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ISO 19178-1:2025

ISO 19178-1:2025 Geographic information — Training data markup language for artificial intelligence — Part 1: Conceptual model

CDN $337.00

This publication was last reviewed and confirmed in 2025.

Geographic information — Training data markup language for artificial intelligence — Part 1: Conceptual model

SKU: 988517bfdefe Category:

Description

Within the context of training data for Earth Observation (EO) Artificial Intelligence Machine Learning (AI/ML), this document specifies a conceptual model that:

     establishes a UML model with a target of maximizing the interoperability and usability of EO imagery training data;

     specifies different AI/ML tasks and labels in EO in terms of supervised learning, including scene level, object level and pixel level tasks;

     describes the permanent identifier, version, licence, training data size, measurement or imagery used for annotation;

     specifies a description of quality (e.g. training data errors, training data representativeness, quality measures) and provenance (e.g. agents who perform the labelling, labelling procedure).

Edition

1

Published Date

2026-06-18

Status

PUBLISHED

Pages

48

Language Detail Icon

English

Format Secure Icon

Secure PDF

Abstract

Within the context of training data for Earth Observation (EO) Artificial Intelligence Machine Learning (AI/ML), this document specifies a conceptual model that:

     establishes a UML model with a target of maximizing the interoperability and usability of EO imagery training data;

     specifies different AI/ML tasks and labels in EO in terms of supervised learning, including scene level, object level and pixel level tasks;

     describes the permanent identifier, version, licence, training data size, measurement or imagery used for annotation;

     specifies a description of quality (e.g. training data errors, training data representativeness, quality measures) and provenance (e.g. agents who perform the labelling, labelling procedure).

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