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CORDIS · AIDAVA

AI powered Data Curation & Publishing Virtual Assistant

Code
AIDAVA
Programme
HORIZON
Call
HORIZON-HLTH-2021-TOOL-06-03
Status
SIGNED
Period
2022-09-01 – 2026-08-31
Total cost (whole consortium)7 720 615 €
EU contribution (whole consortium)7 720 615 €
EU contribution to Bulgarian participants474 219 €

Official data · CORDIS · synced 2026-10-17 10:16 · official record

Participants

OrganisationsRoleCountryGrant
UNIVERSITEIT MAASTRICHTcoordinatorNL1 977 867 €
MEDIZINISCHE UNIVERSITAT GRAZparticipantAT1 145 783 €
EGNOSIS SRLparticipantRO779 688 €
B!LOBAparticipantBE650 469 €
SIHTASUTUS POHJA-EESTI REGIONAALHAIGLAparticipantEE585 163 €
AVERBIS GMBHparticipantDE521 781 €
EURICE EUROPEAN RESEARCH AND PROJECT OFFICE GMBHparticipantDE508 250 €
ONTOTEXT ADparticipantBG474 219 €
THE EUROPEAN INSTITUTE FOR INNOVATION THROUGH HEALTH DATAparticipantBE443 912 €
KATHOLIEKE UNIVERSITEIT LEUVENparticipantBE306 696 €
EUROPEAN HEART NETWORK AISBLparticipantBE190 010 €
DFP Research SOCIEDAD LIMITADAparticipantES95 778 €
EUROPEAN CANCER PATIENT COALITIONparticipantBE41 000 €
RESEARCH AND INNOVATION SERVICES DOO ZA USLUGEthird partyHR0 €
DIGI.ME LIMITEDassociated partnerUK
MIDATA Genossenschaftassociated partnerCH

Description

Integrated, high-quality personal health data (PHD) 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 across institutions, at national and EU level. AIDAVA will fill this gap by prototyping and testing an AI-powered, virtual assistant maximizing automation of data curation & publishing of unstructured and structured, heterogeneous data. The assistant includes a backend with a library of AI-based data curation tools and a frontend based on human-AI interaction modules that will help users when automation is not possible, while adapting to users? preferences. The interdisciplinary team of the consortium will develop and test two versions of this virtual assistant with hospitals and emerging personal data intermediaries, around breast cancer patient registries and longitudinal health records for cardio-vascular patients, in three languages. The team will work around four 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, to increase interoperability and portability; 3) deep learning for information extraction from narrative content; and 4) AI-generated explanations during the process to increase users? confidence. By increasing automation of data quality enhancement, AIDAVA will decrease the workload of clinical data stewards; by providing high-quality data, AIDAVA will improve the effectiveness of clinical care and support clinical research. In the long-term, AIDAVA has the potential to democratise participation in data curation & publishing by citizens/patients leading to overall savings in health care costs (through disease prevention, early diagnosis, personalized medicine) and supporting delivery of the European Health Data Space.

Official data · CORDIS · synced 2026-10-17 10:16 · official record · Licence: © European Union, CC BY 4.0 (Commission reuse policy).