics

Research data management and sharing must be undertaken in line with applicable ethical standards, processes and practices.

Ethical justifications for a more restricted approach to sharing may not only apply to data about people but also other forms of data, such as data identifying the location of a protected species, or research with dual use potential.

The following guidance should be followed for applicable research:

Engagement

We encourage direct engagement with relevant people, groups and organisations when collecting and sharing data, to foster an inclusive, representative, and transparent data sharing environment. This may include participatory research methods, and proportionate public and participant engagement and involvement when sharing data about people.

Legislation and regulation

UKRI-funded organisations must ensure they are aware of relevant legislation and regulations applicable to research data and support their researchers in complying with these.

Partnerships and collaborations

We encourage UKRI-funded organisations and researchers to work in productive, equitable partnerships, including when sharing research data.

Where applicable, research data access, ownership and sharing arrangements must be set out in research collaboration agreements and data sharing agreements. Necessary clearances should be sought from all collaborators before sharing data.

Trusted research and innovation

UKRI-funded organisations must undertake appropriate trusted research and innovation due diligence for all collaborations before openly sharing research data. This is set out in UKRI’s trusted research and innovation principles and expectations and our funding terms and conditions.

Intellectual property and commercialisation

Intellectual property arising from UKRI-funded research activities must be suitably managed, in line with UKRI’s intellectual property strategic statement. This can and should be implemented alongside FAIR data practices.

Partners entering a collaboration should consider if any data may need to be restricted for commercial reasons. This may include data provided by a commercial partner or to allow intellectual property to be protected for the purposes of commercialising research.

Delays or restrictions on sharing data due to managing and exploiting intellectual property are permitted but must be minimised and justified, as detailed under ‘When to share’ and ‘Managing restrictions on sharing’.

Managing restrictions on sharing

Data must be made as open as possible, and as closed as necessary. Restrictions on sharing data for legal, regulatory, security, ethical, contractual and commercial reasons are permitted, where it can be justified for the data and research in question.

If it is anticipated data needs to be shared more securely or cannot be shared, this must be justified and outlined in funding applications and data management plans.

Recognising there are different tiers of data sensitivity, due consideration must be given to options for more secure forms of sharing (for example, data anonymisation, or where this is not appropriate, access via a trusted research environment or a repository that provides managed access).

When deciding how to make research data available, the Five Safes Framework should be consulted (safe data, safe projects, safe people, safe settings, safe outputs), where relevant to the research.

Seeking consent and data sharing rights

Where research data will be collected or derived from secondary or third-party sources (for example, data collected from human research participants, or data that needs to be licensed from another organisation), anticipated data sharing should be discussed as early as possible. Consent or data sharing rights that enable sharing in line with this policy should be sought, although we recognise that rights may not always be granted.

Supporting findability, transparency and secure access

To support the findability, transparency and accessibility of restricted data:

a FAIR metadata record describing the dataset must be shared using an appropriate repository or registry no later than the time of publication
the metadata record, and any data access statements in publications, must provide information about why the data is restricted and how access can be requested

We recognise it may be necessary to also delay or restrict sharing of metadata and information about a dataset in some circumstances.

Where data need to be shared more securely, for example via a trusted research environment or repository with managed access:

appropriate, proportionate and transparent data access processes, policies and governance must be in place
information about how others can apply to the data provider to access data, subject to approval, must be available by the time of first publication
data sharing must only proceed with an appropriate End User Licence Agreement or data sharing agreement

Environmental sustainability

Generating and storing data has an environmental footprint. Good data management supports sustainability, by enabling the discovery and reuse of existing data, and minimising unnecessary data storage.

When planning data management, project teams and research organisations should consider environmental sustainability, for example:

considering low-carbon storage methods (for example, magnetic tape)
back-up plans which avoid excessive duplication
balanced data retention periods, and appropriate assessment and processes for data disposal, including review dates for indefinite storage
retaining final curated, or minimal versions of data needed for future use and replicability

Cost recovery and revenue generation

Unless otherwise approved by UKRI, projects must not seek to profit or generate revenue through the sole purpose of research data sharing.

Unless otherwise specified by UKRI, cost recovery for data sharing is acceptable if it is reasonable and proportionate; for example, in circumstances involving high costs of data preparation and transfer.

UKRI reserves the right to set out specific expectations on cost recovery and revenue generation for some investments.

Failure to comply

UKRI will monitor the implementation of this policy to assess compliance of research organisations and to evaluate policy effectiveness and impact.

We will act where there is clear evidence of a research organisation disregarding implementation of the policy. For example, where there is a pattern of repeated or extensive non-compliance, or evidence of an organisation not adequately supporting researchers.

Any measures will be proportionate and aim to support research organisations to address compliance issues.

Sanctions for non-compliance are set out in our grant terms and conditions.

Management of this policy

This policy is owned and managed by UKRI’s Head of Open Research Strategy, who approved the policy on 2 October 2026.

Questions about this policy can be directed to openresearch@ukri.org

Annex 1: supplementary information on scope

This annex provides supplementary information for the ‘What this policy covers’ section of the UKRI research data policy (referred to as ‘this policy’).

Research council and cross-UKRI programmes

This policy applies to research activities funded by UKRI-wide schemes and our research councils, including:

Arts and Humanities Research Council (AHRC)
Biotechnology and Biological Sciences Research Council (BBSRC)
Engineering and Physical Sciences Research Council (EPSRC)
Economic and Social Research Council (ESRC)
Medical Research Council (MRC)
Natural Environment Research Council (NERC)
Science and Technology Facilities Council (STFC)

This includes UKRI-funded studentships and fellowships.

This policy applies to UKRI-funded research centres, consortia and infrastructures. UKRI will advise for specific investments if there are any exceptions or variations in how this policy applies.

UKRI research centres, facilities and institutes

This policy applies to research undertaken by UKRI research centres, facilities and institutes, where the research is UKRI-funded.

It does not apply to users of UKRI research facilities who are not funded by UKRI. However, a facility’s own data policy may still apply.

It does not apply to data resulting from or relating to work carried out by UKRI research centres, facilities and institutes under contract or service-level agreements with other organisations (for example, data arising from commercial use of facility beam time). Policy regarding such data is the responsibility of the contracting organisation.

It does not apply to information products (in which another level of intellectual input refines or adds value to the original, shared research data) or data services produced or provided by UKRI centres, facilities and institutes. The NERC licensing and charging for information policy sets out how such products and services are made available.

Innovate UK

This policy recognises that some data may need to be shared more securely or restricted for commercial reasons (see ‘Responsibly managing and sharing data’).

If a business and academic partner agree to publish a peer-reviewed publication that needs to acknowledge Innovate UK funding, the publication must be made open access in line with Annex 1 of the UKRI open access policy. The data and metadata needed to understand and validate the published findings must also be managed and shared in line with this policy.

Unless detailed in guidance for funding opportunities, other Innovate UK funding is not in scope of this policy. However, UKRI encourages good practice, in line with this policy’s principles.

Research England

Most Research England funding is deployed by universities at their discretion and is not intended to support specific research projects. Where such discretionary funds are used by universities to support research, the research and its outputs, including research data, cannot be directly attributed to Research England funding, nor is it possible to identify what research was produced or supported in this way. No acknowledgement of Research England funding is expected or necessary, and any associated data is considered out of scope of this policy.

This policy applies where Research England funding is given for specific purposes, and that funding leads directly to particular research outputs or project findings that include:

research data necessary to understand and validate published findings
research data that has potential reuse value

Research England will specify this in the terms and conditions of each relevant scheme.

However, Research England expects universities in receipt of funding that is out of scope of this policy to still act according to good practice, in line with this policy’s principles and the concordat on open research data.

International research

This policy applies to in-scope UKRI-funded activities (and applications for funding), irrespective of whether they take place in the UK or internationally.

Where UKRI is a subscribing partner to an external organisation (for example CERN), or involved in other internationally agreed collaborations, we will seek to ensure that the organisation has a research data policy, and that it is sufficiently compatible with UKRI’s policy.

For other international projects co-funded by UKRI, the awarding council will advise if there are any exemptions or variations with respect to how this policy applies.

Co-funded research

UKRI may fund research in partnership with other organisations. Where funding is issued under UKRI terms and conditions, this policy must be followed. Where funding is awarded under another funder’s terms and conditions, that funder’s policies will generally apply. Researchers and organisations should consult the specific terms and conditions associated with their award to confirm the relevant policy requirements.

Data sharing in emergencies

UKRI reserves the right to apply additional conditions to funding opportunities to expedite open data sharing, when this is in the public interest to support the response to a national or international crisis, such as a public health emergency.

Other exceptions

Given the diversity of UKRI-funded activities, some funding opportunities and investments may specifically detail how to follow this policy or provide additional expectations.

Annex 2: definitions

This annex provides definitions for other research-relevant digital objects and other terms used in the UKRI research data policy (referred to as ‘this policy’).

‘Research data’ is defined in the ‘What this policy covers’ section of this policy.

These definitions draw on international definitions, including:

Algorithms

The computational steps and rules to be followed in calculations or other problem-solving operations, especially by a computer.

Artificial intelligence artefacts

Research data and research-relevant digital objects include machine learning and artificial intelligence artefacts (including algorithms) where these are necessary to understand, verify, reproduce or reuse research findings, such as training data, model weights, parameters, prompts, evaluation datasets and generated outputs.

Code

A set of human-readable computer program instructions that expresses an algorithm so that it can be executed by a computer. This policy distinguishes between research software source code, and data processing code or statistical programming code provided as supporting documentation about how data is generated, processed and cleaned.

Data access statement

A statement accompanying a research publication that describes whether supporting data is available to access, where this has been made available and under what conditions. May also be referred to as a data availability statement.

Data management plan

A statement describing how research data will be managed throughout a specified research project’s life cycle (during and after the active phase of the research project).

FAIR principles

A set of internationally recognised guiding principles to make (meta)data and software findable, accessible, interoperable and reusable (FAIR).

Machine-actionable

Machine-readable dataset or file format that is structured in such a way as to allow machines to take automated programmed actions as a result.

Metadata

Data (or information) that defines and describes the characteristics of other data. It is used to improve the understanding, findability and reusability of data. Machine-actionable metadata is structured so that it can be read, interpreted and processed by a machine.

Models

A model is a structured representation used to improve understanding, analysis, communication or decision-making about an object, system, process, phenomenon, concept or scenario. Models may take a range of forms, including visual diagrams, conceptual frameworks, mathematical representations, datasets or computer simulations.

Open as possible, and as closed as necessary

An internationally recognised principle that publicly funded research data should be shared with as few restrictions on access and reuse as possible.

Open data are data that can be freely accessed, used, modified and shared, under the terms of an open licence.

The principle recognises there can be legitimate reasons for some data to be closed or shared in a more secure or restricted way. For example, to maintain confidentiality, protect individuals’ privacy, respect consent terms, manage security or other risks, and support commercialisation.

Preservation

The managed activities undertaken to ensure that data and associated metadata remain accessible, understandable, usable for as long as required, with their provenance and integrity maintained over time. Activities may include, but are not limited to, format monitoring, data integrity checks and platform migrations.

Repository

An institutional, subject-specific or generalist digital archive that supports the storing, curation and sharing of research data or other research-relevant digital objects. In this policy, this term is used broadly and encompasses repositories referred to by other names (for example, archives, databases, data centres and trusted research environments).

Research data management

The part of the research process that deals with the organisation, preparation and handling of research data. This includes data management planning, structured storing, description, curation, preservation, the provision of metadata and supporting documentation, and compliance with national and international legislation.

Research data sharing

Any activity where data is provided, or made available, beyond primary research purposes.

Software

The source code files, algorithms, scripts, computational workflows, documentation and executables that were created during the research process or for a research purpose.

Supporting documentation

Descriptive or contextual documentation that explains how data or other research-relevant digital objects were collected, generated or processed. Examples include, but may not be limited to:

method summaries
protocols
workflows
statistical programming code
data processing code
interview questions
survey forms
topic guides
README files

Trusted research environment

A highly secure digital environment that provides access to data for analysis by approved researchers, where data need to be stored and shared more securely. In this policy, this term is also used to refer to secure data environments and data safe havens.

These expectations apply to social science data, as defined in the following section, arising from any UKRI-funded research in scope of the UKRI research data policy.

In addition to requirements set out below:

UKRI guidance on sharing data about people as a research output must also be consulted if relevant to the research
the UK Data Service research data management guide should be consulted for information and resources to support managing and sharing social science data

Social science data definition

Social science data is defined as data about people and society that is generated, collected or reused through research on economic, social, behavioural, and population issues. This includes data about people and their relationships, as well as data about economic and social institutions, such as business organisations and public sector agencies.

Social science data includes:

primary data collected from participants (for example, survey, interview, observational data, administrative and other third-party sources)
data derived from secondary or third-party sources (sometimes referred to as ‘Research Ready Data’ where permitted under licence or agreement)
statistical programming code (statistical code written in a programming language used to generate, prepare and clean data and generate results)

Types of social science data include:

survey and population data
administrative data (generated through interactions between individuals and business organisations with government agencies)
qualitative data (for example, from interviews, focus groups, ethnographic observations, case studies)
experimental and behavioural data (for example, social or economic behavioural data)
digital and emerging data (for example, consumer data about people generated through loyalty schemes, apps and other transactions between individuals and business organisations via new technologies)

Deposit requirements

ESRC funds UK Data Service to support the deposit, dissemination and preservation of economic, population and social research data collections to maximise their discovery, value and impact.

Further to the UKRI research data policy requirement for research data to be deposited in an appropriate repository, the following requirements apply:

social science data from ESRC-funded research must be offered for deposit in UK Data Service by the end of the grant period
we encourage social science data arising from other UKRI-funded research to be offered for deposit in UK Data Service
if data is deposited in an alternative repository to UK Data Service, a metadata record must still be submitted to UK Data Service to support discoverability of social science data

If choosing an alternative repository, we encourage researchers to choose one that undertakes appropriate checks and curation for social science data. Researchers should also be aware some repositories may have restrictions on depositing identifiable or sensitive data, or data with intellectual property implications.

We recognise some data and metadata could be subject to restrictions that mean it may not be offered for deposit in UK Data Service. The UKRI research data policy’s requirements for managing restricted data still apply.

How to deposit

The deposit process is completed online and involves submitting a data collection for appraisal. UK Data Service will:

review the submitted information and accompanying documentation
assess its suitability for deposit and long-term preservation in UK Data Service
recommend the most appropriate alternative repository and access conditions when this is more suitable for the nature of the data, and in line with the UK Data Service collections development policy

The submission form and further information can be found on the UK Data Service website.

Researchers should also review the UK Data Service guidance about preparing collections for deposit.

Cost of service

Depositing data in UK Data Service is free of charge to UKRI grant holders. However, costs associated with preparing data for deposit, including anonymisation, documentation, metadata creation and administrative time for submission and responding to repository feedback or revisions, need to be planned for and included in grant budgets. These activities are eligible costs under UKRI funding.

UK Data Service provides a data management costing tool for social science research.

Annex 4: environmental science data deposit requirements

These expectations apply to environmental science data, as defined in the following section, arising from any UKRI-funded research in scope of the UKRI research data policy.

Environmental science data definition

Environmental science data is defined as individual items or records (both digital and analogue) usually obtained by measurement, observation or modelling of the natural world and the impact of humans upon it. This includes data generated through complex systems, such as information retrieval algorithms, data assimilation techniques and the application of models.

Deposit requirements for digital data

NERC funds the Environmental Data Service (EDS) to provide data stewardship services to ensure that environmental science data is made available, accessible and reusable for the long-term.

Further to the UKRI research data policy requirement for research data to be shared using an appropriate repository, the following requirements apply where research is funded by NERC:

environmental data of long term value must be offered to EDS for secure long term management and dissemination
in agreement with EDS, where environmental data is not suitable for deposit within EDS, researchers will be referred to other appropriate, approved repositories where the environmental data must be deposited
if data is deposited in another repository, a metadata record must be submitted to EDS to ensure NERC-funded data is discoverable

We encourage environmental data arising from other UKRI-funded research to be offered for deposit in EDS.

We encourage NERC-funded researchers, and other UKRI-funded researchers considering using EDS, to contact the service when planning research, in order to:

check if the data fall within the service’s remit
discuss the available support and guidance and costs, where applicable

Contact the Environmental Data Service

NERC-funded researchers must follow these requirements. Those who fail to do so may risk having award payments withheld or becoming ineligible for future funding from NERC.

Cost of service

NERC-funded research

NERC funds the EDS directly to archive and curate data arising from NERC-funded grants. However, costs associated with preparing data for archiving, including documentation, metadata creation and administrative time for submission and responding to EDS feedback or revisions, should be budgeted for in your grant. These activities are eligible costs under UKRI funding.

Additional EDS services, such as database development or a specialist in project data management for a project, need to be discussed with EDS prior to submitting a grant proposal. Costs for additional services need to be included in grant budgets.

Other UKRI-funded research

NERC does not directly fund EDS for other UKRI-funded grants. For other UKRI-funded projects planning to use EDS, the following costs will need to be budgeted for in your grant:

costs for using the EDS to archive and curate data
costs associated with preparing data for archiving

EDS can provide costing guidance and information.

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