ISO 19178-1:2025

Current Revision
Geographic information - Training data markup language for artificial intelligence - Part 1: Conceptual model

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ISO 19178-1:2025

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

PUBLISH DATE 2025
ISO 19178-1:2025

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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