AIDAVA - Revision history

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2026-04-13T19:02:35Z

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172.19.0.1: Undo revision 129 by Admin 3julmthh (talk)

2026-04-13T19:02:19Z

Undo revision 129 by Admin 3julmthh (talk)

← Older revision	Revision as of 19:02, 13 April 2026
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		__NOTOC__

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

		== Overview ==
		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.<ref>European Commission CORDIS, Grant 101057062: "AI powered Data Curation & Publishing Virtual Assistant" — https://cordis.europa.eu/project/id/101057062</ref>

		== Key Facts ==
		{\|
		\|-
		! Detail !! Value
		\|-
		\| Grant ID \|\| [https://cordis.europa.eu/project/id/101057062 101057062]
		\|-
		\| Funding Call \|\| HORIZON-HLTH-2021-TOOL-06
		\|-
		\| Total Cost \|\| €7,720,620
		\|-
		\| EU Contribution \|\| €7,720,620 (100% funded)
		\|-
		\| Start Date \|\| September 1, 2022
		\|-
		\| End Date \|\| August 31, 2026
		\|-
		\| Duration \|\| 4 years
		\|-
		\| Partners \|\| 13 from 9 countries
		\|-
		\| Type \|\| Horizon Europe Research and Innovation Action (RIA)
		\|-
		\| Website \|\| [https://aidava.eu aidava.eu]
		\|}

		== Vision ==
		"Curate once, reuse many times" — supporting patients, clinical care providers and clinical researchers from the same curated data.<ref>AIDAVA official website — https://aidava.eu</ref>

		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 across institutions, at national and EU level.<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>

		== Technology Pillars ==
		# '''Automation of quality enhancement and FAIRification''' of collected health data, in compliance with EU data privacy
		# '''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<ref>AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts</ref>
		# '''Deep learning for information extraction''' from narrative content — NLP developed in three languages
		# '''AI-generated explanations''' during the process to increase users' confidence (explainability)<ref>AIDAVA, "Solution" — https://aidava.eu/about/solution</ref>

		== Use Cases ==
		# '''Breast cancer patient registries''' — structured registry data curation
		# '''Longitudinal health records for cardiovascular patients''' — integrating heterogeneous data sources over time

		Both tested in three languages with hospitals and emerging personal data intermediaries.<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>

		== Solution Architecture ==
		* '''Data cleaning machine''' — orchestrating multiple AI-based tools to automate curation
		* '''Personal Health Knowledge Graph (PHKG)''' — universal semantic representation of all personal health data
		* '''Conversational AI assistant''' — engages patients, with explainability capabilities
		* '''Metadata capture''' — on data sources to support automation within a formalised Data Transfer Specification
		* Tools orchestrated include: OCR, syntactic transformation, semantic transformation, entity deduplication, NLP, feature extraction from imaging<ref>AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts</ref>

		== Impact ==
		* Decrease workload of clinical data stewards through increased automation
		* Improve effectiveness of clinical care through high-quality data
		* Support clinical research with reusable, interoperable data
		* Long-term: democratise participation in data curation by citizens/patients
		* Support delivery of the European Health Data Space (EHDS)<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>

		== Partners ==
		{\| class="wikitable"
		\|-
		! 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]] \|\| 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
		\|-
		\| [[European Heart Network]] \|\| Belgium \|\| Patient advocacy (cardiovascular)
		\|-
		\| [[B!LOBA]] \|\| Belgium \|\| Data management
		\|-
		\| [[DFP Research]] \|\| Spain \|\| Research partner
		\|-
		\| [[EURICE]] \|\| Germany \|\| Project management
		\|}

		All partners identified via OpenAIRE/CORDIS project registry.<ref>OpenAIRE, AIDAVA project 101057062 — https://api.openaire.eu/search/projects?keywords=AIDAVA</ref>

		== Related Topics ==
		* [[Knowledge Graphs in Health]]
		* [[Interoperability]]
		* [[Longitudinal Journals]]
		* [[EU Regulation]]

		== External Links ==
		* [https://aidava.eu Official AIDAVA website]
		* [https://cordis.europa.eu/project/id/101057062 CORDIS project page]
		* [https://doi.org/10.3030/101057062 DOI: 10.3030/101057062]

		<references />
		[[Category:Project]]
		[[Category:EU]]

Admin 3julmthh: Added document summaries

2026-04-13T18:45:17Z

Added document summaries

← Older revision		Revision as of 18:45, 13 April 2026
Line 1:		Line 1:
	~~__NOTOC__~~

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

	~~== Overview ==~~
	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.<ref>European Commission CORDIS, Grant 101057062: "AI powered Data Curation & Publishing Virtual Assistant" — https://cordis.europa.eu/project/id/101057062</ref>

	~~== Key Facts ==~~
	{\|
	\|-
	~~! Detail !! Value~~
	\|-
	~~\| Grant ID \|\| [https://cordis.europa.eu/project/id/101057062 101057062]~~
	\|-
	~~\| Funding Call \|\| HORIZON-HLTH-2021-TOOL-06~~
	\|-
	~~\| Total Cost \|\| €7,720,620~~
	\|-
	~~\| EU Contribution \|\| €7,720,620 (100% funded)~~
	\|-
	~~\| Start Date \|\| September 1, 2022~~
	\|-
	~~\| End Date \|\| August 31, 2026~~
	\|-
	~~\| Duration \|\| 4 years~~
	\|-
	~~\| Partners \|\| 13 from 9 countries~~
	\|-
	~~\| Type \|\| Horizon Europe Research and Innovation Action (RIA)~~
	\|-
	~~\| Website \|\| [https://aidava.eu aidava.eu]~~
	\|}

	~~== Vision ==~~
	~~"Curate once, reuse many times" — supporting patients, clinical care providers and clinical researchers from the same curated data.<ref>AIDAVA official website — https://aidava.eu</ref>~~

	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 across institutions, at national and EU level.<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>

	~~== Technology Pillars ==~~
	~~# '''Automation of quality enhancement and FAIRification''' of collected health data, in compliance with EU data privacy~~
	# '''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<ref>AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts</ref>
	~~# '''Deep learning for information extraction''' from narrative content — NLP developed in three languages~~
	~~# '''AI-generated explanations''' during the process to increase users' confidence (explainability)<ref>AIDAVA, "Solution" — https://aidava.eu/about/solution</ref>~~

	~~== Use Cases ==~~
	~~# '''Breast cancer patient registries''' — structured registry data curation~~
	~~# '''Longitudinal health records for cardiovascular patients''' — integrating heterogeneous data sources over time~~

	Both tested in three languages with hospitals and emerging personal data intermediaries.<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>

	~~== Solution Architecture ==~~
	* '''Data cleaning machine''' — orchestrating multiple AI-based tools to automate curation
	* '''Personal Health Knowledge Graph (PHKG)''' — universal semantic representation of all personal health data
	* '''Conversational AI assistant''' — engages patients, with explainability capabilities
	* '''Metadata capture''' — on data sources to support automation within a formalised Data Transfer Specification
	* Tools orchestrated include: OCR, syntactic transformation, semantic transformation, entity deduplication, NLP, feature extraction from imaging<ref>AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts</ref>

	~~== Impact ==~~
	* Decrease workload of clinical data stewards through increased automation
	* Improve effectiveness of clinical care through high-quality data
	* Support clinical research with reusable, interoperable data
	* Long-term: democratise participation in data curation by citizens/patients
	* Support delivery of the European Health Data Space (EHDS)<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>

	~~== Partners ==~~
	~~{\| class="wikitable"~~
	\|-
	~~! 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]] \|\| 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~~
	\|-
	~~\| [[European Heart Network]] \|\| Belgium \|\| Patient advocacy (cardiovascular)~~
	\|-
	~~\| [[B!LOBA]] \|\| Belgium \|\| Data management~~
	\|-
	~~\| [[DFP Research]] \|\| Spain \|\| Research partner~~
	\|-
	~~\| [[EURICE]] \|\| Germany \|\| Project management~~
	\|}

	~~All partners identified via OpenAIRE/CORDIS project registry.<ref>OpenAIRE, AIDAVA project 101057062 — https://api.openaire.eu/search/projects?keywords=AIDAVA</ref>~~

	~~== Related Topics ==~~
	* [[Knowledge Graphs in Health]]
	* [[Interoperability]]
	* [[Longitudinal Journals]]
	* [[EU Regulation]]

	~~== External Links ==~~
	* [https://aidava.eu Official AIDAVA website]
	* [https://cordis.europa.eu/project/id/101057062 CORDIS project page]
	* [https://doi.org/10.3030/101057062 DOI: 10.3030/101057062]

	~~<references />~~
	~~[[Category:Project]]~~
	~~[[Category:EU]]~~

Admin 3julmthh: Fixed doubled title

2026-04-13T17:29:28Z

Fixed doubled title

← Older revision		Revision as of 17:29, 13 April 2026
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	__NOTOC__		__NOTOC__
	~~= AIDAVA =~~

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

Admin 3julmthh: Fixed references with proper URLs

2026-04-13T17:27:59Z

Fixed references with proper URLs

← Older revision		Revision as of 17:27, 13 April 2026
Line 5:		Line 5:

	== Overview ==		== Overview ==
	AIDAVA ~~protypes~~ 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.<ref>~~OpenAIRE /~~ CORDIS (Grant 101057062): "AI powered Data Curation & Publishing Virtual Assistant"</ref>		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.<ref>European Commission CORDIS, Grant 101057062: "AI powered Data Curation & Publishing Virtual Assistant" — https://cordis.europa.eu/project/id/101057062</ref>

	== Key Facts ==		== Key Facts ==
Line 12:		Line 12:
	! Detail !! Value		! Detail !! Value
	\|-		\|-
	\| Grant ID \|\| 101057062		\| Grant ID \|\| [https://cordis.europa.eu/project/id/101057062 101057062]
	\|-		\|-
	\| Funding Call \|\| HORIZON-HLTH-2021-TOOL-06		\| Funding Call \|\| HORIZON-HLTH-2021-TOOL-06
Line 34:		Line 34:

	== Vision ==		== Vision ==
	"Curate once, reuse many times" — supporting patients, clinical care providers and clinical researchers from the same curated data.<ref>aidava.eu ~~homepage~~</ref>		"Curate once, reuse many times" — supporting patients, clinical care providers and clinical researchers from the same curated data.<ref>AIDAVA official website — https://aidava.eu</ref>

	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.<ref>~~OpenAIRE~~ project summary, 101057062</ref>		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 across institutions, at national and EU level.<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>

	== Technology Pillars ==		== Technology Pillars ==
	# '''Automation of quality enhancement and FAIRification''' of collected health data, in compliance with EU data privacy		# '''Automation of quality enhancement and FAIRification''' of collected health data, in compliance with EU data privacy
	# '''Knowledge graphs with ontology-based standards''' as universal representation~~, to increase interoperability and portability~~ — 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<ref>aidava.eu/about</ref>		# '''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<ref>AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts</ref>
	# '''Deep learning for information extraction''' from narrative content (NLP in three languages)		# '''Deep learning for information extraction''' from narrative content — NLP developed in three languages
	# '''AI-generated explanations''' during the process to increase users' confidence (explainability)		# '''AI-generated explanations''' during the process to increase users' confidence (explainability)<ref>AIDAVA, "Solution" — https://aidava.eu/about/solution</ref>

	== Use Cases ==		== Use Cases ==
Line 48:		Line 48:
	# '''Longitudinal health records for cardiovascular patients''' — integrating heterogeneous data sources over time		# '''Longitudinal health records for cardiovascular patients''' — integrating heterogeneous data sources over time

	Both tested in three languages with hospitals and emerging personal data intermediaries.<ref>~~OpenAIRE~~ project summary</ref>		Both tested in three languages with hospitals and emerging personal data intermediaries.<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>

	== Solution Architecture ==		== Solution Architecture ==
Line 55:		Line 55:
	* '''Conversational AI assistant''' — engages patients, with explainability capabilities		* '''Conversational AI assistant''' — engages patients, with explainability capabilities
	* '''Metadata capture''' — on data sources to support automation within a formalised Data Transfer Specification		* '''Metadata capture''' — on data sources to support automation within a formalised Data Transfer Specification
	* Tools orchestrated include: OCR, syntactic transformation, semantic transformation, entity deduplication, NLP, feature extraction from imaging<ref>aidava.eu/about</ref>		* Tools orchestrated include: OCR, syntactic transformation, semantic transformation, entity deduplication, NLP, feature extraction from imaging<ref>AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts</ref>

	== Impact ==		== Impact ==
Line 62:		Line 62:
	* Support clinical research with reusable, interoperable data		* Support clinical research with reusable, interoperable data
	* Long-term: democratise participation in data curation by citizens/patients		* Long-term: democratise participation in data curation by citizens/patients
	* Support delivery of the European Health Data Space (EHDS)<ref>~~OpenAIRE~~ project summary</ref>		* Support delivery of the European Health Data Space (EHDS)<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>

	== Partners ==		== Partners ==
Line 73:		Line 73:
	\| [[KU Leuven]] \|\| Belgium \|\| Research partner		\| [[KU Leuven]] \|\| Belgium \|\| Research partner
	\|-		\|-
	\| [[i-HD]] \|\| Belgium \|\| Health data standards & quality		\| [[i-HD]] \|\| Belgium \|\| Health data standards and quality
	\|-		\|-
	\| [[Egnosis]] \|\| Romania \|\| Health data intermediary		\| [[Egnosis]] \|\| Romania \|\| Health data intermediary
Line 79:		Line 79:
	\| [[Ontotext]] \|\| Bulgaria \|\| Knowledge graph technology		\| [[Ontotext]] \|\| Bulgaria \|\| Knowledge graph technology
	\|-		\|-
	\| [[Averbis]] \|\| Germany \|\| NLP / text mining		\| [[Averbis]] \|\| Germany \|\| NLP and text mining
	\|-		\|-
	\| [[Medical University of Graz]] \|\| Austria \|\| Clinical partner		\| [[Medical University of Graz]] \|\| Austria \|\| Clinical partner
Line 95:		Line 95:
	\| [[EURICE]] \|\| Germany \|\| Project management		\| [[EURICE]] \|\| Germany \|\| Project management
	\|}		\|}

			All partners identified via OpenAIRE/CORDIS project registry.<ref>OpenAIRE, AIDAVA project 101057062 — https://api.openaire.eu/search/projects?keywords=AIDAVA</ref>

	== Related Topics ==		== Related Topics ==
Line 102:		Line 104:
	* [[EU Regulation]]		* [[EU Regulation]]

	== ~~See Also~~ ==		== External Links ==
			* [https://aidava.eu Official AIDAVA website]
	* [https://cordis.europa.eu/project/id/101057062 CORDIS project page]		* [https://cordis.europa.eu/project/id/101057062 CORDIS project page]
	* [https://~~aidava~~.~~eu Official website~~]		* [https://doi.org/10.3030/101057062 DOI: 10.3030/101057062]

	<references />		<references />
	[[Category:Project]]		[[Category:Project]]
	[[Category:EU]]		[[Category:EU]]

Admin 3julmthh: Added/updated

2026-04-13T17:14:37Z

Added/updated

New page

__NOTOC__
= AIDAVA =

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

== Overview ==
AIDAVA protypes 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.<ref>OpenAIRE / CORDIS (Grant 101057062): "AI powered Data Curation & Publishing Virtual Assistant"</ref>

== Key Facts ==
{|
|-
! Detail !! Value
|-
| Grant ID || 101057062
|-
| Funding Call || HORIZON-HLTH-2021-TOOL-06
|-
| Total Cost || €7,720,620
|-
| EU Contribution || €7,720,620 (100% funded)
|-
| Start Date || September 1, 2022
|-
| End Date || August 31, 2026
|-
| Duration || 4 years
|-
| Partners || 13 from 9 countries
|-
| Type || Horizon Europe Research and Innovation Action (RIA)
|-
| Website || [https://aidava.eu aidava.eu]
|}

== Vision ==
"Curate once, reuse many times" — supporting patients, clinical care providers and clinical researchers from the same curated data.<ref>aidava.eu homepage</ref>

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.<ref>OpenAIRE project summary, 101057062</ref>

== Technology Pillars ==
# '''Automation of quality enhancement and FAIRification''' of collected health data, in compliance with EU data privacy
# '''Knowledge graphs with ontology-based standards''' as universal representation, to increase interoperability and portability — 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<ref>aidava.eu/about</ref>
# '''Deep learning for information extraction''' from narrative content (NLP in three languages)
# '''AI-generated explanations''' during the process to increase users' confidence (explainability)

== Use Cases ==
# '''Breast cancer patient registries''' — structured registry data curation
# '''Longitudinal health records for cardiovascular patients''' — integrating heterogeneous data sources over time

Both tested in three languages with hospitals and emerging personal data intermediaries.<ref>OpenAIRE project summary</ref>

== Solution Architecture ==
* '''Data cleaning machine''' — orchestrating multiple AI-based tools to automate curation
* '''Personal Health Knowledge Graph (PHKG)''' — universal semantic representation of all personal health data
* '''Conversational AI assistant''' — engages patients, with explainability capabilities
* '''Metadata capture''' — on data sources to support automation within a formalised Data Transfer Specification
* Tools orchestrated include: OCR, syntactic transformation, semantic transformation, entity deduplication, NLP, feature extraction from imaging<ref>aidava.eu/about</ref>

== Impact ==
* Decrease workload of clinical data stewards through increased automation
* Improve effectiveness of clinical care through high-quality data
* Support clinical research with reusable, interoperable data
* Long-term: democratise participation in data curation by citizens/patients
* Support delivery of the European Health Data Space (EHDS)<ref>OpenAIRE project summary</ref>

== Partners ==
{| class="wikitable"
|-
! Organization !! Country !! Role
|-
| [[Maastricht University]] || Netherlands || Coordinator
|-
| [[KU Leuven]] || Belgium || Research partner
|-
| [[i-HD]] || Belgium || Health data standards & quality
|-
| [[Egnosis]] || Romania || Health data intermediary
|-
| [[Ontotext]] || Bulgaria || Knowledge graph technology
|-
| [[Averbis]] || Germany || NLP / 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
|-
| [[European Heart Network]] || Belgium || Patient advocacy (cardiovascular)
|-
| [[B!LOBA]] || Belgium || Data management
|-
| [[DFP Research]] || Spain || Research partner
|-
| [[EURICE]] || Germany || Project management
|}

== Related Topics ==
* [[Knowledge Graphs in Health]]
* [[Interoperability]]
* [[Longitudinal Journals]]
* [[EU Regulation]]

== See Also ==
* [https://cordis.europa.eu/project/id/101057062 CORDIS project page]
* [https://aidava.eu Official website]

<references />
[[Category:Project]]
[[Category:EU]]