This chapter explores the critical concepts of findability and discoverability in data management, underscoring the necessity of structured approaches like the ontology pipeline. It addresses the challenges of defining entities within data contexts and the critical role of accurate controlled vocabularies for building knowledge graphs. Additionally, the discussion highlights the importance of balancing human insight with automated systems in data modeling to maintain clarity and integrity.