A set of correspondences is also called an alignment.
For computer scientists, concepts are expressed as labels for data.
Historically, the need for ontology alignment arose out of the need to integrate heterogeneous databases, ones developed independently and thus each having their own data vocabulary.
In the Semantic Web context involving many actors providing their own ontologies, ontology matching has taken a critical place for helping heterogeneous resources to interoperate.
Ontology alignment tools find classes of data that are semantically equivalent, for example, "truck" and "lorry".
The classes are not necessarily logically identical.
According to Euzenat and Shvaiko (2007),[1] there are three major dimensions for similarity: syntactic, external, and semantic.
Coincidentally, they roughly correspond to the dimensions identified by Cognitive Scientists below.
A number of tools and frameworks have been developed for aligning ontologies, some with inspiration from Cognitive Science and some independently.
Ontology alignment tools have generally been developed to operate on database schemas,[2] XML schemas,[3] taxonomies,[4] formal languages, entity-relationship models,[5] dictionaries, and other label frameworks.
Since the emergence of the Semantic Web, such graphs can be represented in the Resource Description Framework line of languages by triples of the form
The problem of Ontology Alignment has been tackled recently by trying to compute matching first and mapping (based on the matching) in an automatic fashion.
Systems like DSSim, X-SOM[6] or COMA++ obtained at the moment very high precision and recall.
is the set of values, we can define different types of (inter-ontology) relationships.
[1] Such relationships will be called, all together, alignments and can be categorized among different dimensions: Subsumption, atomic, homogeneous alignments are the building blocks to obtain richer alignments, and have a well defined semantics in every Description Logic.
Let's now introduce more formally ontology matching and mapping.
An atomic homogeneous matching is an alignment that carries a similarity degree
, describing the similarity of two terms of the input ontologies
A (subsumption, homogeneous, atomic) mapping is defined as a pair
For cognitive scientists interested in ontology alignment, the "concepts" are nodes in a semantic network that reside in brains as "conceptual systems."
The focal question is: if everyone has unique experiences and thus different semantic networks, then how can we ever understand each other?
This question has been addressed by a model called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems for Translation).
[8] Existing matching methods in monolingual ontology mapping are discussed in Euzenat and Shvaiko (2007).
[1] Approaches to cross-lingual ontology mapping are presented in Fu et al.