HealthDCAT-AP: The Standard That Connects Health Data to People

Data is the engine of innovation, and its transformative potential is reflected in all areas, especially in health. From faster diagnoses to personalized treatments to more effective public policies, the intelligent use of health information has the power to change lives in profound and meaningful ways.

But, for this data to unfold its full value and become a real force for progress, it is essential that it "speaks the same language". That is, they must be well organized, easy to find, and can be shared securely and consistently across systems, countries, and practitioners.

This is where HealthDCAT-AP comes into play, a new European specification  that, although it sounds technical, has a lot to do with our well-being as citizens. HealthDCAT-AP is designed to describe health data—from aggregated statistics to anonymized clinical records—in a homogeneous, clear, and reusable way, through metadata. In short, it does not act on the clinical data itself, but rather makes it easier for them to be located and better understood thanks to a standardized description.HealthDCAT-AP is exclusively concerned with metadata, i.e., how datasets are described and organized in catalogs, unlike HL7, FHIR, and DICOM, which structure the exchange of clinical information and images. CDA, which describes the architecture of documents; and SNOMED CT, LOINC, and ICD-10, which standardize the semantics of diagnoses, procedures, and observations to ensure that data have the same meaning in any context.

This article explores how HealthDCAT-AP, in the context of the European Health Data Space (EHDS) and the National Health Data Space (ENDS), brings value primarily to those who reuse data—such as researchers, innovators, or policymakers—and ultimately benefits citizens through the advances they generate.

What is HealthDCAT-AP and how does it relate to DCAT-AP?

Imagine a huge library full of health books, but without any system to organize them. Searching for specific information would be a chaotic task. Something similar happens with health data: if it is not well described, locating and reusing it is practically impossible.

HealthDCAT-AP was born to solve this challenge. It is a European technical specification that allows for a clear and uniform description of health datasets within data catalogues, making it easier to search, access, understand and reuse them. In other words, it makes the description of health data speak the same language across Europe, which is key to improving health care, research and policy.

This technical specification is based on DCAT-AP, the general specification used to describe catalogues of public sector datasets in Europe. While DCAT-AP provides a common structure for all types of data, HealthDCAT-AP is your  specialized health extension, adapting and extending that model to cover the particularities of clinical, epidemiological, or biomedical data.

HealthDCAT-AP was developed within the framework of the European EHDS2 (European Health Data Space 2) pilot project  and continues to evolve thanks to the support of projects such as HealthData@EU Pilot, which are working on the deployment of the future European health data infrastructure. The specification is under active development and its most recent version, along with documentation and examples, can be publicly consulted in its official GitHub repository.

HealthDCAT-AP is also designed to apply the FAIR principles: that data is Findable, Accessible, Interoperable and Reusable. This means that although health data may be complex or sensitive, its description (metadata) is clear, standardized, and useful. Any professional or institution – whether in Spain or in another European country – can know what data exists, how to access it and under what conditions. This fosters trust, transparency, and responsible use of health data. HealthDCAT-AP is also a cornerstone of EHDS and therefore ENDS. Its adoption will allow hospitals, research centres or administrations to share information consistently and securely across Europe. Thus, collaboration between countries is promoted and the value of data is maximized for the benefit of all citizens.

To facilitate its use and adoption,  from Europe, under the initiatives mentioned above, tools such as the  HealthDCAT-AP editor and validator have been created, which allow any organization to generate descriptions of datasets through metadata that are compatible without the need for advanced technical knowledge. This removes barriers and encourages more entities to participate in this networked health data ecosystem.

How does HealthDCAT-AP contribute to the public value of health data?

Although HealthDCAT-AP is a technical specification focused on the description of health datasets, its adoption has practical implications that go beyond the technological realm. By offering a common and structured way of documenting what data exists, how it can be used and under what conditions,  it helps different actors – from hospitals and administrations to research centres or startups – to better access, combine and reuse the available information, enabling the so-called secondary use of the same, beyond its primary healthcare use.

• Faster diagnoses and personalized treatments: When data is well-organized and accessible to those who need it, advances in medical research accelerate. This makes it possible to develop artificial intelligence tools that detect diseases earlier, identify patterns in large populations and adapt treatments to the profile of each patient. It is the basis of personalized medicine, which improves results and reduces risks.
• Better access to knowledge about what data exists: HealthDCAT-AP makes it easier for researchers, healthcare managers or authorities to locate useful datasets, thanks to its standardized description. This can facilitate, for example, the analysis of health inequalities or resource planning in crisis situations.
• Greater transparency and traceability: The use of metadata allows us to know who is responsible for each set of data, for what purpose it can be used and under what conditions. This strengthens trust in the data reuse ecosystem.
• More efficient healthcare services: Standardizing metadata improves information flows between sites, regions, and systems. This reduces bureaucracy, avoids duplication, optimizes the use of resources, and frees up time and money that can be reinvested in improving direct patient care.
• More innovation and new solutions for the citizen: by facilitating access to larger datasets, HealthDCAT-AP promotes the development of new patient-centric digital tools: self-care apps, remote monitoring systems, service comparators, etc. Many of these solutions are born outside the health system – in universities, startups or associations – but directly benefit citizens.
• A connected Europe around health: By sharing a common way of describing data, HealthDCAT-AP makes it possible for a dataset created in Spain to be understood and used in Germany or Finland, and vice versa. This promotes international collaboration, strengthens European cohesion and ensures that citizens benefit from scientific advances regardless of their country.

And what role does Spain play in all this?

Spain is not only aligned with the future of health data in Europe: it is actively participating in its construction. Thanks to a solid legal foundation, a largely digitized healthcare system, accumulated experience in the secure sharing of health information within the Spanish National Health System (SNS), and a long history of open data—through initiatives such as datos.gob.es—our country is in a privileged position to contribute to and benefit from the European Health Data Space (EHDS).

Over the years, Spain has developed legal frameworks and technical capacities that anticipate many of the requirements of the EHDS Regulation. The widespread digitalization of healthcare and the experience in using data in a secure and responsible way allow us to move towards an interoperable, ethical and common good-oriented model.

In this context, the National Health Data Space project represents a decisive step forward. This initiative aims to become the national reference platform for the analysis and exploitation of health data for secondary use, conceived as a catalyst for research and innovation in health, a benchmark in the application of disruptive solutions, and a gateway to different data sources. All of this is carried out under strict conditions of anonymization, security, transparency, and protection of rights, ensuring that the data is only used for legitimate purposes and in full compliance with current regulations.

Spain's familiarity with standards such as DCAT-AP facilitates the deployment of HealthDCAT-AP. Platforms such as datos.gob.es, which already act as a reference point for the publication of open data, will be key in its deployment and dissemination.

Conclusions

HealthDCAT-AP may sound technical, but it is actually a specification that can have an impact on our daily lives. By helping to better describe health data, it makes it easier for that information to be used in a useful, safe, and responsible manner.

This specification allows the description of data sets to speak the same language across Europe. This makes it easier to find, share with the right people, and reuse for purposes that benefit us all: faster diagnoses, more personalized treatments, better public health decisions, and new digital tools that improve our quality of life.

Spain, thanks to its experience in open data and its digitized healthcare system, is actively participating in this transformation through a joint effort between professionals, institutions, companies, researchers, etc., and also citizens. Because when data is understood and managed well, it can make a difference. It can save time, resources, and even lives.

HealthDCAT-AP is not just a technical specification: it is a step forward towards more connected, transparent, and people-centered healthcare. A specification designed to maximize the secondary use of health information, so that all of us as citizens can benefit from it.

Content created by Dr. Fernando Gualo, Professor at UCLM and Government and Data Quality Consultant. The content and views expressed in this publication are the sole responsibility of the author.