Data Collaboratives Programme (DCP)


The Data Collaboratives Programme seeks to support businesses to explore how to implement and manage mechanisms that allow for safe and economically sustainable data sharing. Through this programme, businesses interested in data sharing for meaningful innovation, can refer to the Trusted Data Sharing Framework for a systematic approach to understanding the broad considerations for establishing trusted data sharing partnerships.

The programme also offers Data Regulatory Sandbox to businesses and their data partners to explore and pilot innovative use of data in a safe “environment”, in consultation with IMDA and PDPC. The Sandbox reduces uncertainty in compliance to current and planned policies, and limits the exposure of companies and consumers.

Businesses who are interested to explore cross border data innovation may look into the programme for relevant resources and support. 

Trusted Data Sharing Framework

IMDA has released the Trusted Data Sharing Framework to help companies overcome challenges in addressing trust between data providers and develop “trusted data”.  The framework helps companies by establishing a baseline “common data sharing language” and systematic approach to understanding the broad considerations for establishing trusted data sharing partnerships.

trusted data sharing framework

Download the framework and resources here:

Data Regulatory Sandbox

There are three stages in the Data Regulatory Sandbox:

The stages are not necessarily sequential, and dependent on the company’s use case and readiness.

Data Collaborative Programme

Key considerations to leverage Data Regulatory Sandbox

Innovative:  The use case should demonstrate how data can be used to derive new value or creation of new products, which would not be possible under the current regulation

Benefit the public: The use case should not likely to have any adverse impact on the consumers

Ready and concrete use case: The use case should not be hypothetical. It should have sufficient interest from the relevant stakeholders and has clear outcomes

Risks assessment and mitigation: The risks and impact should be assessed and mitigated, and there should be reasonable effort to protect the interest of the individual

Case Study: Public-Private Data Collaboration (626.40KB)

Data Sharing Agreements

Bilateral Data Sharing

Access the Bilateral DSA Sample here.


Multilateral Data Sharing

Access the Multilateral DSA Sample here


Multilateral Data Sharing (with Lead)

Access the Multilateral (with Lead) DSA Sample here

How to apply?

Interested companies can approach IMDA ( to leverage the Data Regulatory Sandbox to explore and pilot innovative use of data to support commercialisation of products and services.

Other useful information

Personal Data Protection Act (PDPA) & the Advisory Guidelines

Businesses planning to share personal data, within and between companies, can read up on the PDPAand the Advisory Guidelines.

External resources

For broad, common data sharing scenarios, particularly in relation to training AI models, can refer to the three model data use agreements published by Microsoft, and the two agreements optimized for “open” data are posted on GitHub here and here for community input.

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Last updated on: 28 Mar 2022