REDASA COVID-19: Curated Medical Documents and Annotations

REDASA COVID-19 Open Data provides a snapshot of curated medical documents and annotations for COVID-19 research. The collection includes text documents extracted from the CORD-19 dataset and other sources, along with relevance-ranked documents and ground-truth annotations. It was produced by the REDASA consortium, which includes Imperial College London.

Use Cases

• Train information retrieval models based on the relevance-ranked documents surfaced for specific medical questions.
• Develop text mining pipelines for COVID 19 research based on the large collection of extracted medical documents.
• Create or evaluate question-answering systems using the provided GroundTruth annotations.
• Conduct meta-analysis of COVID-19 literature using the curated document collection from multiple sources.

Strengths

• Includes ground-truth annotations created by a curator community, which can support supervised learning.
• Documents are sourced from multiple relevant collections, including CORD-19, as mentioned in the description.
• Data is licensed under CC-BY-4.0, permitting reuse with attribution.

Limitations

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

Provenance

Source

REDASA Consortium, Imperial College London, UK

Collection Method

Output of a curation protocol produced by a curator community, sourcing from CORD-19 and other relevant datasets.

Time Range

Temporal coverage is not specified.

Freshness

Last updated date is unknown.

Geography

Spatial coverage is not specified.