EN ISO/IEC 8183:2024 PDF

Name: EN ISO/IEC 8183:2024 — Information technology - Artificial intelligence - Data life cycle framework (ISO/IEC 8183:2023)
SKU: EN ISO/IEC 8183:2024
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Information technology - Artificial intelligence - Data life cycle framework (ISO/IEC 8183:2023)

Название (английский):

EN ISO/IEC 8183:2024

Information technology - Artificial intelligence - Data life cycle framework (ISO/IEC 8183:2023)

Статус документа:: Действующий
Формат:: Электронный (PDF)
Количество страниц:: 18
Дата публикации:: 12 июня 2024 г.
Издание:: CEN/CENELEC EN 8183 edition 1 version 1
ICS:: 35.020

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Описание (английский):

This document defines the stages and identifies associated actions for data processing throughout the artificial intelligence (AI) system life cycle, including acquisition, creation, development, deployment, maintenance and decommissioning. This document does not define specific services, platforms or tools. This document is applicable to all organizations, regardless of type, size or nature, that use data in the development and use of AI systems.

Abstract

Похожие стандарты

Стандарты, упомянутые в описании

Overview

EN ISO/IEC 8183:2024 / ISO/IEC 8183:2023 defines a standardized data life cycle framework for artificial intelligence (AI) systems. Adopted by CEN as EN ISO/IEC 8183:2024, the standard maps the stages data pass through from initial idea conception to final system and data decommissioning. It is technology‑agnostic and does not mandate specific tools, services or platforms. The framework is intended to improve AI data governance, data quality, security and system utility across organizations of all sizes.

Key topics and technical requirements

Ten life cycle stages are identified and described:

Idea conception, Business requirements, Data planning, Data acquisition, Data preparation, Building a model, System deployment, System operation, Data decommissioning, System decommissioning.

Life cycle processes: actions and processes appropriate to each stage (planning, acquisition, preparation, verification/validation, maintenance, decommissioning).

Verification vs validation: distinction between internal model verification/validation and whole‑system validation during operation.

Data decommissioning vs system decommissioning: Stage 9 focuses on data-specific actions (secure deletion, archiving, repurposing) while Stage 10 covers disposal of the system regardless of data outcome.

Terminology and references: aligns with ISO/IEC 22989 (AI concepts and terminology) and references other related work (e.g., ISO/IEC 23053, ISO/IEC 5212 under preparation).

Applicability and constraints: applicable to all organizations using data in AI development and operation; highlights patent considerations and national adoption rules under CEN/CENELEC.

Practical applications

Establishing repeatable AI data governance and lifecycle management processes.

Designing compliant workflows for data planning, acquisition and preparation to reduce bias and improve data quality.

Guiding teams on model building, verification/validation and safe system deployment/operation.

Defining secure data decommissioning and archival procedures for privacy and compliance (e.g., PII handling, DPIA considerations).

Informing procurement, auditing and risk management for AI projects.

Related standards

ISO/IEC 22989 - AI concepts and terminology

ISO/IEC 23053 - data sets (referenced for dataset lifecycle details)

ISO/IEC 5212 (under preparation) - data usage life cycle

Keywords: ISO/IEC 8183, data life cycle, AI data governance, artificial intelligence data framework, data decommissioning, model verification, AI system lifecycle.

EN ISO/IEC 8183:2024 PDF

Abstract

Похожие стандарты

Overview

Key topics and technical requirements

Practical applications

Who should use this standard

Related standards

Технические детали

BS EN ISO/IEC 22989:2023

Information technology. Artificial intelligence. Artificial intelligence concepts and terminology.

BS EN ISO/IEC 23053:2023

Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML).

BS ISO/IEC 5212:2024

Information technology. Data usage. Guidance for data usage

BS EN ISO/IEC 8183:2024

Information technology. Artificial intelligence. Data life cycle framework