Artificial intelligence (AI) can play a significant role in making metadata more meaningful for data management by enhancing its accuracy, relevance and efficiency. This interesting topic came to us from Formtek in their article, “How AI Can Make Metadata More Meaningful for Data Management.”

AI algorithms, particularly natural language processing (NLP) models, can analyze the content of data and automatically generate descriptive metadata. This includes extracting key concepts, entities and relationships from textual and multimedia data.

AI can analyze the relationships between different pieces of data, providing insights into dependencies and connections. This relationship mapping can be used to create metadata that reflects the interconnectivity of data, aiding in better data discovery.

By incorporating AI into metadata management processes, organizations can streamline data management, improve data discoverability and enhance the overall efficiency of their data-related workflows.

Metadata makes digital content findable. However, findability works only when a proper taxonomy is in place. Proper indexing against a strong standards-based taxonomy increases the findability of data. Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.