Standard

This document is the first of a family of standards. This document provides an overview of ISO 10303. ISO 10303 provides a representation of product information along with the necessary mechanisms and definitions to enable product data to be exchanged. The exchange is among different computer systems and environments associated with the complete product lifecycle, including product design, manufacture, use, maintenance, and final disposition of the product. This document defines the basic principles of product information representation and exchange used in ISO 10303. It specifies the characteristics of the various series of parts of ISO 10303 and the relationships among them. The following are within the scope of this document:(1) scope statement for ISO 10303 as a whole;(2) overview of ISO 10303;(3) architectures of ISO 10303;(4) structure of ISO 10303;(5) terms and definitions used throughout ISO 10303;(6) overview of data specification methods used in ISO 10303; NOTE: This includes the EXPRESS data specification language and graphical presentation of product information models.(7) introduction to the series of parts of ISO 10303: (a) integrated resources; (b) application interpreted constructs; (c) application modules; (d) business object models; (e) application protocols; (f) implementation methods; (g) usage guides; (h) conformance testing methodology and framework; (i) abstract test suites; (j) scheme for identification of schemas and other information objects defined within parts of ISO 10303.

This document defines a set of metadata to support the audit trail of the transformation of a geometry definition, while it is distributed and shared in supply-chains, to ensure the traceability of geometric model data. It also defines a set of web services based on the utilisation of these metadata. The following are within the scope of this document:(1) metadata definitions for geometry transformation audit trail:(2) syntax for storing these metadata in geometry data sets in various formats;(3) conformance level for implementers and business processes; and(4) definitions of web services to query the geometric model data set and its associated metadata.The following are outside the scope of this document:(1) service specifications for CAD operations;(2) specifications of a cybersecurity infrastructure to enable web services;(3) the technical implementation of a STEP geometry services client or server;(4) any geometric model definition;(5) any product and manufacturing information (PMI) definition; and(6) archiving.

This document establishes terminology for AI and describes concepts in the field of AI. This document can be used in the development of other standards and in support of communications among diverse, interested parties or stakeholders. This document is applicable to all types of organizations (e.g. commercial enterprises, government agencies, not-for-profit organizations).

The standard establishes requirements for blockchain based digital identity systems. The standard addresses the following attributes of the system, including but not limited to, digital identity definition, distributed digital identity creation, distributed digital identity authentication, distributed digital identity note (refers to identity credentials such as identity card, work card, member card), data or asset circulation protocols.

This standard defines a model for ethical considerations and practices in the design, creation and use of empathic technology, incorporating systems that have the capacity to identify, quantify, respond to, or simulate affective states, such as emotions and cognitive states. This includes coverage of 'affective computing', 'emotion Artificial Intelligence' and related fields.

The standard identifies/addresses the manner in which personal privacy terms are proffered and how they can be read and agreed to by machines.

This document is the first of a family of standards. It specifies a set of functions for computer graphics programming, the graphical kernel system. Provides functions for two dimensional graphical output, the storage and dynamic modification of pictures, and operator input. Applicable to a wide range of applications that produce two dimensional pictures on vector or raster graphical devices in monochrome or colour.

A set of processes by which organizations can include consideration of ethical values throughout the stages of concept exploration and development is established by this standard. Management and engineering in transparent communication with selected stakeholders for ethical values elicitation and prioritization is supported by this standard, involving traceability of ethical values through an operational concept, value propositions, and value dispositions in the system design. Processes that provide for traceability of ethical values in the concept of operations, ethical requirements, and ethical risk-based design are described in the standard. All sizes and types of organizations using their own life cycle models are relevant to this standard.

The impact of artificial intelligence or autonomous and intelligent systems (A/IS) on humans is measured by this standard. The positive outcome of A/IS on human well-being is the overall intent of this standard. Scientifically valid well-being indices currently in use and based on a stakeholder engagement process ground this standard. Product development guidance, identification of areas for improvement, risk management, performance assessment, and the identification of intended and unintended users, uses and impacts on human well-being of A/IS are the intents of this standard.

Guidance to developers of IEEE 1232 - conformant applications is provided in this guide. A simple doorbell is used as an example system under test to illustrate how the static model constructs of Artificial Intelligence Exchange and Service Tie to All Test Environments (AI-ESTATE) are used to form a diagnostic reasoner knowledge base. Each of AI-ESTATE's knowledge base types is discussed in conceptual terms, and how those concepts are represented in exchange files is shown. Also, some of the nuanced aspects of diagnostic knowledge bases in AI-ESTATE are clarified. An example reasoner session is provided to illustrate the use of AI-ESTATE services.

A framework of knowledge graphs is proposed in this standard. The knowledge graph conceptual model, construction and integration process of knowledge graphs, main activities in the processes, and stakeholders of knowledge graphs are described in detail. This standard can be applied in various organizations that plan, design, develop, implement, and apply knowledge and in organizations that develop support technologies, tools, and services to knowledge graphs.

Artificial intelligence (AI) computing differs from generic computing in terms of device formation, operators, and usage. AI server systems, including AI server, cluster, and high-performance computing (HPC) infrastructures are designed specifically for this purpose. The performance of these infrastructures is important to users not only on generic models but also on the ones for specific domains. Formal methods for the performance benchmarking for AI server systems are provided in this standard, including approaches for test, metrics, and measure. In addition, the technical requirements for benchmarking tools are discussed.