This document provides a generic digital twin maturity model, definition of assessment indicators, and guidance for a maturity assessment.
This document establishes terminology for Digital Twin (DT) and describes concepts in the field of Digital Twin, including the terms and definitions of Digital Twin, concepts of Digital Twin (e.g., Digital Twin ecosystem, lifecycle process for Digital Twin, and classifications of Digital Twin), Functional view of Digital Twin and Digital Twin stakeholders. This document can be used in the development of other standards and in support of communications among diverse, interested parties/stakeholders. This document is applicable to all types of organizations (e.g., commercial enterprises, government agencies, not-for-profit organizations).
This standard defines a digital twin maturity model for industry, including digital twin capability domains and corresponding subdomains. This standard also defines assessment methodologies, including assessment content, assessment processes, and assessment maturity levels.
Definition of DTw correspondence measure; Components of the measure such as similarity, resolution, latency, LoD (level of detail); Quantification of the measure, Relation with other DTw projects including maturity level; and Unique features of DTw including twinning.
This document specifies technical aspects related to the extraction, decoupling, trading, and benefits of data components throughout the digital twin life cycle.
Defines:- common formats,- values, and- coding for Internet of things (IoT).
This document specifies the general principles for presenting views, sections and cuts applicable to various kinds of technical drawings (e.g. mechanical, electrical, architectural, civil engineering), following the orthographic projection methods specified in ISO 5456-2. Views and sections for shipbuilding technical drawings are discussed in ISO 128-15. Views and sections for 3D models are discussed in ISO 16792. Attention has also been given in this document to the requirements of reproduction, including microcopying in accordance with ISO 6428.
This standard defines the requirements of an identity framework for metaverse. This standard provides an identity framework for use across different metaverse systems. Furthermore, the standard helps to recognize the relevance between real world and virtual world entities. The standard covers business logic, operational procedures, and authentication programs. Also, the standard defines terminologies, a basic architectural framework, and key indicators.
This standard specifies the terminology, definitions, and taxonomy for metaverse and related terms. This standard defines categories and levels of metaverse to provide clarification for metaverse users and a roadmap for metaverse developers.
This Technical Report describes general considerations to be taken for measurement of user’s Quality of Experience (QoE) on multimedia conferencing services.
This document provides a set of guidelines for identifying the context, opportunities, and processes for developing and applying AI applications. It can be used by ISO, IEC, and JTC1 Technical Committees and Sub-Committees to build on this work in developing standards for AI applications in their areas of interest. The guidelines provide a macro level view of the AI application context, the stakeholders and their roles, relationship to the life cycle of the system, and common AI application characteristics. The guidelines will reference but not duplicate or overlap other AI-related standards to build details.
This document defines a set of processes and associated terminology for describing the life cycle of AI systems. This document forms the foundation of a detailed AI system life cycle specification. It is based on ISO/IEC/IEEE 15288 and ISO/IEC/IEEE 12207 with substitutes for and additions of AI specific processes, whose foundation is based on ISO/IEC 22989 and ISO/IEC 23053. Selected sets of these processes can be applied throughout the life cycle for managing and performing the stages of an AI system's life cycle. This document provides processes that support the definition, control and improvement of the AI system life cycle processes used within an organization or a project. Organizations and projects can use these processes when developing or acquiring AI systems. When an element of an AI system is traditional software or a traditional system, the software life cycle processes in ISO/IEC/IEEE 12207 and the system life cycle processes in ISO/IEC/IEEE 15288 may be used to implement that element.