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Semantic integration is the process of interrelating information from diverse sources, for example calendars and to do lists, email archives, presence information (physical, psychological, and social), documents of all sorts, contacts (including social graphs), search results, and advertising and marketing relevance derived from them. In this regard, semantics focuses on the organization of and action upon information by acting as an intermediary between heterogeneous data sources, which may conflict not only by structure but also context or value.
Applications and methods
In enterprise application integration (EAI), semantic integration can facilitate or even automate the communication between computer systems using metadata publishing. Metadata publishing potentially offers the ability to automatically link ontologies. One approach to (semi-)automated ontology mapping requires the definition of a semantic distance or its inverse, semantic similarity and appropriate rules. Other approaches include so-called lexical methods, as well as methodologies that rely on exploiting the structures of the ontologies. For explicitly stating similarity/equality, there exist special properties or relationships in most ontology languages. OWL, for example has "owl:equivalentClass", "owl:equivalentProperty" and "owl:sameAs".
Eventually system designs may see the advent of composable architectures where published semantic-based interfaces are joined together to enable new and meaningful capabilities. These could predominately be described by means of design-time declarative specifications, that could ultimately be rendered and executed at run-time.
Semantic integration can also be used to facilitate design-time activities of interface design and mapping. In this model, semantics are only explicitly applied to design and the run-time systems work at the syntax level. This "early semantic binding" approach can improve overall system performance while retaining the benefits of semantic driven design.
Semantic integration situations
From the industry use case, it has been observed that the semantic mappings were performed only within the scope of the ontology class or the datatype property. These identified semantic integrations are (1) integration of ontology class instances into another ontology class without any constraint, (2) integration of selected instances in one ontology class into another ontology class by the range constraint of the property value and (3) integration of ontology class instances into another ontology class with the value transformation of the instance property. Each of them requires a particular mapping relationship, which is respectively: (1) equivalent or subsumption mapping relationship, (2) conditional mapping relationship that constraints the value of property (data range) and (3) transformation mapping relationship that transforms the value of property (unit transformation). Each identified mapping relationship can be defined as either (1) direct mapping type, (2) data range mapping type or (3) unit transformation mapping type.
The Pacific Symposium on Biocomputing has been a venue for the popularization of the ontology mapping task in the biomedical domain, and a number of papers on the subject can be found in its proceedings.
- Data integration
- Enterprise integration
- Ontology-based data integration
- Ontology alignment
- Ontology matching
- Semantic heterogeneity
- Semantic technology
- Semantic translation
- Semantic unification