Request Closed: March 24, 2023 12:00 am — April 23, 2023 11:59 pm

The Open Geospatial Consortium (OGC) seeks public comment on the candidate OGC Training Data Markup Language for Artificial Intelligence (TrainingDML-AI) Part 1: Conceptual Model Standard. The Standard defines the model and encodings for standardized geospatial machine learning training data. Comments are due by April 23. 2023.

Training data plays a fundamental role in Earth Observation (EO) Artificial Intelligence Machine Learning (AI/ML) applications, especially Deep Learning (DL). It is used to train, validate, and test AI/ML models. Understanding the source and applicability of training data allows for better understanding of the results of AI/ML operations.

To maximize the interoperability and re-usability of geospatial training data, the candidate TrainingDML-AI Standard defines a model and encodings consistent with the OGC Standards baseline to exchange and retrieve the training data via the Web. 

Additionally, the 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 and quality;
  • How to specify different metadata used for different ML tasks;
  • How to differentiate the high-level training data information model and extended information models specific to various ML applications;
  • How to describe the version, license, training data size;
  • How to introduce external classification schemes and flexible means for representing ground-truth labeling.

OGC Members interested in staying up to date on the progress of this standard, or contributing to its development, are encouraged to join the Training Data Markup Language for AI SWG via the OGC Portal.

The candidate OGC Training Data Markup Language for Artificial Intelligence (TrainingDML-AI) Part 1: Conceptual Model Standard (23-008r1) (.DOCX) is available for review and comment on the OGC Portal. Comments are due by April 23, 2023, and should be submitted via the method below.

To Comment: 

Comments can be submitted to a dedicated email reflector for a thirty day period ending on the “Close request date” listed above, Comments received will be consolidated and reviewed by OGC members for incorporation into the document. Please submit your comments using the following link: Click here to submit comments.
Please refer to the following template for the message body: Comments Template.

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AI/ML, Earth Observation