Training Data Markup Language for Artificial Intelligence


The Training Data Markup Language for Artificial Intelligence (TrainingDML-AI) Standard aims to develop the UML model and encodings for geospatial machine learning training data. Training data plays a fundamental role in Earth Observation (EO) Artificial Intelligence Machine Learning (AI/ML), especially Deep Learning (DL). It is used to train, validate, and test AI/ML models. This Standard defines a UML model and encodings consistent with the OGC Standards baseline to exchange and retrieve the training data in the Web environment.

The TrainingDML-AI Standard provides detailed metadata for formalizing the information model of training data. This includes but is not limited to the following aspects:

  • How the training data is prepared, such as provenance or quality;
  • How to specify different metadata used for different ML tasks such as scene/object/pixel levels;
  • How to differentiate the high-level training data information model and extended information models specific to various ML applications; and
  • How to introduce external classification schemes and flexible means for representing ground truth labeling.


(Hover over Type for full description)
Document title Version OGC Doc No. Type
OGC Training Data Markup Language for Artificial Intelligence (TrainingDML-AI) Part 1: Conceptual Model Standard 1.0 23-008r3 IS

Related links

No Results Found.

Go To OGC Press Page

Sign up today

Receive the latest news on OGC.

© 2024 Open Geospatial Consortium. All Rights Reserved.

Become a memberBecome a member