Ontology (information science)
Introduction
Ontology in the field of information science is a formal representation of knowledge as a set of concepts within a domain, and the relationships between those concepts. It is used to reason about the entities within that domain, and can be used to describe the domain. In theory, an ontology is a "formal, explicit specification of a shared conceptualization". An ontology provides a shared vocabulary, which can be used to model a domain — that is, the type of objects and/or concepts that exist, and their properties and relations.
History
The concept of ontology has its roots in philosophy, where it is the name given to the study of the nature of being, existence or reality, as well as the basic categories of being and their relations. In information science, however, ontology has a slightly different meaning. The term was first used in this context by the artificial intelligence community in the late 1980s, and has been employed in a variety of fields ever since, including computer science, information retrieval, and knowledge management.
Ontology Components
An ontology consists of several components, including:
- Classes: These are the concepts that are present in the domain. They are often hierarchical and are based on a taxonomic structure.
- Attributes: These are the properties or characteristics that the classes possess.
- Relations: These are the ways in which the classes and attributes are connected to one another.
- Function Terms: These are the functions or methods that can be performed on the classes and attributes.
- Restrictions: These are the rules that apply to the classes and attributes.
- Individuals: These are the instances or members of the classes.
Ontology Languages
There are several languages that can be used to create ontologies, including:
- RDF and RDFS: These are simple languages that can be used to create ontologies. They are based on the idea of making statements about resources in the form of subject-predicate-object expressions, known as triples.
- OWL: This is a more complex language that can be used to create ontologies. It is based on description logic, and it allows for greater expressivity than RDF and RDFS.
- UML: This is a general-purpose, developmental, modeling language in the field of software engineering, that is intended to provide a standard way to visualize the design of a system.
Ontology in Computer Science
In computer science, ontologies are used in artificial intelligence, the Semantic Web, systems engineering, software engineering, biomedical informatics, library science, enterprise bookmarking, and information architecture as a form of knowledge representation about the world or some part of it. The creation of domain ontologies is also fundamental to the definition and use of an enterprise architecture framework.
Ontology in Information Retrieval
In information retrieval, an ontology can improve the precision and recall of the system by using the relationships between the concepts in the ontology. It can also be used to disambiguate the meaning of terms that have multiple meanings.
Ontology in Knowledge Management
In knowledge management, an ontology can be used to create a common vocabulary and shared understanding among different stakeholders. It can also be used to capture knowledge about a domain and to enable the reuse of this knowledge.
Ontology in Information Architecture
In information architecture, an ontology is used to create a structured and organized view of a domain. It can be used to improve the usability and findability of information in a system.
Ontology in Artificial Intelligence
In artificial intelligence, an ontology is used to represent knowledge about a domain. It can be used to enable reasoning about the entities within that domain and to support the creation of intelligent systems.
Ontology in Systems Engineering
In systems engineering, an ontology can be used to create a shared understanding of a system. It can be used to support the design and development of the system, as well as its operation and maintenance.
Ontology in Biomedical Informatics
In biomedical informatics, an ontology can be used to represent knowledge about biological and medical concepts. It can be used to support the integration and analysis of data from different sources.
Ontology in Library Science
In library science, an ontology can be used to create a structured and organized view of a domain. It can be used to improve the findability and usability of information in a library system.
Ontology in Enterprise Bookmarking
In enterprise bookmarking, an ontology can be used to create a structured and organized view of a domain. It can be used to improve the findability and usability of information in a bookmarking system.
Conclusion
In conclusion, ontology in information science is a powerful tool for representing knowledge about a domain. It provides a shared vocabulary that can be used to model a domain, and it can be used to reason about the entities within that domain. Ontologies are used in a variety of fields, including computer science, information retrieval, and knowledge management, and they can be created using a variety of languages, including RDF, RDFS, OWL, and UML.