Data Spaces Kit: a guide to digital transformation and data economy

Data gain more value when they can be used with context, quality and clear rules. However, sharing them between companies, administrations and other actors requires a resolution of technical, legal, organizational and security issues.

The Data Spaces Kit The programme, managed by Red.es and funded by the European Union through the Recovery, Transformation and Resilience Plan - NextGenerationEU - helped public and private entities to enter existing sectoral data spaces.

The aim was not to subsidize a generic tool or an internal database. effective and accredited incorporation into an eligible data space.

September 2026 update. The deadline for applications was 31 March 2026. The website of Red.es indicates that the applications received exceeded the available budget and already published decisions of the file. This article retains the information of the call to explain the programme and its requirements; it should not be interpreted as an open call.

What is a data space

A data space is an environment in which different organizations can share, access and use information under common rules. It does not require all data to end up in a single repository. It can operate through a federated architecture in which each participant retains control over its assets and agrees how they are discovered, exchanged and used.

For the exchange to be useful and reliable, several layers are needed:

• Governance: who is involved, what responsibilities he assumes and how decisions are made.
• Identity and trust: how participants are checked and access is allowed.
• Interoperability: formats, vocabularies, APIs and mechanisms that allow you to understand and move the data.
• Security and privacy: access, encryption, traceability and regulatory compliance controls.
• Catalogue: description of available data sets and services.
• Business model: utility, costs, incentives and value generated for participants.

Technology is only a part. A data space also needs contracts, policies, information quality and a case of use that justifies participation.

What the Data Spaces Kit was financing

The TDF / 758 / 2025 Order established the basis for financing the costs necessary for the effective incorporation into an eligible data area. EUR 60 million, amplified by resolution.

The aid was granted by means of non-competitive competition:: were examined in a presentation order, provided that the requirements were met, until the available credit was exhausted.

It could be financed up to 100% of eligible expenditurewithin the limit for each type of beneficiary and mode.

Beneficiaries and maximum amounts

The call distinguishes between public or private entities that were engaged in economic activity and Spanish public administrations.

Beneficiary	Modality	Maximum aid
Public and private entities with economic activity	Effective incorporation as a participant	€15,000
Public and private entities with economic activity	Advanced effective incorporation as a supplier	€30,000
Public administrations	Effective incorporation as a participant	€25,000
Public administrations	Advanced effective incorporation as a supplier	€50,000

The two modalities were incompatible with each other for the same entity, the final amount being based on the incorporation that could be credited and the costs accepted.

Entities with economic activity

Public or private entities with their own legal personality, a tax office in the European Union and economic activity could be involved. Eligible actions should be carried out in Spain and the entity should meet the administrative and economic requirements of the bases.

Non-profit entities could benefit when they had legal personality, developed eligible economic activity and met the other conditions.

Public administrations

The call included the General State Administration, Autonomous Communities and Local Entities, in addition to the bodies included in the perimeter defined by the bases. The procurement and justification should respect the rules applicable to the public sector.

Main exclusions

Persons in a situation of self-employment, temporary business unions, civil societies, property communities and other economic units without their own legal personality could not benefit.

The aid was also subject to incompatibility with certain previous data space programmes.

Participant or supplier: both modalities

Effective incorporation as a participant

The entity should register, adhere and be able to consume, exchange or use resources within the data space, providing the evidence required by the call.

Advanced effective incorporation as a supplier

In addition to being incorporated, the entity should publish or make available data or services through space capabilities, which required that the chosen environment be provided with sufficient catalogue and functionalities to credit such publication.

Before deciding a modality it was appropriate to check the maturity of the data itself: origin, rights of use, quality, format, metadata, security and real ability to keep it up to date.

Which expenditure could be eligible

The aid was aimed at the costs strictly necessary for the adaptation and incorporation into the data area.

• Identification of opportunities and definition of the case of use.
• Data preparation, cleaning, processing and documentation.
• Technological adaptation and integration with the chosen space.
• Development of connectors, APIs or exchange mechanisms.
• Legal, contractual and governance work linked to accession.
• Preparation of metadata, catalogue and publication of data sets.
• Training needed to participate and operate in the ecosystem.
• Consulting or integration services contracted to external suppliers.
• Own staff directly assigned to the activities, with well-justified dedication and cost.

The participation or accession quotas the amount of the aid received by the promoter and the acquisition of hardware were not considered eligible costs.

The expenditure should have been incurred from the date set by the call and should be linked in an indubious way to the financed action.

Aid based on implementation and justification

The procedure had an important particularity: the incorporation and associated costs should be implemented and paid before submitting the application. It was not a question of first applying for a bonus and then starting the project.

The application incorporated the justification for the action, and the relevant documentation and evidence included:

1. Contractual adherence to the data space.
2. Identification of the participant and registration in the environment.
3. A report of the activities carried out.
4. Technical evidence of incorporation and, where appropriate, publication.
5. Inputs, payments and cost documentation.
6. Dedication of own staff when charged to the project.
7. Business plan that explained how participation would generate value.

The Dato General Directorate verified the incorporation of the evidence submitted and issued the certificate in the procedure on its own initiative. It was not a document that the applicant had to obtain separately before the application was initiated.

Which data spaces were eligible

It was not enough to connect to any platform. The incorporation should be carried out in one of the areas recognized by the program: initiatives of the Plan to Impulse Sectoral Data Spaces, the National Health Data Area, projects included in the Trust List or those that determined the call.

The official catalogue brought together projects in many areas:

• Health and social care.
• Agrofood.
• Mobility and logistics.
• Industry and automotive.
• Tourism.
• Environment, biodiversity and water.
• Social economy and care.
• Trade and ecommerce.
• Energy.
• Finance and financial technology.
• Media.
• Training and employment.
• Cybersecurity and information technologies.

The cases collected included spaces for health research, agri-food traceability, urban mobility, carbon footprint calculation, tourism intelligence, water management, ecommerce or information exchange for training and artificial intelligence application.

The catalogue evolved as new spaces were recognized. Therefore, the valid source for the eligibility was always the official relationship published by the Data Spaces Reference Centre and the existing documentation of the file.

The business plan: turning data into a real opportunity

The participation should not be justified by the availability of aid alone. The memory required to explain how the investment would be made profitable and what value the sharing or use of data would produce.

A case of solid use answers at least these questions:

• What business, public service or research problem is being solved?
• What data are needed and who can use them legitimately?
• What quality, frequency and level of detail should they have?
• What does each participant earn when sharing them?
• What decisions, products or automations can be activated?
• How will the result be measured?
• Who will maintain integration and information after the project?

Without these responses, the risk is to build a technically valid connection but without adoption or continuity.

Prepare a step-by-step incorporation

Although the call is already closed, the method remains useful for any organization that is considering joining a data ecosystem:

1. Define the case of use. Concrete the problem and the expected result.
2. Inventory the data. Identify sources, responsible, permissions, quality and frequency.
3. Choose the right space. Review participants, rules, technology, catalogue and sustainability.
4. Validate the legal lace. Determine legal bases, contracts, ownership, licenses and data protection.
5. Design architecture. Prepare integration, identity, security, observability and operation.
6. Prepare and document the datasets. Standardize data and generate understandable metadata.
7. Integrate and try. Check exchange, permissions, traceability and quality.
8. Measure the value. Establish indicators of use, efficiency, income, savings or impact.

Data, integrations and artificial intelligence

Data spaces can become a useful infrastructure for advanced analytics and artificial intelligence. They allow for combining information from different participants, expanding the context of models and creating services that an isolated organization could not develop with its own data.

But sharing more information does not guarantee better results. To use this data in BI, Machine Learning or Generative AI, it is necessary to maintain governance, quality, traceability, permissions and mechanisms to keep them up to date.

Technical integration should also be considered as a productive system: APIs, automatic processes, error control, monitoring, security and operation. A connector that works during the demonstration but cannot be maintained does not solve the problem.

How Sitelicon can help you

At Sitelicon we approach data projects from the relationship between business and technology. We can help an organization identify cases of use, order sources, define an architecture, prepare integrations and build solutions of analysis or artificial intelligence on governed information.

Our experience in the development of the custom, APIs, automation, Power BI, cloud and AI allows us to work from end to end: from diagnosis and design to implementation, observability and system evolution.

If a future call for such support is to be recovered, its requirements, dates and budget should always be checked on Red.es, Accelerera Pyme and the BOE before making decisions or taking on expenses.