When two or more organizations work together, data often moves with them: Between systems, across teams, and sometimes across borders. But without clear guardrails in place, that movement can create risk, confusion, or even legal exposure.
A well-crafted data sharing agreement ensures everyone involved knows exactly what can be shared, how it should be handled, and what safeguards are required. It’s the blueprint for responsible collaboration, protecting privacy, aligning with compliance requirements, and creating mutual trust from day one.
A data sharing agreement is a formal document that outlines how data will be shared between two or more parties. It defines what data is being shared, for what purpose, under what conditions, and with what safeguards.
Typically, a data sharing agreement includes:
The identities of all parties involved
The types of data being shared (e.g., personal, anonymized, aggregated)
The purpose of data sharing
Data access controls and usage restrictions
Retention periods and deletion protocols
Security measures and encryption requirements
Legal and regulatory compliance clauses
A well-crafted data sharing agreement ensures that both the data provider and recipient know their responsibilities and liabilities, reducing the risk of misuse or breach.
Sharing data without a formal agreement in place opens the door to unnecessary risk. Sensitive or regulated information can be mishandled, left unsecured, or accessed by individuals who were never authorized. Even when working with trusted partners, a lack of clarity can lead to misaligned expectations, compliance failures, or legal consequences.
A data sharing agreement brings structure and accountability to the process. It sets clear boundaries for how data can be used, outlines each party’s responsibilities, and ensures that both sides adhere to relevant privacy regulations. Just as importantly, it promotes transparency and trust, both internally and with external stakeholders.
You should consider a data sharing agreement any time data is exchanged outside your organization’s direct control. Common scenarios include:
Collaborating with research partners on health or social science projects
Sharing user or customer data with third-party service providers
Participating in multi-party data analysis initiatives
Cross-border data transfers between different jurisdictions
Using cloud vendors or software platforms that process sensitive information
If the data is personal, regulated, or business-critical, a data sharing agreement is more than a formality, it’s a necessity.
To ensure your data sharing agreement is both legally sound and practically useful, it's important to go beyond generic templates. A strong agreement should reflect the realities of your data, your partnerships, and your regulatory environment. Here are key best practices to guide the process:
1. Be specific about the data
Don’t leave room for interpretation. Clearly define what types of data will be shared, such as personal identifiers, anonymized records, or aggregated datasets, and be explicit about what is excluded. This not only sets expectations but also reduces the risk of unauthorized or accidental over-sharing.
2. Align with privacy regulations
Make sure your agreement complies with the relevant legal frameworks, whether that’s GDPR, HIPAA, or local data protection laws. This includes addressing consent requirements, lawful basis for processing, cross-border data transfer conditions, and the rights of data subjects. Non-compliance can lead to costly fines and loss of trust.
3. Define roles clearly
Clarify who is responsible for what. Identify whether each party acts as a data controller, data processor, or joint controller, and specify their respective duties. Ambiguity in these roles can lead to legal gaps and make it unclear who is accountable in the event of an incident.
4. Include technical safeguards
A data sharing agreement should specify the minimum technical standards required to protect the data. This includes encryption for data in transit and at rest, access controls, secure authentication, and audit trails. These details show that security is not just assumed, it’s enforceable.
5. Plan for breaches
Even with safeguards, breaches can happen. Your agreement should outline what steps each party must take in the event of a data incident: how quickly breaches should be reported, who needs to be notified, and what mitigation actions are required. This ensures a coordinated and timely response when it matters most.
6. Set time limits
Define how long the shared data can be stored or used, and what should happen when that period ends. Should the data be deleted, returned, or archived securely? Time-bound limits reduce the risk of data being held indefinitely and falling out of compliance.
7. Review and update regularly
Data partnerships evolve, and so should your agreements. Build in review periods, quarterly, annually, or aligned with project milestones, and update the agreement when new risks, regulations, or data types emerge. A stagnant data sharing agreement is a liability; a living one adds value.
A data sharing agreement sets the terms, but the right technology makes those terms enforceable. At Partisia, we help organizations strengthen their data sharing frameworks by minimizing the need to expose sensitive data in the first place.
Using Multi-Party Computation (MPC), we enable secure collaboration where each party retains full control of their data. Even when working across borders or with multiple stakeholders, sensitive information stays private throughout the entire process.
With MPC:
Each organization shares insights without revealing raw data
No single party ever gains full access to the dataset
Joint results are accurate, auditable, and privacy-preserving
This model complements and elevates your data sharing agreement turning documented trust into technical assurance. Whether you’re entering a cross-industry partnership, coordinating multi-institution research, or managing regulatory risk, Partisia helps ensure your agreements are backed by architecture that delivers security and compliance by design.
The future of data collaboration is about not exposing data in the first place. With Multi-Party Computation, we enable organizations to generate insights together without giving up control of their data.
Stay ahead of the curve with expert insights on privacy-first data sharing, compliance strategies, and cutting-edge cryptographic technologies like Multi-Party Computation.
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MPC strengthens data sharing agreements by enabling secure data collaboration without exposing raw data. It ensures each party can contribute to joint analysis while keeping their own data private, reducing compliance and security risks.