Vocabulary integration environment: vine

Interoperability between distributed information systems requires an agreement of metadata standards, protocols, interfaces and controlled vocabularies. Such an agreement is often pursued by adopting standards published by organizations such as the International Organization for Standardization (ISO...

Full description

Autores:
Bermúdez, Luis
Tipo de recurso:
Article of journal
Fecha de publicación:
2007
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/24123
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/24123
http://bdigital.unal.edu.co/15160/
Palabra clave:
Computer Software
Artificial Intelligence
Software Tools.
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:Interoperability between distributed information systems requires an agreement of metadata standards, protocols, interfaces and controlled vocabularies. Such an agreement is often pursued by adopting standards published by organizations such as the International Organization for Standardization (ISO) and the Open Geospatial Consortium (OGC). These standards are general and do not fully dictate the control vocabularies used for annotating metadata. Therefore, when communities share metadata they encounter semantic conflicts because of the “stage�, “gage height� and “water elevation� are different concepts that are semantically equivalent. To be able to solve these semantic heterogeneities, VINE, the Vocabulary Integration Environment tool, was created. This tool was successfully used at the workshop “Advancing Domain Vocabularies�, hosted by the Marine Metadata Initiative (MMI) in 2005. This tool specializes in “thesauri type� relations to map controlled vocabularies, encoded as (Resource Description Framework) RDF graphs. VINE also allows free text searches in the graph. It is a JAVA Eclipse Plugin and it follows the Model View Controller paradigm. The architecture of the tool and the concept of the smart deep graph search will be discussed.