Data sharing strategies

The rise of open science, supported by digital technologies, has transformed how research outputs, including data, are shared and preserved. There is a growing push, from funders, publishers, and institutions, for data to be made available for future reuse. Sharing your data increases the transparency, reproducibility, and reach of your research. However, responsible sharing means balancing openness with ethical and legal considerations.

Clarifying “open” access

Open access to data does not necessarily mean unrestricted access or an open licence. Especially when collecting data from human participants, data may require specific access controls and licensing restrictions, or embargo periods. Sharing responsibly means thinking critically about who can access the data, under what conditions, and with what protections in place.

Aligning with funding requirements

It is important to ensure that your data sharing strategy aligns with the data management and sharing policies set by your research funders. Many funders have specific conditions regarding how and when data should be shared. Checking these requirements early in your planning will help avoid compliance issues and make the data sharing process smoother.

Choosing your research data sharing strategy

There are several ways to share data. Each comes with different levels of support, sustainability, and responsibility. Wherever possible, use trustworthy data repositories (responsible repositories) that provide robust services and align with the FAIR data principles.

Trustworthy data repositories / Data Archives / Data centres

Using a certified domain-specific data repository, sometimes referred to as a Data Archive or data centre, and occasionally including a Trusted Research Environment / Secure Data Environment function, is often the most sustainable and reliable option. This sharing strategy aligns with the FAIR data principles and for example supports data discoverability through standard metadata and data cataloguing, enables responsible sharing through appropriate licences and access control, and provides safe, long-term preservation.

For example, at the UK Data Service we support data producers in the social sciences by providing trusted infrastructures for sharing both population representative data and smaller scale, experimental data and code. We implement and promote the FAIR principles via the use of standard metadata schemas such as DDI, domain-specific controlled vocabularies and ontologies, and open protocols like OAI-PMH for metadata harvesting. We also assign persistent identifiers (DOIs) to data collections to facilitate citation and long-term traceability.

Our team supports researchers in creating rich metadata to maximise data discoverability and reuse and we provide guidance and training to help meet community standards and regulatory requirements. At the same time, we balance FAIR principles with necessary ethical and legal safeguards, helping data producers navigate ethical and legal considerations to ensure responsible data sharing that maximises research impact. Researchers funded by the Economic and Social Research Council are contractually required to offer their data for deposit with the UK Data Service, or, if using an alternative responsible repository, to ensure that metadata is submitted to the UK Data Service to increase the discoverability of the data.

To identify suitable trustworthy repositories, you can explore registries like re3data.org, which provides a comprehensive, curated directory of research data repositories worldwide. This resource helps data producers find repositories that align with their disciplinary needs, certification standards, and data governance requirements, ensuring their data are preserved and shared responsibly.

Institutional repositories

Some institutions offer repositories for sharing data produced by their staff or students. These may support discoverability and short-term storage, but may not provide services such as in-house curation, active preservation, or multiple tiers of access controls. Check your institution’s and funder’s guidance and policies before using them for sensitive or long-lived data.

Sharing as journal supplementary material

You may also consider sharing data as supplementary materials alongside journal articles. While this can provide immediate access linked to publications, journals typically lack the infrastructure for long-term preservation, rich metadata, and appropriate access control.

Self-managed dissemination and preservation

You may also consider hosting your data on a project website or sharing it informally with colleagues. However, this approach would need significant investment to align with the FAIR data principles and comes with risks such as uncertain sustainability, no guaranteed long-term preservation and an increased burden to manage requests and maintain the data.

Licensing and access conditions

To support responsible reuse and clarify user rights, you should always select an appropriate licence for reuse. Trustworthy repositories can help you choose a suitable licence and guide you in applying appropriate conditions.

You should also consider:

• What information was provided to participants in the consent and communication materials regarding data sharing and reuse.
• Whether multiple versions of the data can be made available, possibly at different access levels, to enable sharing that is “as open as possible, as closed as necessary”.
• Whether a dissemination embargo is needed before the data become available to allow for your publication.