MADS (Metadata Authority Description Schema)
E606690
MADS (Metadata Authority Description Schema) is an XML-based schema used primarily by libraries and related institutions to structure and manage authority data for names, subjects, and other controlled vocabularies.
All labels observed (1)
| Label | Occurrences |
|---|---|
| MADS (Metadata Authority Description Schema) canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T6519665 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MADS (Metadata Authority Description Schema) Context triple: [Library of Congress Network Development and MARC Standards Office, maintainsStandard, MADS (Metadata Authority Description Schema)]
-
A.
MODS (Metadata Object Description Schema)
MODS (Metadata Object Description Schema) is an XML-based bibliographic description standard designed to provide a flexible, user-friendly alternative to MARC for describing and sharing library and cultural heritage resources.
-
B.
S-100 metadata framework
The S-100 metadata framework is an IHO-developed standard that defines a flexible, interoperable structure for describing and managing geospatial and hydrographic data within the broader S-100 universal hydrographic data model.
-
C.
MARC
MARC is a regional planning and coordination agency serving the Kansas City metropolitan area, focusing on transportation, emergency services, environmental planning, and community development.
-
D.
MARC
MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
-
E.
METS
METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MADS (Metadata Authority Description Schema) Target entity description: MADS (Metadata Authority Description Schema) is an XML-based schema used primarily by libraries and related institutions to structure and manage authority data for names, subjects, and other controlled vocabularies.
-
A.
MODS (Metadata Object Description Schema)
MODS (Metadata Object Description Schema) is an XML-based bibliographic description standard designed to provide a flexible, user-friendly alternative to MARC for describing and sharing library and cultural heritage resources.
-
B.
S-100 metadata framework
The S-100 metadata framework is an IHO-developed standard that defines a flexible, interoperable structure for describing and managing geospatial and hydrographic data within the broader S-100 universal hydrographic data model.
-
C.
MARC
MARC is a regional planning and coordination agency serving the Kansas City metropolitan area, focusing on transportation, emergency services, environmental planning, and community development.
-
D.
MARC
MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
-
E.
METS
METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
- F. None of above. chosen
Statements (52)
| Predicate | Object |
|---|---|
| instanceOf |
XML schema
ⓘ
authority data schema ⓘ metadata schema ⓘ |
| abbreviation | MADS ⓘ |
| applicationArea |
archives
ⓘ
digital libraries ⓘ library catalogs ⓘ museum information systems ⓘ |
| dataModelType | XML element-based model ⓘ |
| developedBy | Library of Congress NERFINISHED ⓘ |
| domain |
information science
ⓘ
library science ⓘ |
| fullName | Metadata Authority Description Schema NERFINISHED ⓘ |
| hasComponent |
elements for identifiers
ⓘ
elements for names ⓘ elements for relationships between authorities ⓘ elements for subjects ⓘ elements for variant forms ⓘ |
| maintainedBy | Library of Congress NERFINISHED ⓘ |
| primarySerializationFormat | XML NERFINISHED ⓘ |
| purpose |
to provide a machine-readable format for authority records
ⓘ
to structure authority data for libraries and related institutions ⓘ to support interoperability of authority data ⓘ |
| relatedTo |
MARC 21
NERFINISHED
ⓘ
MARC 21 Authority Format NERFINISHED ⓘ MODS NERFINISHED ⓘ RDF NERFINISHED ⓘ SKOS NERFINISHED ⓘ |
| supports |
authority control
ⓘ
complex relationships between authority records ⓘ controlled subject access ⓘ corporate body authority records ⓘ geographic name authority records ⓘ name authority records ⓘ personal name authority records ⓘ subject authority records ⓘ temporal authority records ⓘ topic authority records ⓘ |
| supportsEncodingOf |
authority identifiers
ⓘ
broader-narrower relationships ⓘ preferred forms of names ⓘ related term relationships ⓘ see-also references ⓘ variant forms of names ⓘ |
| targetUsers |
archives
ⓘ
libraries ⓘ museums ⓘ other cultural heritage institutions ⓘ |
| usedFor |
authority data
ⓘ
controlled vocabularies ⓘ names ⓘ subjects ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: MADS (Metadata Authority Description Schema) Description of subject: MADS (Metadata Authority Description Schema) is an XML-based schema used primarily by libraries and related institutions to structure and manage authority data for names, subjects, and other controlled vocabularies.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
Library of Congress Network Development and MARC Standards Office
→
maintainsStandard
→
MADS (Metadata Authority Description Schema)
ⓘ