The Evolution of Data Sharing

Sharing data effectively is not  a technical challenge, it’s a socio-technical challenge that requires blending human trust, legal frameworks, and digital architecture. Over the years, the drive to securely and fairly share data among organizations and individuals has led to the creation of several distinct inter-organisational data sharing models. Below is presented the current data economy landscape, the pros and cons, and why one model is rising to the top.

Data Trusts act as strict legal guardians for information, operating under the established rules of Trust Law to manage datasets on behalf of their contributors. By placing data under the control of an independent trustee who is legally accountable for granting access and use in accordance with the Trust Instrument rules and regs that are co-designed with data donors, this model fosters strong trust between providers and consumers. However, that level of legal liability makes trusts expensive to operate, and navigating the complex legalities can make them slow to establish, particularly when crossing international borders, and difficult to make financial sustainable.

Data Foundations take the approach of an independent, trusted mediator rather than a centralized vault, brokering secure agreements between data providers and consumers. Instead of permanently storing data in a single repository, foundations enable dynamic, on-demand data linking where information is only accessed and combined for specific, pre-approved projects. This targeted approach minimizes unnecessary data retention and significantly reduces the security risks associated with holding large amounts of sensitive information in a single location, and is most suitable for socially responsible data use as opposed to commercial usage for similar reasons as with Data Trusts.

Data Co-operatives operate as democratic, member-owned unions that combine data from different sources to give everyday individuals and smaller organizations collective power against massive data-processing corporations. Based on Co-operative Law, members voluntarily contribute their data while retaining their underlying rights, voting together on the rules for access, sharing, and value distribution. While this model prioritizes data sovereignty and fairness, managing a democratic system requires significant operational effort and comes with complex legal compliance costs.

Data Marketplaces function like digital markets designed to facilitate the commercial discovery, licensing, and exchange of data products. Historically, these platforms have treated data sharing as a purely technical challenge, focusing heavily on matching algorithms, platform architecture, and seamless payment processes. They provide a good way to buy and sell data, but because they often lack built-in governance and sovereignty protections, they frequently struggle with real-world adoption. Data owners remain hesitant to openly sell their assets without specialist legal, sovereignty and usage guarantees.

Data Spaces represent a federated, decentralised approach to trustworthy and technologically simple data sharing between organisations, often in a business context. Directly negotiated contracts between provider and consumer must align with the meta-level rules and regulations of the Data Space itself – the ‘Rulebook’ - and fulfil the ‘Dataset Policies’ (the restrictions and limits attached to an individual dataset) and are underpinned by existing Contract Law. Data Spaces limit access to fellow members of the Data Space, but Data Spaces can also be linked and data shared under the same set of Rulebook and Policy restrictions to members of federated Data Spaces. Data Spaces can also include data marketplaces for purchasing services. By combining this governance framework with plug-and-play digital infrastructure and integration capabilities, Data Spaces lower the barrier to entry for businesses of all sizes, and provide a scalable and sustainable solution for modern inter-organisational data sharing. However, once the data is released to a consumer there is no effective way to ensure that the data is used for the agreed purposes within the terms of the contract, thus weakening long-term data sovereignty.

Overall, Data Spaces are emerging as the most viable long-term solution, especially in the commercial domain, because they provide trusted, shared governance and technical frameworks adaptable to negotiated individual context; are not dependent on complex Trust or Co-operative Law; and most importantly can be both scalable and financially sustainable through the federation of Data Spaces and the incorporation of data marketplaces.