Difference between knowledge graphs and ontologies

Question

What is the difference between a knowledge graph and an ontology? And which of them is dependent on the other?

I understand that :

1. both are represented with nodes and edges, indicating entities and the relationships between these entities.

2. knowledge graphs are more specific and are used for a certain application, while ontology is more general.

3. an ontology is referred to when building a knowledge graph to check for the consistency of this knowledge graph.

Am I correct?

Answer 1

Putting concepts in simple words I can say:

• Knowledge graphs: Are a combination between a graph database (usually triplestore based) and a ontology or a taxonomy.
• Taxonomy: It is just a tree of categories where the data can belong to. For instance, root:Human, branches:Men,Women -> George belongs to subcategory Men, and as a consequence it belongs to category Human.
• Ontologies: Are advanced taxonomies, they add information about how the categories are related, ontologies have the structure of a graph, not just a tree. Using the latest example, in a ontology we can specify that a Man can not be a Woman at the same time. This can be powerful information for computers to "understand" the data so they can make inferences.

So, in summary: Knowledge Graph = Graph database + Ontology

Answer 2

My response would be more or less what Tico said before, with the following clarification: The ontology plays the role of the "schema" that the data should comply to, while the knowledge graph is the actual data (often the knowledge graph contains also the ontology, i.e., the schema definition).

Please read this and this post for a better overview.