- "an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse."
The study of the nature of existence, including the relationship between entities and their properties.
What is Ontology?: Introduction to the concept of ontology and its relationship to other fields such as philosophy, computer science, and cognitive science.
Types of Ontologies: Overview of the different types of ontologies such as top-level ontologies, domain ontologies, and task-specific ontologies.
Ontology Engineering: Process of designing and creating ontologies to represent knowledge in a specific domain or application.
Ontology Languages: Discussion of formal languages used for defining and representing ontologies such as OWL, RDF, and RDFS.
Ontology Tools: Introduction to various tools used in ontology development and management such as Protégé, TopBraid Composer, and OWL API.
Ontology Reasoning and Querying: Techniques for reasoning with ontologies and querying them such as forward chaining, backward chaining, and SPARQL.
Applications of Ontology: Examples of how ontologies are applied in various domains such as healthcare, finance, and e-commerce.
Ontology Evaluation: Methods for evaluating the quality and effectiveness of ontologies such as the OWL Test Cases and OAEI.
Ontology Integration: Techniques for integrating multiple ontologies, resolving conflicts and inconsistencies, and aligning ontologies based on common concepts.
Formal Ontology: This ontology focuses on providing a formalized representation of the concepts, relationships, and entities in a particular domain.
Descriptive Ontology: This ontology aims to describe the entities, attributes, and relationships in a specific domain, and make them understandable to humans.
Domain Ontology: This ontology focuses on specific domains, such as healthcare, finance, or education, and maps out the concepts, relationships, and entities within that domain.
Upper Ontology: This ontology provides a high-level framework for organizing and modeling more specific ontologies. It defines the fundamental concepts, such as time, space, and causality, which are used across different domains.
Process Ontology: This ontology captures the processes involved in a particular domain, describing the sequence of events, relationships between events, and the resources required for each step.
Social Ontology: This ontology focuses on the social entities, relationships, and norms that exist in a particular community or society.
Cognitive Ontology: This ontology models the cognitive processes and structures that human beings use to understand and reason about the world.
Foundational Ontology: This ontology provides a framework for understanding reality, at the most fundamental level, using concepts such as substance, quality, and event.
Linguistic Ontology: This ontology is concerned with the structure of language, such as semantic relationships between words, and the grammatical rules that govern their usage.
- "Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge."
- "Each uses ontological assumptions to frame explicit theories, research and applications."
- "Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages."
- "An example of economics relying on information science occurs in cases where a simulation or model is intended to enable economic decisions."
- "What ontologies in both information science and philosophy have in common is the attempt to represent entities, ideas and events, with all their interdependent properties and relations, according to a system of categories."
- "considerable work on problems of ontology engineering (e.g., Quine and Kripke in philosophy, Sowa and Guarino)"
- "debates concerning to what extent normative ontology is possible (e.g., foundationalism and coherentism in philosophy, BFO and Cyc in artificial intelligence)."
- "Applied ontology is considered a successor to prior work in philosophy, however many current efforts are more concerned with establishing controlled vocabularies of narrow domains than first principles, the existence of fixed essences or whether enduring objects may be ontologically more primary than processes."
- "Artificial intelligence has retained the most attention regarding applied ontology in subfields like natural language processing within machine translation and knowledge representation."
- "ontology editors are being used often in a range of fields like education without the intent to contribute to AI."
- "ontologies may improve problem solving within that domain."
- "represent entities, ideas and events, with all their interdependent properties and relations."
- "an ontology encompasses a representation, formal naming, and definition of the categories, properties, and relations between the concepts, data, and entities that substantiate one, many, or all domains of discourse."
- "there is considerable work on problems of ontology engineering (e.g., Quine and Kripke in philosophy, Sowa and Guarino)."
- "Every academic discipline or field creates ontologies to limit complexity and organize data into information and knowledge."
- "New ontologies may improve problem solving within that domain."
- "Translating research papers within every field is a problem made easier when experts from different countries maintain a controlled vocabulary of jargon between each of their languages."
- "the definition and ontology of economics is a primary concern in Marxist economics, but also in other subfields of economics."
- "cases where a simulation or model is intended to enable economic decisions, such as determining what capital assets are at risk and by how much (see risk management)."