21 October 2026

Data sharing and data pooling in Switzerland: an overview of the different types of agreement

  • Articles
  • Legal
  • Data / Technology / IP

Data creates value when it is shared, combined and put to use. In the absence of a comprehensive Swiss legal framework, contractual arrangements play a crucial role. This article provides an overview of the most common contractual models for data sharing and data pooling in Switzerland.

  • Dr. Martin Eckert

    Legal Partner

  • Jannine Rüegg

    Junior Legal Associate

Data is regarded as a key raw material of the digital economy. However, it only realises its economic value when it is used, analysed, linked and shared with third parties. As Switzerland lacks a comprehensive legal framework governing the sharing and pooling of data, careful contractual structuring is essential to enable companies to benefit from these activities without losing control over their data. This article provides an overview of the most common types of agreement.

I. What is «non-personal data»?

Unlike personal data, «non-personal data» is not defined by statute under Swiss law. The term generally refers to data that does not constitute personal data within the meaning of the Data Protection Act – i.e. data that does not relate to an identified or identifiable natural person and is not protected by intellectual property law. Examples include production and machine data, digitised know-how, transaction data, meteorological data and sufficiently anonymised personal data. Switzerland has no specific regulations governing non-personal data. However, specific legal provisions must be observed, including those concerning trade secrets, unfair competition, competition law in the case of data pooling and data protection law where personal data is involved.

II. What is meant by «data sharing» and «data pooling»?

«Data sharing» means making data available to third parties for use or further use. The focus is on providing authorised access to datasets in order to generate additional economic or social value. Arrangements may range from the one-off transfer of a dataset and ongoing access to updated datasets to a reciprocal exchange between several parties. «Data pooling» refers to the combining of data from various sources or participants in a shared data pool, such as an industry, research or AI training data pool.

III. What are the opportunities and risks?

Data sharing unlocks economic and organisational potential: shared data can enable new business models, drive data-driven innovation, improve products and services, and provide a more reliable basis for analyses and forecasts. For businesses, this can lead to efficiency gains, additional revenue opportunities and greater competitiveness.

However, these opportunities are accompanied by certain risks. Foremost among them are the potential loss of control over the shared data, the need to protect trade secrets and competitively sensitive information, and the often difficult enforcement of agreed restrictions on use. Further considerations include data quality, the cost of preparing data for sharing and technical dependencies on platforms or service providers.

As Switzerland lacks a comprehensive legal framework governing non-personal or technical data, contractual arrangements for managing these risks are of central importance.

IV. Different types of data-sharing and data-pooling agreement

In data law practice, various types of agreement have emerged, which are generally classified as innominate contracts. The appropriate type of data-sharing or data-pooling agreement, and the key matters it should address, depend on the precise nature of the collaboration. Certain points should, however, be clarified in every agreement: which data is to be made available; for what purpose it may be used; the format in which, and infrastructure through which, access is to be provided; and whether a fee is payable. The agreement should also address distribution rights, commercial use, use for training AI models, confidentiality, trade secrets, intellectual property rights, warranties, liability, audit rights and any additional services, such as support, maintenance or hosting.

Depending on the form and specific structure of the data exchange and the interests of the parties involved, additional contractual priorities and regulatory requirements may arise. The types of agreement described below are not mutually exclusive; they may overlap or be combined.

1. One-off provision of data – Technical Data Transfer Agreement

Bei der einmaligen, einseitigen Übermittlung eines Datensatzes stehen in der Datentransfer-Vereinbarung die genaue Beschreibung der Daten, das technische Format und der zulässige Nutzungsumfang im Vordergrund. Dieses Modell eignet sich insbesondere für einzelne Projekte, Pilotversuche oder Testzwecke, bei denen eine Partei punktuell auf bestimmte Datengrundlagen zugreifen soll. Denkbar ist etwa, dass ein Industrieunternehmen einem Technologieanbieter ausgewählte Maschinendaten zur Verfügung stellt, damit dieser ein neues Wartungs- oder Analysemodell testen kann. Fragen der laufenden Aktualisierung und dauerhaften Verfügbarkeit treten demgegenüber regelmässig in den Hintergrund.

2. Recurring provision of data – Subscription Agreement for Access to Technical Data

Where one party provides data on a regular and ongoing basis, this typically creates a long-term relationship of use. In Switzerland, this is referred to as a subscription contract or a Subscription Agreement for Access to Technical Data. Typically, the data holder undertakes to provide updated data. Accordingly, the currency and availability of the data, the fee, termination rights and any monitoring or audit rights become significantly more important than in the case of a one-off transfer. A practical example would be a machine manufacturer that receives operational or quality data from its customers on an ongoing basis in order to improve its products, determine maintenance intervals more accurately or identify sources of error at an early stage.

3. Reciprocal exchange of technical data – Technical Data Exchange Agreement

In a reciprocal exchange, two or more parties make their respective datasets available and use the insights generated from them. This model may be useful, for example, where several companies within an industry exchange non-sensitive operational data to identify trends more effectively or compare processes. For instance, a number of architectural or planning firms could exchange anonymised information on the processing times for planning permission applications in order to assess planning processes more realistically. In addition to the general regulatory provisions, such agreements must specifically address reciprocity, access to newly generated datasets, the use of joint analyses or results, and control over their further use.

4. Data Pooling Agreement

In data pooling, several participants contribute data to a shared data pool. Typical examples include industry pools, research data pools, health data platforms (which are subject to stringent personal data protection requirements), mobility data repositories and AI training data pools. In addition to the general regulatory matters, the agreement must specifically address the governance of the data pool, the admission and exclusion of participants, access rights and the distribution of revenue generated through use. Rights in aggregated data, as well as in AI models and analyses, must also be clarified. As the pooling and shared use of data may involve competitively sensitive information, competition law requirements must also be observed.

From a legal perspective, a data pool of this kind often resembles a simple partnership, an association, a cooperative or a consortium, supplemented by a Data Pooling Agreement.

5. Data Trust Model

Under the Data Trust Model, a neutral trustee manages the data and access to it, while the participants remain the data owners. This model is particularly suitable for sensitive datasets and is increasingly used internationally. It is characterised by uniform governance and stringent compliance requirements.

In addition to the general regulatory provisions, the trustee’s duties and powers, the conditions governing access to the data, and the participants’ control and audit rights must be specifically defined.

6. Data Cooperation Agreement

A Data Cooperation Agreement focuses on the shared use of data infrastructure. This model is particularly suitable where several parties operate or finance a shared platform through which data is made available, processed or analysed. In addition to the general provisions, the agreement should specify how the platform is to be operated and financed, which party is responsible for operation and support, and which requirements apply to cybersecurity, interfaces and APIs.

7. Research and Innovation Data Pool

Research and innovation data pools bring together data from various stakeholders for a joint research or development project. This model is frequently used by universities, in the pharmaceutical industry, in other industrial sectors and in AI projects. In addition to the general regulatory matters, particular attention must be paid to intellectual property rights, publication rights and confidentiality. The agreement must also specify how results generated through the collaboration are to be handled and whether, and to what extent, open-data components are envisaged.

8. AI Data Pooling Agreement

In AI data pooling, data from several parties is combined in a shared data pool for the development, training or optimisation of AI models. AI Data Pooling Agreements of this kind have become significantly more important since 2024/2025. In addition to the general regulatory matters, it is particularly important to clarify whether the data may be used for training, who holds the rights in the models and whether fine-tuning is permitted. The agreement must also stipulate whether the AI provider may reuse the data and how data deletion and audits are to be organised.

V. Technical implementation via an API – API Terms of Use

The types of agreement described above determine which data may be shared or jointly used, for which purposes and on what terms. This must be distinguished from the technical means of implementation. Application Programming Interfaces (APIs) are frequently used for this purpose. An API connects two software systems and enables data to be transferred automatically in accordance with defined rules. For example, current operational data from a machine can be transmitted directly to a service provider’s analysis software without files having to be exported and sent manually at regular intervals.

An API is therefore not a distinct type of agreement, but a technical means of transferring data. It is particularly useful where data is provided and updated on an ongoing basis, for example under a subscription arrangement, in a data pool or as part of a data cooperation. For a one-off data transfer, however, the simple transfer of a file is often sufficient. Whether an API is required therefore depends on the frequency and volume of the data exchange and on how current the data needs to be.

Where an API is used, the terms governing technical access must be defined in addition to the provisions of the relevant data-sharing or data-pooling agreement. In particular, it must be clarified who may use the interface, how access is secured, what level of availability is required, and who is responsible for maintenance and support. The agreement should also stipulate how access is to be blocked upon termination. These technical and operational matters can be addressed in supplementary API Terms of Use, platform terms or hosting terms, while the underlying agreement continues to determine which data may be used and for which purposes.

VI. Conclusion and recommendation

Data sharing and data pooling offer companies a wide range of economic and organisational opportunities, but require a contractual framework tailored to the particular collaboration. Companies should therefore determine at an early stage which data they wish to share or pool, with whom, for which purpose and on what terms. On that basis, the appropriate type of agreement should be selected and supplemented by the provisions required for technical implementation, particularly in relation to APIs, platforms or hosting. A clear contractual framework protects against loss of control and provides the necessary certainty to make targeted use of the potential offered by data sharing and data pooling. Our team would be pleased to assist you with this.
Back