FAST Linked Data
FAST Authority File
Search FAST Linked Data
Cheke, John, Sir, 1514-1557
Information about the Resource
- Identifier:
-
- 19872
- SKOS Preferred Label:
-
- Cheke, John, Sir, 1514-1557
- SKOS Alternative Label:
-
- Checus, Joannes, Sir, 1514-1557
Information about the Resource Source
- Document:
-
- in Dataset:FAST
- Primary Topic:http://id.worldcat.org/fast/19872
- Format:application/rdf+xml
- Date Created:2004-09-24T00:00:00.0
- Date Modified:2012-07-06T14:07:21.0
- Language: http://lexvo.org/id/iso639-3/eng
- Cataloged by agency: OCoLC
- Transcribed by agency: OCoLC
- Data Set:
-
- Title:FAST (Faceted Application of Subject Terminology) Data
-
License:
- Description:
- Title:Open Data Commons Attribution License (ODC-By) v1.0
- Comment:This is OCLC's "local copy" of the ODC-By license
- See Also: Open Data Commons Localization Note
- Same As: Open Data Commons Attribution License (ODC-By) v1.0
Different Formats Available
- Record Views
FAST is a project of OCLC Research.
- © 2011-2015 OCLC
- OCLC Privacy Policy
- Available under the OCLC Open Data Commons Attribution (ODC-By) License
Learn more about the FAST project.
The FAST Ontology can be found here.
The FAST Dataset is available for download.
The most recent update for FAST was 8/9/2017. A table of recent changes can be found here. The FAST database will be updated periodically. Our target is to update FAST at least twice each year.
For comments on FAST as Linked Data contact the FAST Team
FAST Projects
- searchFAST
- A full feature search interface to the FAST database.
- mapFAST
- mapFAST is a Google Maps mashup prototype designed to provide map based access to bibliographic records using FAST geographic and event authorities. Also available in Mobile versions.
- FAST Converter
- The FAST Converter is a Web interface for the conversion of LCSH headings to FAST headings.
- FAST Linked Data
- FAST as a Linked Data service to interact with the Semantic Web.
- assignFAST
- A Web service that automates the manual selection of FAST Subjects based on autosuggest technology.