Abstract
This disclosure presents a framework for managing semantic evolution across biomedical data ecosystems using dependency graphs. Changes to terminologies, ontologies, information models, mappings, datasets, analytical features, and AI/ML assets are represented as typed semantic changes and propagated across their dependencies. The framework identifies affected artifacts, determines the semantic conditions that must be preserved, and selects the minimum set of transformations required to accommodate the change. Current and proposed semantic states are validated against consistent evaluation criteria to assess mapping consistency, feature compatibility, model dependencies, and traceability. When validation succeeds, the proposed state is released with supporting evidence. When validation does not meet the required conditions, the framework revises the transformation, isolates affected artifacts, retains the existing version, or restores the previous semantic state. This enables controlled, traceable, and reversible semantic evolution across interconnected biomedical data ecosystems.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Mishra, Soumendra Kumar, "SEMANTIC EVOLUTION OF BIOMEDICAL DATA ECOSYSTEMS USING DEPENDENCY GRAPHS", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/11831