Third Iron

Artificial Intelligence

• Analyze, clean, reconcile, and enrich large-scale bibliographic and holdings datasets
• Investigate metadata quality, duplication, normalization, matching, and entity-resolution issues
• Use Excel, SQL, AI tools, and other data-analysis methods to identify patterns, exceptions, and improvement opportunities
• Design and refine metadata rules, mappings, validation processes, and automated workflows
• Evaluate bibliographic data from publishers, aggregators, libraries, and other external sources
• Support the evolution of metadata architecture, discovery capabilities, and knowledge-base systems
• Develop repeatable methods for assessing metadata completeness, accuracy, consistency, and timeliness
• Document data sources, standards, workflows, decisions, and quality-control procedures
• Use AI-assisted approaches while validating results and maintaining standards for accuracy, privacy, and responsible use
• Collaborate with technical and product teams to strengthen metadata quality, coverage, matching, and interoperability
• Improve bibliographic data accuracy, consistency, and coverage
• Develop scalable approaches to data analysis and quality control
• Turn complex bibliographic data into more reliable experiences for libraries and their users

AI-Native Metadata Librarian