Standard

This document maps and describes the differences between GDF (ISO 20524 series), from ISO/TC 204, and conceptual models from the ISO 19100 family, from ISO/TC 211, and suggests ways to harmonize and resolve issues of conflict. Throughout this document, reference to GDF refers to GDF v5.1, ISO 20524-1 and ISO 20524-2, unless expressly identified otherwise. Where necessary, reference will be made to Part 1 or Part 2.

ISO/TS 19129:2009 defines the framework for imagery, gridded and coverage data. This framework defines a content model for the content type imagery and for other specific content types that can be represented as coverage data. These content models are represented as a set of generic UML patterns for application schemas.

This document is the first of a family of standards. This document defines XML based encoding rules for conceptual schemas specifying types that describe geographic resources. The encoding rules support the UML profile as used in the UML models commonly used in the standards developed by ISO/TC 211. The encoding rules use XML schema for the output data structure schema. The encoding rules described in this document are not applicable for encoding UML application schema for geographic features (see ISO 19136 for those rules).

This document is the first of a family of standards. ISO/TS 19150-1:2012 defines the framework for semantic interoperability of geographic information. This framework defines a high level model of the components required to handle semantics in the ISO geographic information standards with the use of ontologies.

This standard defines a methodology for creating possible Metaverse systems. A description of the techno-socio aspects of Metaverse systems is provided, together with a high level ethical assessment methodology for the design and operation of Metaverse systems.

ISO 37100:2016 defines terms relating to sustainable development in communities, smart community infrastructure and related subjects.

As accelerating improvements in city services and quality of life is fundamental to the definition of a smart city ISO 37120 is intended to provide a complete set of indicators to measure progress towards a smart city.

Avatar Representation and Animation (ARA) is a Technical Specification being developed to provide data format specifications enabling a party to represent and animate an avatar transmitted by another independent party. The goal is represented by the following use case: Avatar-Based Videoconference: avatars representing humans with a high degree of accuracy participate in a videoconference. A virtual secretary (VS) represented as an avatar displaying PS creates an online summary of the meeting with a quality enhanced by the VS’s ability to understand the PS of the avatar it converses with.

This document is the first of a planned series of technical documents designed to facilitate interoperability between Metaverse Instances.

Technical Report - MPAI Metaverse Model - Functionality Profiles is the second of a planned series of technical metaverse interoperability technical documents.

This document provides guidance for members of the governing body of an organization to enable and govern the use of Artificial Intelligence (AI), in order to ensure its effective, efficient and acceptable use within the organization. This document also provides guidance to a wider community, including: executive managers; external businesses or technical specialists, such as legal or accounting specialists, retail or industrial associations, or professional bodies; public authorities and policymakers; internal and external service providers (including consultants); assessors and auditors. This document is applicable to the governance of current and future uses of AI as well as the implications of such use for the organization itself. This document is applicable to any organization, including public and private companies, government entities and not-for-profit organizations. This document is applicable to an organization of any size irrespective of their dependence on data or information technologies.

This document defines a reference architecture of Knowledge Engineering (KE) in Artificial Intelligence (AI). The reference architecture describes KE roles, activities, constructional layers, components and their relationships among themselves and other systems from systemic user and functional views. This document also provides a common KE vocabulary by defining KE terms.