Big Tech Ontology Development

Designed and implemented comprehensive semantic ontology organizing ~300 content pieces across 10 primary classes, 19 specialized subcategories, and complex entity relationships. Built JSON-LD schema framework with custom templates, relationship mapping, and machine-readable structure for enhanced discoverability.

The challenge: Traditional content management systems lack semantic depth for complex topic relationships. Flat taxonomies can't capture the interconnected nature of technology companies, innovations, regulatory matters, and societal impacts.

The solution: Developed custom ontology extending Schema.org vocabulary with Big Tech-specific classes and properties. Created standardized templates for 19 content types, established explicit entity relationships, and implemented RDF-queryable structure supporting both human navigation and AI understanding.

The result: Scalable knowledge graph framework covering major tech companies (Google, Amazon, Meta, Apple, Microsoft, OpenAI, Anthropic), enabling sophisticated content discovery, competitive intelligence analysis, and semantic search optimization. Ready-to-implement system with complete technical specifications, database schemas, and API designs.

Skills demonstrated: Ontology engineering, knowledge graph design, semantic web technologies, structured data implementation, information architecture, entity relationship modeling