Simple Knowledge Organization System (SKOS) is a standard for representing knowledge organization systems such as thesauri, classification schemes, and taxonomies. Essential for enabling interoperability and sharing of structured knowledge across different systems.
The practice and science of classification, often used to organize content and information. Essential for improving findability and usability in information systems.
A structured classification of risks into categories, helping organizations identify, assess, and manage different types of risks. Important for understanding and managing risks effectively within an organization.
Ontology is a comprehensive model that includes entities, their attributes, and the complex relationships between them, while taxonomy is a hierarchical classification system that organizes entities into parent-child relationships. Essential for understanding the depth and scope of data organization, helping to choose the appropriate structure for information management and retrieval.
A tree-like model of decisions and their possible consequences, used in data mining and machine learning for both classification and regression tasks. Valuable for creating interpretable models in digital product design and user behavior analysis.
A method of categorizing information in more than one way to enhance findability and user experience. Crucial for improving navigation, search, and overall usability of complex information systems.
Knowledge Organization System (KOS) refers to a structured framework for organizing, managing, and retrieving information within a specific domain or across multiple domains. Essential for improving information findability, enhancing semantic interoperability, and supporting effective knowledge management in digital environments.