- Composing theories
As understood by Philippe A. MARTIN
Definition: a list of formal terms and a list of formal definitions/constraint for these terms (and hence any domain representation/specification except for "beliefs" regarding individual objects).
Definition: (From: the Free On-line Dictionary of Computing)
An explicit formal specification of how to represent the objects, concepts and other entities that are assumed to exist in some area of interest and the relationships that hold among them.
For AI systems, what "exists" is that which can be represented. When the knowledge about a domain is represented in a declarative language, the set of objects that can be represented is called the universe of discourse. We can describe the ontology of a program by defining a set of representational terms. Definitions associate the names of entities in the universe of discourse (e.g. classes, relations, functions or other objects) with human-readable text describing what the names mean, and formal axioms that constrain the interpretation and well-formed use of these terms. Formally, an ontology is the statement of a logical theory.
A set of agents that share the same ontology will be able to communicate about a domain of discourse without necessarily operating on a globally shared theory. We say that an agent commits to an ontology if its observable actions are consistent with the definitions in the ontology. The idea of ontological commitment is based on the Knowledge-Level perspective.
ISI has been exploring a novel approach to assist in this process using
existing broad coverage ontologies such as the SENSUS and
WordNet ontologies.
The approach begins by identifying a small number of key domain terms (called
seeds). These terms are then mapped to terms in the SENSUS ontology (cf. figure
below part a).
Using a variety of structural and probabilistic heuristics, we then identify
terms in the ontology that relate to the seed terms (cf. figure below part b).
These terms delimit the domain relevant aspects of the larger ontology,
and are extracted to create an approximate domain-specific ontology (cf. figure
below part c).
The designer can then browse this ontology and delete unrelated terms
or import additional terms to arrive at an initial domain model.
This process
was used to create the ACP-SENSUS ontology for air campaign planning (ARPI).
Using 50 seed terms provided by experts, an initial ontology of approximately
1200 domain terms was created in less than a week. A detailed description
of this process is in Swartout & al. (1996).
Extracting a domain-specific ontology from a broad coverage ontology.
A prototype of an interactive merging capability was demonstrated at the I*3 workshop in November 1996. In this demonstration, Ontosaurus was used to augment the C2 Schema (JTF-ATD) with more detailed information about combat aircraft from an independently developed ACP ontology (ARPI). During the demonstration, the C2 Schema was extended by approximately 200 additional concepts within 10 minutes, a process which would take hours to days to complete without this tool.
Merging parts of one ontology into another.