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Standards Development
This document provides a specification for an extension to a Metadata Registration (MDR), as specified in ISO/IEC 11179-3 in which metadata that describes training data can be registered.
With the in-depth advancement of global AI industrialization and governance, training data has become a core production factor for AI technology iteration and industrial application, and its quality, traceability and compliance level directly determine the performance, credibility and governance effectiveness of machine learning based AI systems. At present, stakeholders including AI enterprises, data service providers, regulatory authorities and research institutions are generally faced with practical difficulties such as inconsistent descriptive calibers of training data attributes, incomplete provenance tracing of multi-level derived and non-uniform quality and bias measurement standards, and lack of standardized metadata carriers for compliance supervision, which has severely restricted the cross-organizational discoverability, trusted reuse and full-lifecycle governance of training data. Consequently, there is an urgent need to standardize training data metadata and establish a comprehensive metamodel for training data registration.
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