ARCHIVE
rxiv_geo.zip (118.87 MB)
ARCHIVE
citation_metadata.zip (2.93 MB)
ARCHIVE
rxiv_metadata.zip (986.74 MB)
ARCHIVE
mag_fos.zip (16.41 MB)
ARCHIVE
covid_semantic.zip (12.65 MB)
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Artificial Intelligence and the Fight Against COVID-19
Version 5 2020-06-23, 15:07
Version 4 2020-06-22, 12:57
Version 3 2020-06-21, 20:18
Version 2 2020-06-14, 14:09
Version 1 2020-06-14, 13:46
dataset
posted on 2020-06-23, 15:07 authored by Juan Mateos-GarciaJuan Mateos-Garcia, Joel Klinger, Konstantinos StathoulopoulosDatasets analysed in a paper mapping AI research activity against COVID-19. Includes:
-rxiv metadata: A dataset with metadata about 1.8m papers from arXiv, biorXiv and medrXiv as of end May 2020 enriched with dummies about whether the papers are related to AI and/or COVID-19 research (updated 22/06/2020 to fix some ids)
-rxi_geo: A dataset with geographical metadata for papers based on the institutional affiliations of their authors after matching with the GRID database.
-covid_semantic: A dataset with topic information about COVID-19 papers based on a semantic analysis of their abstracts, including the clusters where papers have been classified and their topic mixes (updated 22/06/2020 to fix some ids).
-citation_metadata: Two JSON objects. One contains a lookup between COVID-19 related papers in the rXiv corpus and the papers they cite. Another contains metadata about the cited papers including their fields of study.
-mag_fos: A dataset with the Microsoft Academic Graph field of study hierarchy we use in our analysis (added 22 June 2020)
Each zipped folder includes a data dictionary.
For information about data processing and analysis in: https://github.com/nestauk/ai_covid_19