Artificial intelligence (AI) significantly enhances metadata management by improving accuracy, relevance and efficiency. AI, particularly through natural language processing (NLP) models, can automatically generate descriptive metadata by analyzing data content. This involves extracting key concepts, entities and relationships from both textual and multimedia data. This interesting topic came to us from Formtek in their article, “How AI Can Make Metadata More Meaningful for Data Management.”
AI can also map relationships between different data pieces, providing insights into dependencies and connections. This relationship mapping creates metadata that reflects data interconnectivity, improving data discovery.
Incorporating AI into metadata management processes streamlines data management, enhances data discoverability and boosts overall workflow efficiency.
Effective metadata makes digital content easily findable. However, findability depends on having a proper taxonomy in place. Proper indexing against a robust, standards-based taxonomy significantly increases data findability. Access Innovations is one of the few companies capable of helping clients generate taxonomies compliant with ANSI, ISO, and W3C standards.
Melody K. Smith
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