Context
The Open Dataspace Lab (ODL) is a federated, sovereign data-sharing environment designed to enable secure collaboration across organisations working with environmental, geospatial, and sensor-based data. Hosted by dotSPACE and developed in partnership with stakeholders including the Netherlands Food and Consumer Product Safety Authority (Nederlandse Voedsel- en Warenautoriteit – NVWA) and Rijkswaterstaat, ODL provides a controlled digital environment where participants can analyse and derive insights from data such as satellite imagery, drone footage, and sonar recordings without transferring raw datasets between parties. This compute-to-data approach ensures that data owners retain full sovereignty over their datasets while enabling cross-organisational analysis and innovation.
Built on decentralised principles aligned with European data sovereignty frameworks, ODL incorporates containerised analytics, policy-driven access control, and secure governance mechanisms to support trusted workflows. Its architecture reflects European priorities for interoperable, standards-based data spaces that respect privacy and regulatory requirements.
ODL is intended for public authorities, research institutes, technology companies, and innovation projects that require secure, compliant, and scalable environments to collaborate on real-world use cases. By facilitating responsible data sharing and co-creation of insights without raw data exchange, ODL catalyses public-sector innovation, accelerates operational efficiencies, and contributes to resilient and sovereign data ecosystems in Europe.
Objectives
The ODL aims to address a fundamental challenge in the public sector: how to securely collaborate on sensitive and high-value data without compromising data sovereignty, regulatory compliance, or organisational control. Public authorities increasingly rely on geospatial, environmental, and sensor-based datasets from multiple sources, yet legal, technical, and governance barriers often prevent effective cross-organisational analysis.
ODL’s primary objective is to enable trusted, federated data collaboration through a compute-to-data architecture in which algorithms move to the data rather than data being transferred between parties. This ensures that data owners retain full control over access policies, usage conditions, and compliance requirements while still enabling joint analytics and AI applications.
The project focuses on four concrete goals:
- Establish a secure, containerised analytics environment that supports advanced AI and data workflows.
- Embed policy-driven access control and governance mechanisms aligned with EU frameworks such as the AI Act and the Data Act.
- Ensure interoperability with European dataspace standards to support cross-domain and cross-border collaboration.
- Demonstrate real-world public-sector use cases that generate measurable operational and societal impact.
Through these objectives, ODL strengthens digital sovereignty, accelerates responsible innovation, and builds a scalable foundation for resilient European data ecosystems
Implementation
The ODL is implemented through a collaborative and adaptive framework that integrates technological development, governance design, and ecosystem coordination. The initiative operates within a public–private innovation setting, enabling cooperation between public authorities, research organisations, and technology partners while remaining aligned with evolving European data space principles.
The project follows a phased approach, combining strategic direction with iterative development. A light but structured governance model ensures alignment with regulatory requirements and broader digital policy frameworks, while operational coordination supports the gradual deployment of infrastructure components and the onboarding of use cases. Technical implementation focuses on secure, federated architectures and trusted processing environments that can evolve alongside emerging standards and technological advancements.
Resources are distributed across infrastructure enablement, specialised expertise in data and AI, governance and compliance alignment, and ecosystem development. The structure is designed to remain flexible, allowing adaptation to changing policy landscapes, stakeholder needs, and innovation opportunities.
Stakeholder engagement is embedded throughout the lifecycle via consultation, collaborative experimentation, and knowledge exchange. Communication and dissemination activities support transparency, shared learning, and connection to broader European initiatives.
This implementation approach ensures scalability, resilience, and long-term sustainability while maintaining strategic flexibility.