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Levels

The following criteria for each level are abbreviated: each item is shorthand for:

  • documented process
  • trained participants
  • implemented process and/or technology
  • monitoring and improvement

Maturity Level 1

  • Minimal ontologies which could be as simple as a list of classes and properties used in graphs
  • Basic metadata (definition, label) for each class and property
  • Each individual (in data) has at least one explicit class
  • Ontology coverage for each use case in scope of the project; project includes minimal number of ontologies and classes not justified by a use case
  • Definitions catalogued and under change management

Maturity Level 2

  • Ontologies expressed in a standard ontology language (could be as simple as RDF Schema)
  • Common (shared or mapped) concepts across EKG projects
  • Ability to see ontology usage by use cases, vocabularies and datasets
  • Namespace scheme established and used for new ontologies in the EKG
  • Ontology guidelines in place and implemented, including common metadata
  • Documented approach for external ontologies, including selection and adaptation
  • Annotated example files for documentation and training
  • Test files based on use cases covering all used ontology elements
  • Ontology change management includes impact analysis and stakeholder approval
  • Tooling for ontology diagrams and documentation
  • Automated basic checking of ontology syntax
  • Access to at least one trained Ontologist

Maturity Level 3

  • Modeling of required data and constraints by use case, including for stored and communicated data
  • Automated validation of ontologies (for guideline compliance, and for logical consistency), with results as triples
  • Automated testing and validation of test data with ontologies (per use case)
  • Separation of concerns to support enterprise management such as bi-temporality, transactions and events
  • Automated transformation of ontologies to use common serialization and metadata
  • Automated checking of ontologies against different profiles (e.g. OWL-RL) to check for technology support
  • Automated checking of ontologies against different best practices
  • Ontology source changes linked to automated operations for testing and deployment
  • Impact analysis identifies ontology breaking changes which require fixes to existing EKG data
  • EKG-wide ontology browsing and searching
  • Follow-your-nose UI starting from any ontology element URI1
  • Follow-your-nose API starting from any ontology element URI1
  • Trained ontologist available to each project (ideally via the EKG Center of Excellence)

Maturity Level 4

  • Separation of ontologies from vocabularies, with multiple vocabularies for different communities mapped to the same concepts
  • Ontology architecture management process, including use of patterns and modularity
  • Generation of logic into business language
  • Automated fixes to existing EKG data in response to ontology breaking changes
  • Basic ontology metrics and reporting, including usage in data
  • Generation of ontologies/shapes for external interchange

Maturity Level 5

  • Sophisticated ontology metrics and reporting, including trends
  • Matching and differencing of ontologies from different sources
  • Automated matching of ontologies with vocabularies
  • Generation of validation code for external interchange
  • Wizard for developing ontologies from business questions
  • Inducing of ontologies from instance data

  1. see also "predicate" ↩↩