Ontology Application Framework

The objective of the framework is to provide a common terminology for describing applications of ontologies and the benefits that ontologies deliver within these applications. In addition to classifying ontology applications, this provides the basis for benchmarks and the ability to compare different applications of ontologies.

Dimensions

Functionality
How are the ontologies used?
- Matching / mapping of concepts
- Automated inference
- Classification
- Specification
Architecture
Are the ontologies being applied to a single system or are they being used among multiple systems?
When are the ontologies used?
Are the ontologies used at design time for the system or are they used by the system at runtime?
Who is using the ontologies?
- Ontology Author
- Data Author
- Application Developer
- Application User
- Knowledge Worker
What ontologies are used?
Problem addressed
Why are the ontologies being used?
Benefit
What is the impact of the ontologies on the functional/nonfunctional requirements of existing system?
- The ontologies support new functional requirements within system.
- The ontologies support nonfunctional requirements of the system: quality, performance, maintenance, cost, portability, reliability, scalability, robustness, usability, and extensibility.
  The value metrics for evaluating the benefits associated with nonfunctional requirements are the same metrics used for nonfunctional requirements themselves.

An Initial Classification of Ontology Applications

We can use the above ``dimensions" to identify the following classes of applications.

Semantic integration
- information integration
  Multiple information resources are combined using ontologies at runtime to match concepts with similar meaning.
- database integration
  Queries that require multiple databases are specified using common ontologies and data schema are matched using these ontologies at runtime.
- software interoperability
  Software systems exchange sentences that are written using ontologies. Each software software uses an ontology (either its own or a set of shared ontology) to translate the exchanged sentences at runtime.
- software access
  Ontologies provide a uniform conceptual interface to multiple software applications.
Decision Support
- deduction from Axioms via Theorem Provers
  The axioms of the ontology and domain theories are used to entail queries using a general-purpose automated theorem prover at runtime.
- deduction from Axioms via Special-Purpose Reasoners
  Special-purpose algorithms are implemented that are sound (and possibly complete) with respect to the set of sentences that are entailed/satisfied by the ontology at runtime.
- validation of integrity constraints
Semantic Augmentation
- ontology-based algorithms
  Existing algorithms use classes and relations within ontologies at design time to define search space and specify heuristics to guide search
- ontology embedded into software
  Object-oriented implementation (e.g. Java classes) generated from classes in the ontology at design time.
- model-driven design
  Design (enterprise or manufacturing artefact) is specified using the ontology and exported into software.
- ontology-based standards
  Terminology within a standard is axiomatized by an ontology. Conformance with the standard is evaluated with respect to this axiomatization.
Knowledge Management
- discovery
  Patterns in data are identified by matching against the classes, relations, and axioms of the ontology
- categorization of information resources
  An ontology is used to organize unstructured information resources by identifying classes and relations within the ontology with terms that appear in the resources.
- knowledge capture
  Classes in the ontology provide templates for gathering knowledge from subject matter experts.