Computer Ontology

Definition of Computer Ontology

Computer Ontology refers to a formal representation of knowledge within a specific domain in computer science. It consists of a hierarchy of concepts, their relationships, and rules within that domain. The primary goal of computer ontology is to enable knowledge sharing and reusability across various applications and systems.


The phonetic pronunciation of “Computer Ontology” is:[kəmˈpyo͞otər ˌänˈtäləjē]

Key Takeaways

  1. Computer ontology provides a structured representation of concepts and their relationships in the domain of computers, enabling better understanding, organization, and retrieval of computer-related knowledge.
  2. It allows for better communication between humans and computers, as well as interoperability among different software systems, by providing a common vocabulary and agreed-upon semantics for the entities in the computer domain.
  3. Computer ontology can facilitate enhanced data analysis, reasoning, and decision-making, particularly in tasks like artificial intelligence and natural language processing, by offering an explicit, machine-readable foundation for computer-related knowledge.

Importance of Computer Ontology

Computer Ontology is important because it plays a crucial role in knowledge representation and information organization within computing systems.

By defining a structured framework of concepts, relationships, and categories, ontology helps in accurately processing, integrating, and retrieving data across diverse domains.

It significantly impacts artificial intelligence, natural language processing, and semantic web developments by enabling machines to understand, interpret and reason about complex information.

Moreover, computer ontology enhances interoperability and reusability of resources, resulting in improved collaboration between systems, researchers, and developers, and facilitating innovative applications and decision-making processes.


Computer ontology serves as a bridge in the realm of technology, enabling effective communication and sharing of information between humans and computer systems, as well as among various software systems. Its primary purpose is to efficiently represent concepts and their relationships within a specific domain using a structured vocabulary that a computer can understand.

This semantic framework plays a crucial role in areas such as artificial intelligence, knowledge management, natural language processing, and data integration, as it makes it possible to draw inferences and derive new knowledge based on the existing database. By implementing computer ontology, humans and machines can collaborate to tackle complex questions in diverse fields like science, medicine, and engineering.

The technology has paved the way for a more versatile and effective approach to data analysis and decision-making, letting experts interact seamlessly with computers to extract valuable insights from vast amounts of information. Additionally, computer ontology assists in supporting software interoperability, as it enables different applications to “converse” via a shared comprehension of both terminology and data structure.

Through fostering more refined understanding and collaboration in the digital landscape, computer ontology has become an invaluable tool for enhancing the ways humans can interact with and harness technology.

Examples of Computer Ontology

Biomedical Ontologies: The Unified Medical Language System (UMLS) is a comprehensive biomedical ontology developed by the National Library of Medicine (NLM). It integrates a variety of medical terminologies and coding systems used in healthcare, allowing for more efficient communication and understanding between healthcare professionals, researchers, and software developers. UMLS facilitates the exchange of medical information and supports tools that analyze and process medical texts for various purposes, such as decision support systems, diagnosis assistance, and electronic health records management.

Semantic Web Technologies: The Web Ontology Language (OWL) is a key technology for creating expressive, machine-readable ontologies that describe concepts, relationships, and rules on the internet. Developed by the World Wide Web Consortium (W3C), OWL enables more advanced search capabilities, content filtering, and reasoning across different sources of information online. This technology is particularly useful in domain-specific applications, such as natural resource management, financial services, and e-commerce platforms, where having a consistent and well-defined understanding of terminology and concepts is crucial for data integration and interoperability.

Enterprise Knowledge Management: Many organizations develop and use ontologies to effectively manage and utilize their internal knowledge. Siemens AG’s Corporate Technology department, for instance, developed the “Siemens Ontology,” which includes various sub-ontologies related to different domains and aspects of their business operations. This semantic model facilitates knowledge sharing, collaboration, and decision-making within the company, helping employees find and use relevant information more efficiently. Additionally, the Siemens Ontology serves as an integral part of their automated information systems, streamlining the process of information extraction, analysis, and reporting.

FAQ: Computer Ontology

What is computer ontology?

Computer ontology is a formal representation of knowledge within a specific domain or area of interest as part of computer science and artificial intelligence. It represents concepts, relationships, and rules within the domain, helping the system understand, reason and even make inferences about it.

Why is computer ontology important?

Computer ontology plays a crucial role in semantic and knowledge-based systems, enabling them to process and understand complex information, improving data integration, interoperability, and exchange across various systems. Ontologies essentially enable computers to understand domain concepts, make inferences and reason to solve problems more efficiently.

What are the key components of an ontology?

The main components of an ontology are classes, instances, relationships, and axioms. Classes represent the main concepts in the domain, instances are instances of those classes, relationships define the connections between classes or instances, and axioms represent the rules governing the ontology.

How is computer ontology different from a database schema?

A database schema is a basic structure that defines the arrangement, logical relations, and constraints of the data within a database. On the other hand, computer ontology is a more advanced and comprehensive representation of knowledge as it involves complex relationships, rules, and abstractions that describe a domain in more detail, making it possible for machines to reason and make inferences.

What are some common applications of computer ontology?

Computer ontology is widely used in various fields, including natural language processing, knowledge engineering, Web semantics, expert systems, and data integration and mining. Some common applications include semantic search engines, intelligent personal assistants, recommendation systems, and interoperability between knowledge-based systems in different domains.

Related Technology Terms

  • Semantic Web
  • Knowledge Representation
  • Ontology Engineering
  • Resource Description Framework (RDF)
  • Web Ontology Language (OWL)

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