ISO-TR 15442:2017, also known as Information and documentation - Principles and methods for the establishment of ontologies, is a technical report published by the International Organization for Standardization (ISO). It provides guidelines for developing ontologies, which are structured representations of knowledge in a specific domain.
of Ontologies
An ontology is a formal representation of knowledge that defines concepts, relationships, and properties within a domain. It helps to establish a common understanding of terms and their meanings, facilitating communication and interoperability among different systems and applications.
Ontologies are widely used in various fields, including information science, artificial intelligence, and knowledge management. They enable reasoning, data integration, and semantic search, making it easier to process and analyze complex data.
Key Features of ISO-TR 15442:2017
ISO-TR 15442:2017 provides a comprehensive set of principles and methods for the development of ontologies. It covers various aspects, including ontology design, documentation, evaluation, and maintenance. It aims to ensure the quality, consistency, and usability of ontologies across different domains and applications.
The standard emphasizes the importance of semantic clarity, avoiding ambiguity, and aligning with existing standards and best practices. It encourages collaboration and knowledge sharing among stakeholders involved in the ontology development process.
Benefits and Applications
ISO-TR 15442:2017 offers several benefits to organizations or individuals involved in ontology development:
Improved data integration and interoperability
Enhanced knowledge sharing and reuse
Facilitated system interoperability and communication
Efficient retrieval and analysis of information
The standard has widespread applications across various domains, such as healthcare, finance, e-commerce, and scientific research. It can be used for developing domain-specific ontologies, semantic web applications, and intelligent systems that rely on accurate and consistent knowledge representation.
Nina She