The primary aim of ontologies is to bring under a single roof three tiers of representations and to ensure both their autonomy and integrated usage:
- Thesauruses federate meanings across digital (observations) and business (analysis) environments
- Models deal with the integration of digital flows (environments) and symbolic representations (systems)
- Ontologies ensure the integration of enterprises’ data, information, and knowledge, enabling a long-term alignment of enterprises’ organization, systems, and business objectives
To ensure their interoperability, tiers should be organized according to linguistic capabilities: lexical, syntactic, semantic, pragmatic.
To ensure their conceptual integration, ontologies must maintain an explicit distinction between:
- Concepts: pure semantic constructs defined independently of instances or categories
- Categories: symbolic descriptions of sets of objects or phenomena: Categories can be associated with actual (descriptive, extensional) or intended (prescriptive, intensional) sets of instances
- Facts: observed objects or phenomena
- Documents: entries for documents represent the symbolic contents, with instances representing the actual (or physical) documents
As for technical integration, it is can be achieved through graphical neural networks (GNN) and Resource description framework (RDF).
FURTHER READING
- Open Ontologies: From Silos to Architectures
- The Finger & the Moon: Fiddling with Definitions
- Reflections for the Perplexed
- Knowledge ArchitectureOpen Ontologies: From Silos to Architectures
- Ontologies & Enterprise Architecture
- Conceptual Models & Abstraction Scales
- Models & Meta-models
- Open Concepts
- Open Concepts Will Make You Free
- Conceptual Thesaurus: Overview
- Conceptual Thesaurus: Typical Use Cases
EXTERNAL LINKS
- Stanford Knowledge Systems Laboratory: “What is an Ontology ?”
- John F. Sowa, “Ontology“
- Zachman Framework
- Davis, Shrobe, and Szolovits: “What is Knowledge Representation“