Towards Data Science is a community-powered publication that showcases work in data science, machine learning and artificial intelligence. Every day newcomers, seasoned researchers and industry practitioners publish tutorials, research notes and real-world case studies that help the field move forward.

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Knowledge graphs organize information through three layers: ontologies that define relationships between concepts, controlled vocabularies that catalog real-world entities, and observational data that provides evidence. Healthcare pioneered this approach through decades of standardization, enabling capabilities like drug discovery, clinical decision support, and regulatory compliance. The structured knowledge foundation allows reasoning over facts, retrieval across fragmented systems, and repurposing of existing assets. While healthcare leads in maturity due to regulatory pressure and collaborative standards, other industries including finance, cybersecurity, and policy are adopting similar approaches to build AI-ready systems grounded in explicit domain knowledge rather than relying solely on model capabilities.

What Is a Knowledge Graph — and Why It Matters