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Dataset Open Access

COVID-19 Open Research Dataset (CORD-19)

Sebastian Kohlmeier; Kyle Lo; Lucy Lu Wang; JJ Yang

A full description of this dataset along with updated information can be found here.

In response to the COVID-19 pandemic, the Allen Institute for AI has partnered with leading research groups to prepare and distribute the COVID-19 Open Research Dataset (CORD-19), a free resource of scholarly articles, including full text content, about COVID-19 and the coronavirus family of viruses for use by the global research community.

This dataset is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in support of the fight against this infectious disease. The corpus will be updated weekly as new research is published in peer-reviewed publications and archival services like bioRxivmedRxiv, and others.

By downloading this dataset you are agreeing to the Dataset license. Specific licensing information for individual articles in the dataset is available in the metadata file.

Additional licensing information is available on the PMC websitemedRxiv website and bioRxiv website.

Dataset content:

  • Commercial use subset
  • Non-commercial use subset
  • PMC custom license subset
  • bioRxiv/medRxiv subset (pre-prints that are not peer reviewed)
  • Metadata file
  • Readme

Each paper is represented as a single JSON object (see schema file for details).

Description:

The dataset contains all COVID-19 and coronavirus-related research (e.g. SARS, MERS, etc.) from the following sources:

  • PubMed's PMC open access corpus using this query (COVID-19 and coronavirus research)
  • Additional COVID-19 research articles from a corpus maintained by the WHO
  • bioRxiv and medRxiv pre-prints using the same query as PMC (COVID-19 and coronavirus research)

We also provide a comprehensive metadata file of coronavirus and COVID-19 research articles with links to PubMedMicrosoft Academic and the WHO COVID-19 database of publications (includes articles without open access full text).

We recommend using metadata from the comprehensive file when available, instead of parsed metadata in the dataset. Please note the dataset may contain multiple entries for individual PMC IDs in cases when supplementary materials are available.

This repository is linked to the WHO database of publications on coronavirus disease and other resources, such as Microsoft Academic Graph, PubMed, and Semantic Scholar. A coalition including the Chan Zuckerberg Initiative, Georgetown University’s Center for Security and Emerging TechnologyMicrosoft Research, and the National Library of Medicine of the National Institutes of Health came together to provide this service.

Citation:

When including CORD-19 data in a publication or redistribution, please cite the dataset as follows:

In bibliography:

COVID-19 Open Research Dataset (CORD-19). 2020. Version 2020-MM-DD. Retrieved from https://pages.semanticscholar.org/coronavirus-research. Accessed YYYY-MM-DD. 10.5281/zenodo.3715505

In text:

(CORD-19, 2020)

The Allen Institute for AI and particularly the Semantic Scholar team will continue to provide updates to this dataset as the situation evolves and new research is released.

Files (671.3 MB)
Name Size
all_sources_metadata_2020-03-13.readme
md5:d31945c945f079e216224c0abe94ad3f
1.1 kB Download
biorxiv_medrxiv.tar.gz
md5:ac41a4ab504ff5b34e118f8e98960d6c
13.8 MB Download
changelog
md5:13a14018cdc1078f32cf5b328413a5f5
577 Bytes Download
comm_use_subset.tar.gz
md5:039dec4d4b93100b655a5c9352266c14
191.5 MB Download
COVID.DATA.LIC.AGMT.pdf
md5:b5cdcc5de0c8c13fdff6b987505968f0
26.7 kB Download
custom_license.tar.gz
md5:0dd50542926f360e02cc6d43fab90b63
361.0 MB Download
json_schema.txt
md5:1d4fb092a058469831e9b5528941e5e5
2.9 kB Download
metadata.csv
md5:10d22a8bb7fdc66b6b331947eef85781
62.8 MB Download
noncomm_use_subset.tar.gz
md5:f23a9b0a7c13739d247d9e8183723181
42.3 MB Download
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