DIN Standards Committee Building and Civil Engineering
Geographic information - Training data markup language for artificial intelligence - Part 1: Conceptual model
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).
Begin
2026-07-07
WI
00287179
Planned document number
DIN EN ISO 19178-1
Project number
00520274
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
