Data Labs in the European AI Ecosystem

The BDVA (Big Data Value Association) community has launched a new initiative to map, connect European projects related to Data Labs. As an active contributor to this European BDVA initiative, Dr. Denia Kanellopoulou is actively co-shaping this framework within the BDVA community to build a stronger, more organized European AI ecosystem.

What are Data Labs and Why Do They Matter? Officially recognized in the European Data Union Strategy, Data Labs are essential building blocks for Europe’s AI future. These specialized facilities connect data holders with common European Data Spaces, bridge the gap between data, AI communities, provide services that transform high-quality data into real, working AI applications.

Ecosystem Mapping: Connecting the Pillars To understand how Data Labs interact with existing European infrastructures, BDVA developed a comprehensive ecosystem mapping, detailed in the official file titled "Data-Labs-Ecosystem-mapping.pdf". This initiative explores synergies, challenges across several core pillars.

BDVA i-Spaces accelerate AI uptake, support Data Labs with core services for data quality, networking, though establishing a formal labeling process to recognize certain i-Spaces as Data Labs remains a challenge.

EDIHs (European Digital Innovation Hubs) act as Experience Centres for AI, helping companies navigate the EU AI Act. They function as brokers directing users to Data Labs, though formal coordination mechanisms are still being operationalised.

Data Spaces act as the primary source of EU-wide data under clear usage conditions. Data Labs serve as a service layer that processes, transforms this data into AI-ready assets, though data provider hesitation remains a barrier.

AI TEFs (Testing and Experimentation Facilities) provide Data Labs with access to real-world experimental data. Together, they form a continuous loop from data preparation to validation, though TEF data is often sensitive or proprietary.

AI Factories bring together computing power, data, talent. The first Data Labs will be embedded within AI Factories through EuroHPC, where AI Factories provide compute, Data Labs provide the data services.

Strategic Priorities of the Initiative The project focuses on several main pillars to ensure long-term success. Strategic Guidance helps decision-makers understand where to invest, how to build future funding programs. The AI-Ready Data priority ensures AI Factories have easy access to high-quality data for training advanced models. For Sustainability, the focus is on finding the right economic models to keep facilities running long-term. Finally, Coordinated Governance establishes frameworks for data rights, intellectual property, liability across hubs.

To learn more about the focus, objectives, priorities of this project, visit the BDVA initiative in Data Labs – Ecosystem mapping