What Does a Knowledge Modeler Do?

A knowledge modeler turns complex, scattered information into structured, connected knowledge that people and systems can use effectively. In practice, this means:

  • Designing and maintaining knowledge structures
    Building models that describe how concepts, processes, and data relate to each other for easy reuse across teams and systems.

  • Translating real-world processes into machine-readable formats
    Representing workflows—like how classrooms integrate AV technology or how energy flows in smart buildings—in a way that software can interpret and automate.

  • Collaborating across teams
    Working with educators, technologists, and policy advocates to ensure models reflect real needs and support decision-making.

  • Applying global standards for linked data
    • RDF (Resource Description Framework): Links data across systems (e.g., “School → hasEnergySystem → DC Microgrid”).
    • OWL (Web Ontology Language): Adds logic and rules (e.g., “Every classroom must have at least one AV device”).
    • SKOS (Simple Knowledge Organization System): Organizes concepts into clear vocabularies (e.g., “Digital Literacy → broader than → AI Curriculum”).
    • SHACL (Shapes Constraint Language): Validates data against rules (e.g., “Every school entity must include Location and Connectivity Status”).
  • Validating and improving models
    Using SHACL and other methods to ensure accuracy, consistency, and alignment with organizational goals.

  • Communicating clearly
    Explaining complex ideas in plain language so non-technical stakeholders—like school leaders or community advocates—understand the value.

Diagram: How the Standards Fit Together

What this shows:
The diagram illustrates how data flows from source systems into a knowledge graph. RDF (Resource Description Framework) provides the linking structure; OWL (Web Ontology Language) adds logic; SKOS (Simple Knowledge Organization System) organizes vocabularies; SHACL (Shapes Constraint Language) validates conformance before analytics and reporting.

Examples

Source Systems
(Classroom AV, IoT, Broadband Data, Policy Docs)

RDF Graph
(Linked Triples)

OWL Ontology
(Classes, Properties, Rules)

SKOS Vocabulary
(Broader/Narrower/Related Concepts)

SHACL Shapes
(Validation Constraints)

Reasoning & Inference
(Consistency Checks)

Trusted Knowledge Graph
(Interoperable + Governed)

Use Cases
(Dashboards, Reports, Compliance, Search)

Example RDF Triple:
School - hasEnergySystem - DC Microgrid

OWL Rule:
Every Classroom must have >= 1 AV Device

SKOS:
Digital Literacy -> broaderThan -> AI Curriculum

SHACL:
School must have Location + Connectivity Status