EQ-Graph · EuroQol seed grant 2582-SG
About this project
EQ-Graph is a research knowledge graph of EuroQol-funded projects and their associated publications. It connects projects and researchers to the studies, populations, instruments, methods, findings, limitations, and reusable products reported in the literature.
The aim is to make the funded research portfolio easier to explore as a connected body of evidence. The graph is not an index of every paper that uses an EQ instrument.
Shoulders built the project under a EuroQol seed grant. The team is Paul Schneider, principal investigator; Sofia Fabishevskaya, co-investigator; and Kazik Pogoda, advisor.
Beta research release1,024 funded projects ·797 included publications ·798 studies · ontology 0.13
Methods
From funded projects to structured research evidence
We combined the funded-project register with publication searches, then used titles and abstracts to decide which full texts to retrieve. Full-text assessment confirmed EuroQol support or direct project origin and recorded the scientific content of each eligible publication.
Structured metadata was parsed before semantic extraction. Canonical registries, controlled vocabularies, source locators, and deterministic checks then kept equivalent evidence together and explicit uncertainty visible.
Ontology
What the graph can represent
The diagram shows the complete semantic layer. The index below it names the main fields recorded for each type.
Ontology 0.13
The semantic model
- Entity
- Canonical registry
- Control or assertion
Portfolio
- Project
- title · abstract · investigator · working group · years · status
- Publication
- bibliographic metadata · funding · URLs · citations · editorial status
- Person
- names · ORCID · authorship · membership · project role
- Study
- primary family · purposes · execution state · result state
Study structure
- StudyPart
- separable sample, data source, method, or state
- Design
- component · time · comparison · allocation
- Population + Sample
- population description · role · flow stage · size
- DataUse
- source · origin · level · purpose
- TaskDesign
- profiles · attributes · levels · blocks · randomisation
- Administration
- respondent · channel · setting · language · time point
- StudyFactor
- condition · comparator · determinant · modifier · stage
- StakeholderInvolvement
- group · activity · stage · role · influence
Scientific use
- InstrumentUse
- instrument identity · context · function
- MethodUse
- method identity · context · function
- ProtocolUse
- protocol identity · context · function
- ModelUse
- model identity · context · function · analytic role
- SoftwareUse
- software identity · context · function
- ProductUse
- existing product examined, compared, or synthesised
- ScoringUse
- instrument responses linked to a scoring product
Evidence and control
- Outcome
- family · source label
- Finding
- statement · selected value · unit · subgroup · comparator · uncertainty
- Interpretation
- source-reported meaning, separate from the finding
- Limitation
- source-reported limitation
- Product
- reusable output · type · dated state assertions
- Concept
- cross-cutting theme for discovery
- Gap
- unmapped value · unmodelled aspect · uncertain mapping · not reported
- SourceConflict
- contradictory source statements kept together
Information types: controlled values · canonical registries · open source-faithful text · provenance
Ontology development
Built through comparison, not assumed in advance
We did not start with a general ontology of research. Independent AI agents reviewed different samples of EuroQol papers and the questions researchers wanted to ask, then proposed structures that covered the evidence they found.
We compared the proposals, combined stable elements, and tested the result on unseen papers. Each round showed where a category was ambiguous, missing, or more detailed than the intended use required. We revised the ontology only when source evidence showed a repeated need.
Four 15-paper development rounds and two 20-publication calibration batches produced version 0.13. Controlled vocabularies now keep equivalent instruments and methods under one identity, while genuinely new terms follow an explicit review route.
Contact
Corrections and contributions are welcome.
Please contact us if information is wrong or missing, if a funded project or publication is absent, or if you want to contribute. We also welcome questions about the method, ontology, and data.