Knowledge Graphs and Supply Chains
https://www.linkedin.com/pulse/knowledge-graphs-supply-chains-kurt-cagle-hvhzc/
Defining Knowledge Grap hs
This is a very good question, and actually lets me lead in to a topic I’ve addressed before, but maybe with a different twist this time:
What is a knowledge graph, and how does it differ from a standard ontology?
Let me address the latter part first, because I think it clarifies the former. A knowledge graph is a form of ontology. Like all ontologies, it generally consists of at least three, and perhaps four parts:
- A schema. This identifies the shapes and properties that are of significance to the knowledge graph. You can have an ontology with a minimal schema (essentially RDFS) but the richer the schema, the more powerful the ontology.
- A taxonomy. These are the classes that identify categorization or type information, and are used typically to identify variants that don’t necessarily have structural distinctions in the model. For instance, in an address, an AddressType is part of the taxonomy, and this generally indicates the role or purpose of the address without explicitly requiring subclassing to add new properties.
- Entity (Event) Data.Entities are things that have existence, meaning that they generally have both a physical locus and a temporal one. Entities are created, fulfill their purpose, and then cease to exist.
- Data Structures.These are underlying abstractions that identify interfaces (schema) but don’t in general have instances, and most frequently these involve blank nodes as their intercessors. Ordered and unordered sets, linked lists, bags, etc., all fall into his category.
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