Co-led by Health Data Hub and the Health Data Lab, WP5 will lead the implementation of the IT infrastructure enabling information exchange between nodes in an agnostic way in order to allow data processing (DCAT, data…) among nodes. The infrastructure will use and specify an eDelivery protocol and provide discovery services. WP5 will also provide hosting solutions.

Results available:

• Framing document
• D5.1 Architecture Definition Document

Towards a common health Resource Description Framework (RDF) representation of metadata for interexchange between data portals

Led by Sciensano, WP6 focuses on standardising the descriptive metadata templates used to present and describe the available data collections in every node. The standard for this common descriptive metadata model is based on a health DCAT-AP extension designed in this WP.

 Access the Health DCAT-AP GitHub repository

 Explore the Health DCAT-AP Validator to ensure metadata quality

Results: 

• Report on the landscape analysis of available metadata catalogues and the metadata standards in use
• Technical working group on the transition from existing metadata templates to HealthDCAT-AP – Working group minutes
• D6.1 Health DCAT-AP Extension
• D6.2 Recommendations for the further development and potential EU-wide adoption of HealthDCAT-AP
• Annex 1- Functional Analysis implementation of HealthDCAT-AP in EU Datasets catalogue

Lead by BBMRI-ERIC, WP7 will provide guidelines in order to build a single data access form for the EHDS, to harmonise legal and ethics data access procedures, security requirements and GDPR citizen access rights compliance for cross-border use of data applied to selected use cases

Results

• Legal landscape analysis (download the summary)
• Find out more on the design of the common data application form  (download the full report and forms)
• Report based on use cases, on general conditions of data sharing and usage security measures for data use including de-identification, onsite use in a secure environment and secure transfer

Lead by BBMRI-ERIC, WP8 deals with interoperability of actual data in different phases of HealthData@EU User Journey: from a study of different common data models, available terminologies and how to make data interoperability between nodes, to data exchange among HealthData@EU Nodes and ultimately data delivery to the researchers. It also deals with quality controlling and more generally quality assurance mechanisms that are to be implemented by the HealthData@EU Nodes. The subject of federated queries to obtain new metadata, such as aggregate availability data, is addressed through a feasibility study. WP8 has relations with respect to standards recommended and piloted by WP5 and WP6 and will closely work with WP7 on legal matters (aspects for standards, legal bases for data processing).

Deliverables

D8.1 Recommendations of standards for data interoperability, querying and exchange

Key findings:

1. Variability in national data access frameworks, leading to interoperability challenges.
2. Differences in metadata standards, affecting harmonization across countries.
3. Technical and semantic interoperability issues, requiring further standardization efforts.
4. Lessons learned from real-world implementation, informing recommendations for future EHDS infrastructure development.

D8.2 Recommendations on quality controlling, assurance & provenance

Key findings:

1. Divergences in national data quality standards, impacting harmonization efforts.
2. Challenges in ensuring data provenance and traceability across multiple jurisdictions.
3. Differences in quality control implementation among participating countries.
4. Lessons learned from real-world implementation, informing recommendations for future EHDS infrastructure development.

D8.3 Recommendations on application of privacy enhancing technologies, data security and node compute capabilities 

Key findings:

1. Diverse PETs adoption across use cases, with different security measures based on data sensitivity and processing needs.
2. Varying approaches to federated and centralised data access, with implications for security and performance.
3. Challenges in ensuring robust data security, particularly in cross-border collaborations.
4. Computational resource requirements differ depending on the size and complexity of the datasets involved.

Co-lead by the Health Data Hub and the Danish Health Data Authority, WP9 will coordinate the implementation of use cases chosen by the European Commission among consortium proposed use cases (building teams, project management, and allocation of resources). This WP will also ensure project management for the implementing common data model designed by WP8 on chosen data use cases and for filling up the HealthDCAT extension and metadata catalogue on selected use cases.

Overview of the Use Cases

• Predicting nationwide cardio-metabolic disease trajectories using machine learning
  • Lead: HDH / University of Helsinki
  • Participating Nodes: University of Helsinki (FI), AHeaD (FR), Copenhagen University (DK), Norwegian Institute of Public Health (NO)
  • Brief Overview: This use case applied machine learning to predict a 5-year cardiovascular risk. It encountered challenges related to the interpretation of data minimization in France and Norway.
• Test use, hospitalisation, and vaccination adherence in vulnerable sub-populations
  • Lead: Sciensano
  • Participating Nodes: Sciensano (BE), Central Denmark Region (DK), Croatian Institute of Public Health (HR), Finnish Institute for Health and Welfare (FI)
  • Brief Overview: This use case analyzed COVID-19 testing, hospitalization, and vaccination rates in vulnerable groups. Issues were encountered in accessing socio-economic data.
• Identifying the risks of coagulation disorders in patients with COVID-19
  • Lead: EMA
  • Participating Nodes: Croatian Institute of Public Health (HR), Danish Health Data Authority (DK), Finnish Institute for Health and Welfare (FI), Health Data Hub (FR), DARWIN EU Network
  • Brief Overview: This use case investigated the venous/arterial thromboembolic risks in COVID-19 patients, using the OMOP CDM for analysis.
• Antimicrobial resistance (AMR) surveillance
  • Lead: ECDC
  • Participating Nodes: Sciensano (BE), Croatian Institute of Public Health (HR), Finnish Institute for Health & Welfare (FI)
  • Brief Overview: This use case tested the EHDS architecture for communicable disease surveillance, focusing on data concordance, legal barriers, and federated data processing.
• Identifying genomic signatures of colorectal cancer
  • Lead: ELIXIR / BSC
  • Participating Nodes: BBMRI-ERIC, Sciensano (BE), Danish Health Data Authority (DK), Norwegian Institute of Public Health (NO), National Institute of Oncology (HU)
  • Brief Overview: This use case used genomic and clinical data for colorectal cancer analysis but faced significant delays in access, eventually leading to transfer to the GDI project.

Results: Use case report

Key Challenges and Findings

• Data Access & governance
  • Data minimization interpretation: This posed a challenge in France and Norway, restricting access to some datasets.
  • Socio-economic data restrictions: The Sciensano use case faced significant challenges in accessing this data.
  • Genomic data complexity: The ELIXIR use case encountered major delays and feasibility issues in accessing genomic data.
• Technical & interoperability challenges
  • Heterogeneous data formats: Different nodes used varying data formats (e.g., OMOP CDM vs native formats).
  • Federated data processing limitations: The ECDC use case highlighted scalability concerns related to federated data processing.
• Legal & ethical considerations
  • Varying national regulations: Different regulations impacted data access and timelines.
  • Data privacy and security concerns: Cross-country challenges emerged in ensuring compliance with data privacy and security standards.