AIDAVA

AI-powered Data Curation & Publishing Virtual Assistant. EU Horizon Europe research project automating curation and publishing of personal health data using AI.

AIDAVA prototypes and tests an AI-powered virtual assistant that maximizes automation of data curation and publishing of unstructured and structured, heterogeneous health data. The assistant includes a backend library of AI-based data curation tools and a frontend based on human-AI interaction modules.

Key Facts

Detail	Value
Grant ID	101057062
Funding Call	HORIZON-HLTH-2021-TOOL-06-03
Total Cost	EUR 7,720,615
Start Date	September 1, 2022
End Date	August 31, 2026
Duration	48 months
Partners	13-14 from 9 countries
Coordinator	Maastricht University, Remzi Celebi — remzi.celebi@maastrichtuniversity.nl
Website	aidava.eu
Documents	AIDAVA Documents — all PDFs with summaries
Contacts	AIDAVA Contacts — partner people and emails

"Curate once, reuse many times" — supporting patients, clinical care providers and clinical researchers from the same curated data.

The project addresses the core problem that integrated, high-quality personal health data represents a potential wealth of knowledge for healthcare systems, but there is no reliable conduit for this data to become interoperable, AI-ready and reuse-ready at scale.

Technology Pillars

1. Automation of quality enhancement and FAIRification of collected health data, in compliance with EU data privacy
2. Knowledge graphs with ontology-based standards as universal representation — each Personal Health Knowledge Graph (PHKG) is an instance of a common reference knowledge graph based on ontologies derived from SNOMED, HL7 FHIR resource profiles, LOINC, and other domain-specific terminologies
3. Deep learning for information extraction from narrative content — NLP developed in three languages
4. AI-generated explanations during the process to increase users' confidence (explainability)

Use Cases

1. Breast cancer patient registries — structured registry data curation across 3 university hospitals
2. Longitudinal health records for cardiovascular patients — integrating heterogeneous data sources over time

Both tested in three languages (Dutch, German, Estonian) with hospitals and emerging personal data intermediaries.

Evaluation Results (from March 2025 Flash)

• 83 patients recruited; 70 completed evaluation
• G1 prototype (June 2024) tested in Estonia, Austria, Netherlands
• 45% of documents curated automatically
• Average 20 minutes per document (too slow)
• Usability good, but explanations suboptimal and benefits unclear
• G2 delivery: end 2025, testing early 2026
• Project end: August 2026

Full document summaries: AIDAVA Documents

Partners

Organization	Country	Role
Maastricht University	Netherlands	Coordinator
KU Leuven	Belgium	Research partner
i-HD	Belgium	Health data standards and quality
Egnosis	Romania	Health data intermediary
Ontotext (Sirma AI EAD)	Bulgaria	Knowledge graph technology
Averbis	Germany	NLP and text mining
Medical University of Graz	Austria	Clinical partner
North Estonia Regional Hospital	Estonia	Clinical partner (use case)
European Cancer Patient Coalition	Belgium	Patient advocacy (until May 2024)
European Heart Network	Belgium	Patient advocacy (cardiovascular)
B!LOBA	Belgium	Data management
DFP Research / Data for Patients	Spain	Research partner (since Oct 2024)
EURICE	Germany	Project management
MIDATA Cooperative	Switzerland	Data cooperative
RISE Research & Innovation Services	Croatia	Innovation services

All contacts: AIDAVA Contacts

Related

• Knowledge Graphs in Health
• Interoperability
• Longitudinal Journals
• AIDAVA Documents
• AIDAVA Contacts

External Links

• Official website
• CORDIS
• DOI

Exploitation & Business Model (from Project Deliverables)

The AIDAVA consortium has identified exploitation plans through WP6 Innovation Management. Key findings from public deliverable descriptions:

Key Exploitable Results (KERs)

D6.8 (Recommendations from the Sustainability Advisory Board, Jan 2025) identified KERs and presented the value proposition and exploitation plans to the Sustainability Advisory Board across three meetings (M01-M22).

Two "Go To Market" Approaches

The Sustainability Advisory Board suggested two potential avenues for an "AIDAVA product" combining several KERs:

1. Interoperability enablement of healthcare authorities and healthcare organisations — as part of implementation of the EHDS
2. Citizens empowerment in managing their health data

These align directly with the two business opportunities explored on Stamen Health Executive Summary: EHDS compliance infrastructure (approach 1) and patient data consolidation apps (approach 2).

Business Requirements

D1.3 (Business requirements for G1, Jun 2023, public) gathered 596 requirements across users (patients, expert curators, data users, administrators, third-party app developers). After consolidation: 277 for prototype (46 blocking, 178 major, 53 minor) + 99 additional for future product.

D1.3 explicitly states: "the second objective is to develop a solution that can be transformed into a full-fledged product, including MDR certification." Product requirements won't be developed during AIDAVA but "the technology architects will take these into account when defining the architecture and ensure the prototype can smoothly evolve toward a marketable product."

Patient Requirements (from D1.2 and D1.8)

From patient workshops (Feb 2023, ECPC and EHN):

• Main incentive: ensure treating physician has smooth access to complete medical record
• Happy to share data "in a controlled way"
• Want to know who accesses data, easy consent mechanism, purpose transparency
• Reward should be envisioned for commercial use of shared data
• Concern about data donation — do they lose control?

G1 Evaluation Reality (from D1.7, Jan 2025)

83 patients recruited, 70 completed. Key findings:

• Only existing OCR and German NLP tools were usable — team had to include "suboptimal open source tools and very early prototypes"
• Data Transfer Specification setup was "time consuming — information not readily available"
• HDI integration was "smooth with regular improvements"
• Patient acceptance "slightly above medium" — perceived importance but "lack of direct benefits"
• Data users concerned: "lack of usable high-quality data to support any decision"
• Despite suboptimal G1, the project confirms "true potential for automation in data curation into a harmonised semantic standard, under the form of a Personal Health Knowledge Graph"

What This Means for Commercialization

• The consortium is thinking about commercialization (D6.2, D6.8) but the exploitation plans are at the strategic level, not product level
• MDR certification is planned for the future product but not scoped within the project
• The two Go To Market approaches (EHDS enablement, citizen empowerment) validate the Stamen Health thesis
• The biggest gap between research and product: curation tool reliability (45% automation → need 80%+), patient-perceived benefits, and MDR compliance

See Also

• AIDAVA Competitive Analysis
• AIDAVA Related Companies
• Ontologies for Longitudinal Health Records
• Companies

Exploitation & Business Model (from Project Deliverables)

The AIDAVA consortium has identified exploitation plans through WP6 Innovation Management. Key findings from public deliverable descriptions:

Key Exploitable Results (KERs)

D6.8 (Recommendations from the Sustainability Advisory Board, Jan 2025) identified KERs and presented the value proposition and exploitation plans to the Sustainability Advisory Board across three meetings (M01-M22).

Two "Go To Market" Approaches

The Sustainability Advisory Board suggested two potential avenues for an "AIDAVA product" combining several KERs:

1. Interoperability enablement of healthcare authorities and healthcare organisations — as part of implementation of the EHDS
2. Citizens empowerment in managing their health data

These align directly with the two business opportunities explored on Stamen Health Executive Summary: EHDS compliance infrastructure (approach 1) and patient data consolidation apps (approach 2).

Business Requirements

D1.3 (Business requirements for G1, Jun 2023, public) gathered 596 requirements across users (patients, expert curators, data users, administrators, third-party app developers). After consolidation: 277 for prototype (46 blocking, 178 major, 53 minor) + 99 additional for future product.

D1.3 explicitly states: "the second objective is to develop a solution that can be transformed into a full-fledged product, including MDR certification." Product requirements won't be developed during AIDAVA but "the technology architects will take these into account when defining the architecture and ensure the prototype can smoothly evolve toward a marketable product."

Patient Requirements (from D1.2 and D1.8)

From patient workshops (Feb 2023, ECPC and EHN):

• Main incentive: ensure treating physician has smooth access to complete medical record
• Happy to share data "in a controlled way"
• Want to know who accesses data, easy consent mechanism, purpose transparency
• Reward should be envisioned for commercial use of shared data
• Concern about data donation — do they lose control?

G1 Evaluation Reality (from D1.7, Jan 2025)

83 patients recruited, 70 completed. Key findings:

• Only existing OCR and German NLP tools were usable — team had to include "suboptimal open source tools and very early prototypes"
• Data Transfer Specification setup was "time consuming — information not readily available"
• HDI integration was "smooth with regular improvements"
• Patient acceptance "slightly above medium" — perceived importance but "lack of direct benefits"
• Data users concerned: "lack of usable high-quality data to support any decision"
• Despite suboptimal G1, the project confirms "true potential for automation in data curation into a harmonised semantic standard, under the form of a Personal Health Knowledge Graph"

What This Means for Commercialization

• The consortium is thinking about commercialization (D6.2, D6.8) but the exploitation plans are at the strategic level, not product level
• MDR certification is planned for the future product but not scoped within the project
• The two Go To Market approaches (EHDS enablement, citizen empowerment) validate the Stamen Health thesis
• The biggest gap between research and product: curation tool reliability (45% automation → need 80%+), patient-perceived benefits, and MDR compliance

See Also

• AIDAVA Competitive Analysis
• AIDAVA Related Companies
• Ontologies for Longitudinal Health Records
• Companies