Published August 17, 2024 | Version 2023.6
Dataset Open

Easy ORCID

Description

The first-party ORCID data dump uses a data structure that is overly complex for most use cases. This Zenodo record contains a derived version that is much more straightforwards, accessible, and smaller. So far, this includes employers, education, external identifiers, and publications linked to PubMed. It adds additional processing to ground employers and educational instutitions using the Research Organization Registry (ROR). It also does some minor string processing, such as standardization of education types (e.g., Bachelor of Science, Master of Science) and standardization of PubMed references.

Records

The records.jsonl.gz file is a JSON Lines file where each row represents a single ORCID record in a simple, well-defined schema (see schema.json). The records_hq.jsonl.gz file is a subset of the full records file that only contains records that have at least one ROR-grounded employer, at least one ROR-grounded education, or at least one publication indexed in PubMed. The point of this subset is to remove ORCID records that are generally not possible to match up to any external information.

This record also contains a SQLite database orcid.db that contains tables for researchers and for organizations. This is useful for quick lookup of data based on an ORCID local unique identifier.

Employers, educational institution, and memberships that couldn't be grounded to an ROR record are listed in affiliation_missing_ror.tsv.

Nomenclature Authority Cross-References

Websites, social links, and other identifiers are parsed and standardized to comply with the Bioregistry then shared using the Simple Standard for Sharing Ontological Mappings (SSSOM) in the sssom.tsv.gz file. This allows for getting Scopus, Web of Science, GitHub, Google Scholar, and other profiles for records that include them. This information is also available through the main records file.

Authorship Links

Authorships are extracted and standardized in the pubmeds.tsv.gz file, which contains an ORCID column and PubMed column that has been pre-sanitized to only contain local unique identifiers. This information is also available through the main records file.

Lexical Indexes

It includes two pre-built Gilda indexes for named entity recognition (NER) and named entity normalization (NEN). One contains all records, and the second is filtered to high-quality records. The following Python code snipped can be used for grounding:

from gilda import Grounder
url = "https://zenodo.org/records/11474470/files/gilda_hq.tsv.gz?download=1"
grounder = Grounder(url)
results = grounder.ground("Charles Tapley Hoyt")

Ontology Artifacts

The file orcid.ttl.gz is an OWL-ready RDF file that can be opened in Protégé or used with the Ontology Development Kit. It can also be converted into OWL XML, OWL Functional Notation, or other OWL formats using ROBOT. This artifact can serve as a replacement for the ones generated by https://github.com/cthoyt/orcidio, which was a smaller-scale way of turning ORCID records for contributors to OBO Foundry Ontologies into a small OWL file. Now, the export here contains all ORCID records with names.

Reproduction

It is automatically generated with code in https://github.com/cthoyt/orcid_downloader.

Files

schema.json

Files (6.5 GB)

Name Size Download all
md5:2da93dfebc320038f9ba2aa267b39300
110.2 MB Download
md5:1f5ed44633130811cfb974a8f47464a4
1.9 GB Download
md5:902226e7e330bf513c121d8611af426a
661.8 MB Download
md5:56de51e912121ad10fac43583bf2f1ca
1.7 GB Download
md5:d656e8a766158abc05c8e6bc262ac4a9
385.1 MB Download
md5:02fd19f4ef86443429ab643d4228bb96
19.2 MB Download
md5:8829b83ba498b901fc7a1d7320040520
920.8 MB Download
md5:e18decdd695473e5c6b040f699e63d04
662.1 MB Download
md5:2c301b44e63079aa460e6ca74b3c42a3
5.7 kB Preview Download
md5:7f141e4eb0e86a41d97fc5307b3061d4
96.0 MB Download

Additional details

Related works

Is derived from
Dataset: 10.23640/07243.24204912.v1 (DOI)
Requires
Software: 10.5281/zenodo.11371784 (DOI)