Government data sharing is more than publishing data on open data portals. Government teams are critical to sharing all kinds of data across the public, private, and third sector by supporting the infrastructure that data sharing relies on. Infrastructure that:
- Accelerates academic research, such as the Administrative Data Research UK service that provides researchers access to joined-up and de-identified administrative data held by agencies across government for policy-related research.
- Enables teams across government to build life-event based services, such as Singapore’s APEX platform that allows public administrators to rely on data from different government agencies to take decisions about the services a person is entitled to receive.
- Grows nascent, high growth potential sectors of the economy, such as Data Cellar in the EU that is setting up a dataspace for exchange of data to support the development of energy communities.
The work of government teams is so important for the flow of data between actors because of the position teams have within data ecosystems. Government teams:
- Generate and hold data that is valuable to other actors.
- Rely on data for decision-making, both in policy making and public service delivery.
- Act as established and neutral coordinators of other actors, from different stakeholder groups.
Thanks to this positioning, government teams can be leaders on data sharing and use it to achieve their priorities. Teams can be leaders by (1) sharing data they control with other actors, inside or outside of government, or (2) facilitating data sharing between other actors, for example by taking advantage of their position as a neutral coordinator to act as trusted stewards of other actors’ data or provide data sharing infrastructure.
A sliding scale of data sharing projects
As the examples above demonstrate, government projects that involve data sharing have wide ranging motivations. We have grouped different kinds of data sharing projects by focus and scale.
Source: Oxford Insights
Small scale, Use case focused
These are usually tightly bound projects or collaborations that a team is running to solve a specific problem. The project may be characterised as solving a data sharing problem or the project may seem to be unrelated to data sharing, but it emerges as a necessary part of working with other actors to solve the target problem.
| Example:
The UK Ministry of Justice’s BOLD programme links data from across UK government agencies to share with government analysts who are working on a set of prioritised, complex policy problems faced by the justice department. |
Medium scale, Challenge area focused
These are projects that are focused on facilitating data sharing in a particular challenge area, which may be a sector, developmental challenge, or government mission. These projects aim to help actors working on this challenge area but currently face obstacles that relate to data access. These obstacles may be caused by a lack of trust, infrastructure, IP concerns, or privacy concerns, among others. Government teams set up projects to alleviate these obstacles.
| Example:
The Mobility Dataspace in Germany is a marketplace with over 150 members, including German companies (e.g. Deutsche Bahn), and international companies (e.g. Vodafone, the Luxembourg Post Office). The dataspace aims to unlock privately held data to enable innovation for a safer and more environmentally efficient mobility sector. |
Large scale, Enabling infrastructure focused
These are projects that are focused on providing the reusable infrastructure for many actors to share data, across a wide range of challenge areas. Teams provide the technical, legal, and governance infrastructure for actors to share data independently, or with varying levels of support.
| Example:
The UK’s Integrated Data Service provides the infrastructure to government agencies for hosting, processing and providing controlled access to researchers and academics to de-identified, critical national data assets that enable the UK’s research community to work on problems relating to the public good. |
Different projects, similar challenges
Across the scales and focuses, government teams can face similar challenges to data sharing. Challenges relate to legal and regulatory know-how, designing robust and secure technical data sharing infrastructure, and setting up responsive governance that guarantees the project’s future.
Legal and regulatory challenges
Government teams must ensure that sharing data for their project is lawful. However, teams may not have experience of applying data governance and/or sector-specific legal frameworks to the context of data sharing. This can make data sharing projects a non-starter for some teams.
Strong regulatory agencies with the resources to engage with teams directly and provide replicable guidance on implementing legislation can alleviate this challenge. However, a lack of capacity within the relevant data governance or sector-specific regulator on data sharing can itself be a challenge for projects seeking support.
Part of ensuring the lawfulness of a data sharing project is the creation of robust data sharing agreements between all parties. Teams may lack experience in drafting data sharing agreements, and the components to include. Other teams may find the process of arriving at agreements is an obstacle. This is because agreements lay out roles and responsibilities across parties that take time to negotiate. These roles and responsibilities will be new, and they may involve a transfer of trust, or a new set of tasks for a team.
If the data being shared includes personal information, managing the consent of data subjects becomes critical. This includes obtaining clear and informed consent for data processing beyond the purposes that consent was originally provided for and may require data subjects to opt in or opt out of this further processing, creating not only legal but citizen engagement challenges for teams.
Technical challenges
Data sharing projects face the same issues relating to data standards and quality that teams face in all digital projects. These can be amplified in data sharing projects as often data standards need to be met across multiple organisations.
In addition to these broader data management challenges, data sharing introduces its own unique set of challenges. Decisions about data architecture—such as whether to adopt a centralized, decentralized, or hybrid approach—are critical to how data can be stored, accessed, and protected by multiple parties. Likewise, teams may want to explore using more advanced privacy-preserving technologies, such as differential privacy or using synthetic data, if they are sharing sensitive data. While these emerging techniques create new opportunities for data sharing and are becoming more common, many government teams do not have the skills or experience to apply them.
Governance challenges
Data sharing projects carry different risks depending on the data being shared, with whom and for what purposes. A challenge teams face is setting up the governance of their project so that it responds to key risks, while not hindering the operations or objectives of the project by making processes overly cumbersome or lengthy.
Data sharing involves the redistribution of value. Usually, the aim is to open up data to more parties so that they can make use of the data, and generate value from it too. As a result, data sharing projects can advantage some groups or individuals over others. Government teams face the challenge of ensuring the selection of data users, for example through procurement or application processes, is fair, and that the value created by data sharing reaches those who contribute to the data’s generation.
A further, related challenge for data sharing projects run by government teams is that the value of the project is not always directly realised within the agency itself. It may create value for the public, or groups of the public. Often, teams find it hard to measure this value and communicate within government. Consequently, projects may struggle to secure longer term funding beyond pilot stages.
Succeeding in data sharing projects
As a team interested in starting work on data sharing it can make sense to start at the small end of the scale. There are likely already some data sharing practices in place to build on and running a dedicated project can demonstrate capability, and lead to learnings that can be built into more widely applicable policies.
As a team already experienced with data sharing, it makes sense to think about how to measure and communicate the value of the projects you have underway, as well as to consider how to make these projects scalable and replicable by turning them into cross-government services and policies.
At Oxford Insights we have extensive experience with data sharing projects, having supported governments across four continents through different stages of their data sharing projects. We offer support on:
- Design: Creating pilot designs for government data sharing programmes.
- Delivery: Partnering to implement data sharing programmes in government.
- Evaluation: Assessing the impact of the data sharing to develop recommendations and demonstrate value.
- Policy and guidance: Developing reusable strategies and guidelines to govern data sharing.
You can learn more about our previous experience here.
