How data spaces can guide innovation in Europe

A manifesto on data spaces from INESC TEC emphasises the need to remove barriers to data sharing and highlights the role of a data space connector.

Data spaces are emerging as an approach for the decentralised sharing and pooling of data in the energy and other sectors and are considered to form the cornerstone for Europe’s digital transition.

However, while numerous initiatives are under way towards their development, there are multiple challenges to overcome such as interoperability and privacy but ultimately in how data intelligence can be used to generate value and can be monetised from, according to INESC TEC, Portugal’s largest research organisation, in its manifesto document.

Arguing for bridging data silos and fostering secure, intelligent collaboration and decentralised yet coordinated governance that allows organisations to retain control over their data while promoting data sharing and economic growth, INESC TEC highlights key challenges the next generation data space should address.

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These include large scale, highly available heterogeneous data storage encompassing a plethora of data sources, efficient and unified data access, querying and quality of service in terms of scale or throughput and identity modules to decentralise the identity mechanisms.

Data usage policies should move away from approaches based on the goodwill of participants and data sovereignty enforcement requires orthogonal control over heterogeneous data sources, i.e. effective policy control requires privacy-preserving capabilities for data at rest and while being queried.

INESC TEC then go on to present the data space connector that is under development, based on the International Data Spaces’ dataspace protocol 2024-1 that is due to become an ISO standard.

Key features include adopting a data plane that closely links with data sources, extending querying capabilities across domains (i.e. energy, health, industry, etc.), addressing privacy needs and supports a near-real-time exchange of information with state-of-the-art performance, i.e., supporting high throughput and larger data payloads

The provision of data services through this data space connector will allow use cases to benefit from a wide variety of data, equipped with the capability to discover and browse structured, unstructured, timestamp-based data, states the manifesto.

INESC TEC researcher Fábio Coelho says that the boom of AI usage being witnessed is becoming the larger consumer of data.

“Within the European values for privacy and sovereignty, we need to equip the data spaces ecosystem to serve AI, breaking data silos, while preserving boundaries. Our connector will directly serve AI models with data, enabling to lodge proactive AI agents, while deploying polyglot data access capabilities, including semantics.”

Renewable energy communities and data cooperatives

As a foundational use case, INESC TEC present a demonstration partnership with the Cooperativa Eléctrica do Vale d’Este (CEVE), a northern Portugal energy cooperative acting as a local DSO and retailer to around 9,000 customers.

A comprehensive range of monitoring equipment including total and individual energy meters, smart plugs, ambient temperature, and humidity sensors were deployed along with PV, electric vehicles, heat pumps and electrical water heaters.

The first data sharing use case under demonstration was the instantiation of the renewable energy community with optimisation of the capacity of the distributed energy resources and simulation of their operation – data that can now be shared with organisations working to mitigate energy poverty.

A second use case was to compute sustainability indicators and business models, such as the traceability of green energy supply within the community or creation of ‘happy hours’ for community EV charging.

INESC TEC adds that other potential use cases with data sharing in renewable energy communities include boosting energy efficiency actions at the community level and quantifying and predicting the energy poverty risk.

Some of the projects in which the scope, data volume and diversity of use cases within the data sharing community are expanding include ENPOWER, HEDGE-IoT, AI-EFFECT and INSIEME.

In conclusion INESC TEC notes that as its data connector solution matures, engagement will be made with the International Data Spaces Association to seek its certification.