Abstract

Within the context of training data for Earth Observation (EO) Artificial Intelligence Machine Learning (AI/ML), this document defines 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 the provenance (e.g. agents who perform the labelling, labelling procedure).

Begin

2024-06-14

WI

00287151

Planned document number

DIN EN ISO 19178-1

Project number

00519782

Responsible national committee

NA 005-03-03 AA - Geographic Information (national mirror committee for CEN/TC 287 and ISO/TC 211)  

Responsible european committee

CEN/TC 287 - Geographic Information  

Responsible international committee

ISO/TC 211/WG 4 - Geospatial services  

draft standard

Geographic information - Training data markup language for artificial intelligence - Part 1: Conceptual model standard (ISO/FDIS 19178-1:2025); English version FprEN ISO 19178-1:2025
2025-05
Order from DIN Media