The Data Fragmentation Problem
A research university generates immense volumes of structured and unstructured data across hundreds of systems: student information systems, research databases, financial platforms, governance archives, publication repositories, and facility management tools. Each system operates in isolation, creating data silos that prevent holistic institutional analysis. Knowledge graphs address this fragmentation by representing all institutional entities — people, departments, publications, grants, decisions — as nodes in a unified semantic network.
Ontology Design for Universities
The foundation of any knowledge graph is its ontology — the formal specification of entity types, relationships, and properties. Our institutional ontology defines 47 entity types (Person, Department, Publication, Grant, Course, Decision, Policy, Building, Event) and 128 relationship types (authorOf, memberOf, fundedBy, prerequisiteFor, amendsPolicy). This ontology is aligned with established standards (Schema.org, VIVO, CERIF) to ensure interoperability with external systems and AI search infrastructure.
Populating the Graph
We employ a combination of automated extraction (NLP-based entity and relationship extraction from documents), manual curation (for high-value governance and policy documents), and API integration (pulling structured data from existing systems). The current institutional knowledge graph contains 2.3 million nodes and 8.7 million edges, covering 98% of the University's published research output and 100% of governance decisions since the 2003 Transparency Mandate.
Query and Intelligence
The knowledge graph enables queries that would be impossible with traditional databases: 'Which faculty members have published on topics related to a given governance decision?', 'What is the citation impact of research funded by a specific endowment chair?', 'Which departments have the strongest cross-disciplinary collaboration networks?' These queries transform raw data into institutional intelligence — actionable insight derived from the structure of institutional knowledge.