OGC Seeks Public Comment on New Standard for Training Data for AI/ML Applications

OGC TrainingDML-AI Standard defines the model and encodings for standardizing any training data used to train, validate, and test Machine Learning models that involve location or time.

24 March 2023: 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 standardizing 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 outlined here.

About OGC

The Open Geospatial Consortium (OGC) is a collective problem-solving community of more than 550 experts representing industry, government, research and academia, collaborating to make geospatial (location) information and services FAIR - Findable, Accessible, Interoperable, and Reusable.

The global OGC Community engages in a mix of activities related to location-based technologies: developing consensus-based open standards and best-practices; collaborating on problem solving in agile innovation initiatives; participating in member meetings, events, and workshops; and more.

OGC's unique standards development process moves at the pace of innovation, with constant input from technology forecasting, practical prototyping, real-world testing, and community engagement.

OGC bridges disparate sectors, domains, and technology trends, and encourages the cross-pollination of ideas between different communities of practice to improve decision-making at all levels. OGC is committed to creating an inclusive and sustainable future.

Visit ogc.org for more info on our work.