Design and Implementation of a Knowledge Graph for Integrating Global Health Data Using Neo4j
DOI: 10.3233/SHTI260882 ↗
Read the study design and limitations alongside its findings.
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Summary
Shows how Nouna population, weather, wearable and indoor climate datasets can be linked in a knowledge graph.
The summary describes the published study and the sources listed below.
Scientific notes: 2026-11-11 · Research connections: 12 November 2026Key findings
Key findings
A Nouna case study demonstrates how demographic, wearable and environmental records can be connected in a shared knowledge graph.
Study design & setting
Study design and methods
Population, setting or evidence base
Nouna methodological case study: census, five weather stations, 150 wearable participants and 600 households with indoor measurements; observation dates unspecified.
Methods
Entity extraction, graph representation and dataset fusion.
Limits to interpretation
Limitations
Single implementation, without comparative benchmarks; Linkage accuracy not quantified; Specialist querying and schema documentation required.
Research relevance
Research relevance
Supports integrated research questions across household and individual scales.
People, places & projects
Research connections
Labels identify published coauthors, study settings, planned protocol settings and wider methods or network connections.
Coauthors with research profiles
Sites & research settings
Study setting described in the publication
↗Methods / network contextHeidelberg · GermanyData-methods study
↗Projects & methods connections
Published sources & review scope
Sources
This page summarises the publication. Sources and editorial scope ↗