The purpose of this framework is to guide organizations through the data sharing journey and outline key considerations for organizations to take into account when planning data partnerships.

The framework is organized into four parts:

• Part 1: Data Sharing Strategy

• Part 2: Legal and Regulatory Considerations

• Part 3: Technical and Organization Considerations

• Part 4: Operationalizing Data Sharing

Organizations may choose to use them in any sequence, depending on their needs, but should not omit any part.

Key Considerations in Data Sharing

The motivation to share data typically stems from business needs such as the creation of new services, lowering business costs, detection of fraud, regulatory compliance, etc. The business motivations will, in turn, help data partners agree on the intended outcomes of their data-sharing activities.

Key Roles in Data Sharing

Data can be said to have been “shared” when it is made available by a “Data Provider” to one or more organizations (each, a “Data Consumer”).

• Data Provider: Creators, licensees, or sellers of data.

• Data Consumer: Recipients collecting or buying external data for their purposes, such as to generate additional insights and supplement internal functions.

• Authority: An institution or organization empowered to operate a supervisory function related to the ecosystem. May refer to the regulator (or other governing bodies), or industry bodies with oversight mandates or other practical influence (e.g., industry associations, standards institutes). Usually, not directly involved in data sharing, but can influence the data-sharing activities through legislative reviews, issuance of the guidelines, standards, or accreditation schemes.

• Data Service Providers: Organizations providing data services supporting the data-sharing ecosystem.

Trust Principles

Embedded throughout the framework is the concept of trust. As data sharing often involves the movement of data assets, it is important to establish that each party would be able to handle and manage the data asset responsibly.

This framework introduces 6 Trust Principles:

• Transparency

• Accessibility

• Standardization

• Fairness and Ethics

• Accountability

• Security and Data Integrity

These are foundations for forming a trusted data-sharing partnership.