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Ontology


1. Introduction: Ontology emerged from the philosophical field as an area of study introduced by Aristotle and has been applied in many different ways. Philosophical ontology is describing the real world as it exists, while computational ontology is describing the world as it should be. In information science, ontology is a formal naming and definition of the types, properties, and interrelationships of the entities that really or fundamentally exist for a particular domain of discourse. The ontology is used to define the concepts, relationships and other distinctions that are relevant for modeling a domain. It is a representation of a set of concepts within a domain and the relationships between those concepts. In other words, ontology defines the vocabulary of a domain.

2. Definition: Ontology is a well-defined set of concepts that are ordered in some manner to create an agreed-upon vocabulary for exchanging information. In information science, ontology formally represents knowledge as a set of concepts within a domain, and the relationships between pairs of concepts.
In the context of knowledge management, ontology is referred as the shared understanding of some domains, which is often conceived as a set of entities, relations, axioms, facts and instances
Ontology is organized using a hierarchy and a set of relationships between its classes.
Artificial Intelligence (AI) community defined ontology in 1991 as “Ontology defines the basic terms and relations comprising the vocabulary of a topic area as well as the rules for combining terms and relations to define extensions to the vocabulary.”
In 1993 Gruber defined ontology as: “Formal explicit specification of shared conceptualization. The definition can be explained as follows:
a) Formal: Ontology should be machine readable and processed by an Artificial Intelligent (AI) system. We do not need there to be communication devices between people and people even people and machine. Ontology should be formally defined using a formal language
b) Specification: Means writing specifications of language syntax to satisfy certain criteria such as precision, non-unambiguity, consistency, completeness and implementation as independent statements; it should provide a communication device to enable users to share knowledge in consensual mode.
c) Shared: Means ontology represents a consensual knowledge that has been arranged and agreed on by groups typically as the result of a social network rather than an individual’s view.
d) Conceptualisation: This is an abstract model of domain knowledge driven by application for users, and represents ways in which it is committed by knowledge- based systems.
In practical terms, ontology is the set of terms of a vocabulary about a given domain and all the relationships between these terms. Ontology uses grammar to employ the vocabulary terms to express something meaningful within a specified domain of interest. Ontology should be formally defined to process by machine. However, ontology is not software and it cannot run as a program, but it can be used by programs.

3. Ontology Library System: An Ontology library system is a library system that offers various functions for managing, adapting and standardizing groups of ontologies. Ontology library systems are an important tool in grouping and re-organizing ontologies for further re-use integration, maintenance, mapping and versioning. An ontology library system will, at the very least, feature a functional infrastructure to store and maintain ontologies, an uncomplicated adapting environment for editing, searching and reasoning ontologies and strong standardization support by providing upper-level ontologies and standard ontology representation languages.
            Typical information representation systems can be categorized into three general categories:
a) Term Lists: Term lists emphasize lists of terms usually presented with definitions. It includes Controlled Vocabulary, Authority Files, Glossaries, Dictionaries, Gazetteers, etc.
b) Classifications and Categories: Classifications and categories emphasize the creation of subject sets. It includes Subject Headings, Classification Schemes, Taxonomies, Categorization Schemes, etc.
c) Relationship Lists: Relationship lists emphasize on the connection between terms and concepts. It includes Thesauri, Semantic Networks, Ontologies, etc.
            Ontology library system can possess following characteristics:
a) Management: This function is the most important function of an ontology library system which facilitates the re-use of knowledge (ontologies).
b) Adaptation: Ontology library systems should facilitate the task of extending and updating ontologies. They should provide user-friendly environments for searching, editing and reasoning ontologies. Important aspects in an ontology library system include support in finding and modifying existing ontologies.
c) Standardization: Ontology library systems should follow existing or available standards, such as standardized ontology representation languages and standardized taxonomies or structures of ontologies.

4. Examples of Ontological Library System: In the following, a few examples of Ontolocial library systems are given
a) IEEE Standard Upper Ontology (IEEE): IEEE Standard Upper Ontology (IEEE)  is developed by IEEE Standard Upper Ontology (SUO) Working Group, who took a tremendous effort to create a standard top-level ontology to enable various applications, such as data interoperability, information search and retrieval, automated inferencing and natural language processing.
b) DAML Ontology Library System:  DAML Ontology library system is the part of DARPA Agent Markup Language (DAML) Program, which officially started in August 2000. The goal of the DAML effort is to develop a language and tools to facilitate the concept of the Semantic Web.

5. Application of Ontology: The fields of artificial intelligence, the Semantic Web, systems engineering, software engineering, biomedical informatics, library science, enterprise bookmarking, and information architecture all create ontologies to limit complexity and to organize information. Ontologies are used for representing knowledge on the whole of a specific domain or on of it. Some applications of ontologies are
a) Information Exchange: Lack of standardization and common vocabulary over the web has continued to generate heterogeneity, which strongly hinders information exchange and communication. Ontology will help people to find relevant information more efficiently and more effectively, give better access to that information, and aid the sharing of knowledge within the user community of a digital library.
b) Used in Software to Retrieve Relevant Information: Ontologies are included in software architectures as a way of facilitating the search for relevant information.
c) Model a domain: Ontologies can be used to model a domain and support reasoning about concepts.

6. Conclusion: Ontology is a set of classes, relations, functions, etc. that represents knowledge of a particular domain. Ontologies provide a formal frame to represent the knowledge related with a complex domain, as a qualitative model of the system. Ontology describes concepts, terms and relations in a specific domain to create communication richness and provides a clear description to these concepts which are related to the domain knowledge. Ontologies can be used to represent the structure of a domain by means of defining concepts and properties that relate them.



How to Cite this Article?
APA Citation, 7th Ed.:  Barman, B. (2020). A comprehensive book on Library and Information Science. New Publications.
Chicago 16th Ed.:  Barman, Badan. A Comprehensive Book on Library and Information Science. Guwahati: New Publications, 2020.
MLA Citation 8th Ed:  Barman, Badan. A Comprehensive Book on Library and Information Science. New Publications, 2020.

Badan BarmanBadan Barman at present working as an Assistant Professor in the Department of Library and Information Science, Gauhati University, Guwahati-781014, Assam, India. He is the creator of the LIS Links (http://www.lislinks.com) - India’s most popular social networking website for Library and Information Science professionals. He also created the UGC NET Guide (http://www.netugc.com) and LIS Study (http://www.lisstudy.com) website.

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