Linked COVID-19 Data from Johns Hopkins University and ECDC

Linked COVID-19 Data integrates case statistics from Johns Hopkins University and the European Centre for Disease Prevention and Control using a formal ontology. The data is structured as RDF files, enabling semantic queries and integration with other linked datasets. It was created by Florian Thiery for the Linked COVID-19 Data Dashboard.

Use Cases

• Model disease spread dynamics based on linked time-series case data.
• Perform semantic queries and federated analysis using the RDF graph structure.
• Compare COVID-19 case trends from two major international sources.
• Build integrated public health dashboards using the provided ontology.

Strengths

• Integrates data from two authoritative public health institutions: Johns Hopkins University and the European Centre for Disease Prevention and Control.
• Uses a formal COVID-19 ontology for semantic structuring, facilitating data linking.
• Data is prepared for the Linked COVID-19 Data Dashboard, suggesting a practical application.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file size, and temporal coverage are unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Johns Hopkins University (JHU) and European Centre for Disease Prevention and Control (ECDC).

Collection Method

Data is linked and structured using the COVID-19 Ontology (10.5281/zenodo.3757828).