|Oracle® Database Semantic Technologies Developer's Guide
11g Release 2 (11.2)
|PDF · Mobi · ePub|
The following are selected terms relevant to the Oracle Database implementation of semantic technologies support. This is not a comprehensive RDF and OWL glossary.
Part of a data access constraint defines additional graph patterns to be applied on the resources that match the match pattern before they can be used to construct the query results. See also: match pattern
A set of triple patterns. From the W3C SPARQL Query Language for RDF Recommendation: "SPARQL graph pattern matching is defined in terms of combining the results from matching basic graph patterns. A sequence of triple patterns interrupted by a filter comprises a single basic graph pattern. Any graph pattern terminates a basic graph pattern."
A graph in which every node of it is connected to, bidirectionally, every other node in the same graph.
An open source bioinformatics software platform for visualizing molecular interaction networks and integrating these interactions with gene expression profiles and other state data. (See
http://www.cytoscape.org/.) An RDF viewer (available for download) is provided as a Cytoscape plug-in.
An object containing precomputed triples that can be inferred from applying a specified set of rulebases to a specified set of models. See also: rulebase
A named dictionary entity that determines the characteristics of a semantic index that is created using the policy. Each extractor policy refers, directly or indirectly, to an instance of an extractor type.
A combination of triples constructed by combining triple patterns in various ways, including conjunction of triple patterns into groups, optionally using filter conditions, and then combining such groups via connectors similar to disjunctions, outer-joins, and so on. SPARQL querying is based around graph pattern matching.
The ability to make logical deductions based on rules. Inferencing enables you to construct queries that perform semantic matching based on meaningful relationships among pieces of data, as opposed to just syntactic matching based on string or other values. Inferencing involves the use of rules, either supplied by Oracle or user-defined, placed in rulebases.
An application that processes unstructured documents and extract meaningful information from them, often using natural-language processing engines with the aid of ontologies.
An Oracle-supplied adapter (available for download) for Jena, which is a Java framework for building Semantic Web applications.
Part of a constraint that determines the type of access restriction it enforces and binds one or more variables to the corresponding data instances accessed in the user query. See also: apply pattern
A user-created semantic structure that has a model name, and refers to triples stored in a specified table column. Examples in this manual are the Articles and Family models.
A shared conceptualization of knowledge in a particular domain. It consists of a collection of classes, properties, and optionally instances. Classes are typically related by class hierarchy (subclass/ superclass relationship). Similarly, the properties can be related by property hierarchy (subproperty/ superproperty relationship). Properties can be symmetric or transitive, or both. Properties can also have domain, ranges, and cardinality constraints specified for them.
An Oracle-defined subset of OWL capabilities; refers to the elements of the OWL standard supported by the Oracle Database semantic technologies native inferencing engine.
An object that can contain rules. See also: rule
An index of type MDSYS.SEMCONTEXT, created on textual documents stored in a column of a table, and used with information extractors to locate and extract meaningful information from unstructured documents. See also: information extractor
An Oracle-supplied adapter (available for download) that integrates the popular Sesame Java APIs with Oracle Semantic Technologies support.
A data model that is especially useful for representing thesauri, classification schemes, taxonomies, and other types of controlled vocabulary. SKOS is based on standard semantic web technologies including RDF and OWL, which makes it easy to define the formal semantics for those knowledge organization systems and to share the semantics across applications.
Similar to an RDF triple, but allows use of a variable in place of any of the three components (subject, predicate, or object). Triple patterns are basic elements in graph patterns used in SPARQL queries. A triple pattern used in a query against an RDF graph is said to match if, substitution of RDF terms for the variables present in the triple pattern, creates a triple that is present in the RDF graph. See also: graph pattern