Knowledge Graphs
A network of real-world entities and their interrelations, organized in a graph structure, used to improve data integration and retrieval. Crucial for enhancing data connectivity and providing deeper insights.
A network of real-world entities and their interrelations, organized in a graph structure, used to improve data integration and retrieval. Crucial for enhancing data connectivity and providing deeper insights.
Data that provides information about other data, such as its content, format, and structure. Essential for organizing, managing, and retrieving digital assets and information efficiently in product design and development.
Technologies that enable machines to understand and interpret data on the web in a human-like manner, enhancing connectivity and usability of information. Essential for improving data interoperability and accessibility on the web.
A structured framework for organizing information, defining the relationships between concepts within a specific domain to enable better understanding, sharing, and reuse of knowledge. Important for creating clear and consistent data models, improving communication, and enhancing the efficiency of information retrieval and management.
A set of metadata standards used to describe digital resources, facilitating their discovery and management. Important for ensuring effective organization and retrieval of digital assets in product design and development.
Retrieval-Augmented Generation (RAG) is an AI approach that combines retrieval of relevant documents with generative models to produce accurate and contextually relevant responses. Essential for improving the accuracy and reliability of AI-generated content.
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.
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.
The series of actions or operations involved in the acquisition, interpretation, storage, and retrieval of information. Crucial for understanding how users handle information and designing systems that align with cognitive processes.
A method for organizing information based on five categories: category, time, location, alphabet, and continuum. Useful for creating clear and effective information architectures.
The process by which search engines systematically browse the internet to index and retrieve information from websites. Essential for understanding how search engines discover and index web content.
3-Tiered Architecture is a software design pattern that separates an application into three layers: presentation, logic, and data. Crucial for improving scalability, maintainability, and flexibility in software development.
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.
Location, Alphabet, Time, Category, and Hierarchy (LATCH) is a framework for categorizing information. Useful for creating clear and intuitive information structures in digital products.
The practice and science of classification, often used to organize content and information. Essential for improving findability and usability in information systems.
A search system that allows users to narrow down search results by applying multiple filters based on different attributes or categories. Essential for improving user search experience and efficiency.