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14 results for “ORCID”
ORCID data to accompany Study of ORCID Adoption Across Disciplines and Locations
<p>Data gathered in January 2017 from the ORCID registry in support of Study of ORCID Adoption Across Disciplines and Locations. Study conducted as part of Horizon 2020 project THOR (http://project-thor.eu).</p> <p><strong>ORCID uptake by discipline and region.xlsx</strong> : Master file of all processed metrics with breakdowns by discipline and region. (For description of selection of disciplinary taxonomy and processing steps, see associated paper.)</p> <p><strong>All other .csv files</strong> : Underlying data for processed metrics. (For description of "full counts" and other factors of data gathering, see associated paper.)</p>
LSPO: A Large-Scale Physics ORCiD-Linked Dataset for Author Name Disambiguation
<p>The LSPO dataset, a Large-Scale Physics ORCiD-Linked Dataset for Author Name Disambiguation is comprised of 554,962 NASA/ADS publications linked to 125,486 unique researchers through ORCiD identifiers. The available meta-data fields are: ORCiD identifier, author name, affiliation, title, asbtract, and name block. The dataset can be utilized to make pairs or triplets for training a author name disambiguation model. </p>
Mapping between zbMATH Open identifiers, DOIs, ORCIDs and arXiv identifiers
<p>The second version of the mapping between zbMATH Open identifiers for <a href="https://www.wikidata.org/w/index.php?title=Property:P1556&oldid=1755821772">authors</a> and <a href="https://www.wikidata.org/w/index.php?title=Property:P894&oldid=1766254659">documents</a> and <a href="https://www.wikidata.org/wiki/Property:P356">DOIs</a> and <a href="https://www.wikidata.org/wiki/Property:P496">ORCIDs</a> in CSV format.</p> <ul> <li>The file authors.csv contains the mapping between zbMATH Open author id and ORCIDs for 38 159 authors.</li> <li>The file documents.csv contains the mapping between zbMATH Open document id and DOI for 2 813 563 documents.</li> </ul> <p>Beginning from this version, we also provide the mapping between <a href="https://www.wikidata.org/w/index.php?title=Property:P894&oldid=1766254659">documents</a> and <a href="https://www.wikidata.org/w/index.php?title=Property:P818&oldid=2151126552">arXiv</a> in CSV format</p> <ul> <li>The file arxiv.csv contains the mapping between zbMATH Open document id and arXiv identifiers for 528 640 documents.</li> </ul> <p>See https://zbmath.org/about/ (section Full Text Links) for a live version of this dataset. That version is more current but less reproducible. Moreover, the dataset here is restricted to documents with a permanent zbMATH Open identifier in the form <code>Zbl d+.d+</code>.</p> <p> </p> <p> </p>
Datos de perfiles en ORCID de instituciones educativas públicas de Panamá 2021
<p>Datos de perfiles de instituciones educativas publicas de Panamá (UTP, UP, UNACHI) con periles en ORCID extraidos en el año 2021.</p> <p>Datos de la tabla:</p> <ul> <li>orcid-identifier.uri: identificador ORCID</li> <li>nombre: nombre del perfil</li> <li>ORCID: afiliado o no a la institución</li> <li>keyword : palabras claves en el perfil</li> <li>alias : alias en el perfil</li> <li>cantidad: cantidad de documentos en el perfil<br><br></li> </ul>
Dataset for publication: "Exploring ORCID adoption and metadata presence in Spain's research landscape"
<p>This dataset is for the publication "<em>Exploring ORCID adoption and metadata presence in Spain's research landscape</em>" and is composed of the following files:</p> <ul> <li><strong>norm_aff.tsv</strong> (2795x5) - Curated list of role titles</li> <li><strong>openalex_all_spanish.csv</strong> (811062x4) - List of Spanish authors retrieved from OpenAlex</li> <li><strong>orcid_affiliation.csv</strong> (377377x23) - Activity employment affiliation of Spanish ORCID records</li> <li><strong>orcid_full_maps.csv</strong> (15182292x6)- Topic classification of Spanish ORCID records</li> <li><strong>orcid_metrics.csv</strong> (226512x39) - Metadata availability in Spanish ORCID records</li> </ul>
Easy ORCID
<p>The <a href="https://doi.org/10.23640/07243.24204912">first-party ORCID data dump</a> 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 <a href="https://ror.org/">Research Organization Registry (ROR)</a>. 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.</p> <h2>Records</h2> <p>The <code>records.jsonl.gz</code> file is a <a href="https://jsonlines.org/">JSON Lines</a> file where each row represents a single ORCID record in a simple, well-defined schema (see <code>schema.json</code>). The <code>records_hq.jsonl.gz</code> 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.</p> <p>This record also contains a SQLite database <code>orcid.db</code> that contains tables for researchers and for organizations. This is useful for quick lookup of data based on an ORCID local unique identifier.</p> <p>Employers, educational institution, and memberships that couldn't be grounded to an ROR record are listed in <code>affiliation_missing_ror.tsv</code>.</p> <h2>Nomenclature Authority Cross-References</h2> <p>Websites, social links, and other identifiers are parsed and standardized to comply with <a href="https://github.com/biopragmatics/bioregistry/">the Bioregistry</a> then shared using the <a href="https://mapping-commons.github.io/sssom/">Simple Standard for Sharing Ontological Mappings (SSSOM)</a> in the <code>sssom.tsv.gz</code> 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.</p> <h2>Authorship Links</h2> <p>Authorships are extracted and standardized in the <code>pubmeds.tsv.gz</code> 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.</p> <h2>Lexical Indexes</h2> <p>It includes two pre-built <a href="https://github.com/gyorilab/gilda">Gilda</a> 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:</p> <pre><code>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")<br></code></pre> <h2>Ontology Artifacts</h2> <p>The file <code>orcid.ttl.gz</code> is an OWL-ready RDF file that can be opened in Protégé or used with the <a href="https://github.com/INCATools/ontology-development-kit">Ontology Development Kit</a>. It can also be converted into OWL XML, OWL Functional Notation, or other OWL formats using <a href="https://robot.obolibrary.org/">ROBOT</a>. This artifact can serve as a replacement for the ones generated by <a href="https://github.com/cthoyt/orcidio">https://github.com/cthoyt/orcidio</a>, 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.</p> <h2>Reproduction</h2> <p>It is automatically generated with code in <a href="https://github.com/cthoyt/orcid_downloader">https://github.com/cthoyt/orcid_downloader</a>.</p>
2020 ORCID Austria Tech-Workshop
<p>Video recording of the ORCID Austria Tech-Workshop on November 25, 2020. For more information https://www.tuwien.at/kooperationen/orcid/en/orcid-resources/webinars-and-workshops/</p>
ORCID for Wikidata – Data enrichment forscientometric applications
<p>For the 19th International Semantic Web Conference (ISWC 2020) at 2020-11-02 I created a short video to introduce the OrcBot project.</p> <p>For the conference publication see: https://ceur-ws.org/Vol-2773/paper-09.pdf</p> <p>GitHub repositorium: https://github.com/EvaSeidlmayer/orcid-for-wikidata</p>
Einstein ORCID
<p>Einstein after THOR bootcamp seminary</p>
Orcid ID
Open the record for dataset details and reuse information.
Supplementary table to "A search for locked ORCIDs reveals a batch of odd accounts"
<p>Supplementary table for: https://doi.org/10.1007/s12262-023-03779-z</p>
ORCID in ZORA - E-Mail Signature @ UZH
<p>The figures were created as part of an information campaign for ORCID at the University of Zurich. All images are freely available under a public domain license. Please remove the UZH logo and the URL in case of any subsequent use. Regarding the use of the ORCID logo, please refer to the Trademark and iD Display Guidelines of ORCID: https://orcid.org/trademark-and-id-display-guidelines</p>
Data from: Introducing ORCID
ORCID wasn't intended as a massive longitudinal survey of the global population of scientists, but with 3 million profiles and growing, it is becoming just that. So far a quarter of those researchers have voluntarily added personal information to their public ORCID profiles including the years, locations, and descriptions of their education and employment histories. As this voluntary sampling grows, the demographic and migration patterns of the scientific workforce is coming into focus. The biases are also apparent: ORCID users skew young, and certain countries are over- and underrepresented. The code for processing and analyzing the raw profile data are offered here to help researchers explore ORCID, the largest open repository of scientific careers. [NOTE: further context for this data package is provided in Bohannon (2017) 'Restless Minds' at http://dx.doi.org/10.1126/science.356.6339.690].
Data from: Introducing ORCID
Open the record for dataset details and reuse information.
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