Terminology-oriented database: Difference between revisions

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}}</ref> It implements [[concept]]s defined in a [[terminology model]]. Compared with [[object-oriented database]]s, the terminology-oriented database requires some minor conceptual extensions on the schema level as supporting set relations (super-set, subset, intersection etc.), weak-typed collections or shared inheritance.

The data model of a terminology-oriented database is high-level; the terminology-oriented database provides facilities for transforming a [[terminology model]] provided by subject area experts completely into a [[database schema]]. The target schema might be the [[database schema]] for an [[object-oriented database]] as well as a [[relational database]] schema, or even an [[XML]] schema. Typically, terminology-oriented databases are not bound on a specific database type. Since the information content, which can be stored in [[object-oriented database]]sdatabases and in [[relational database]]s, is identical,<ref>{{cite conference

| url = http://www.odaba.com/content/downloads/documentation/P1_UnifiedDatabaseTheory.pdf

| title = Unified Database Theory

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|date=July 2003

| conference = The 7th World Multi-Conference on SYSTEMICS, CYBERNETICS AND INFORMATICS - SCI 2003

| conferenceurlconference-url = https://lists.cs.columbia.edu/pipermail/tccc/2002-October/000467.html

| ___location = Orlando, Florida (USAUS)

| format = PDF document

}}</ref> data for a terminology-oriented database can be stored theoretically in any type of database as well as in an XML file. Thus, terminology-oriented databases may support several database systems for storing application data.

Terminology Databasesdatabases, when these contain Termsterms and Vocabulariesvocabularies, these become valuable for Ontologiesontologies and in turn ontologies can help process associated triples or complex predicates thus going deeper than hierarchies or keys in RDBMS. [[Semantic mapper|Semantic mapping]] can also enhance performance.

== References ==