P1: Ontology + Data = Knowledge Graph (KG)
P2: If a KG is the sum of these two summands, it follows:
C: An ontology is a framework for a KG
As a framework, an Ontology consists of person data, classes, properties, relations and axioms.
Personal data: Tom
classes: Interim project manager
Properties: takes over the project
Relationships: Tom is the successor of Bernd
Axioms: Tom takes over the project from Bernd
KG: We ask a question and the knowledge graph makes connections to the individual elements of the Ontology. It brings them to life, so to speak.
If you compare the KG with our neural network, you can see similarities. If I ask Tom a question, he will use his neural network to answer this question and generate new ideas.
That's why Knowledge Graphs are also defined as a kind of semantic network.
Does the community agree with this approach? Please give feedback! Thanks!
Dear researcher,
Ontologies are generally referred as smaller collections of assertions that are hand-curated, usually for solving a domain-specific problem. By comparison, knowledge graphs can include literally billions of assertions, just as often domain-specific as they are cross-domain.
Using ontology as a framework we can add real-time data to create the knowledge graph. Hope this might be helpful.
Link: https://enterprise-knowledge.com/whats-the-difference-between-an-ontology-and-a-knowledge-graph/
Thanks and regards,
Anitha Velu.
I would agree with your reasoning and add that you are talking about Graph Neural Networks(GNN), which are connection models that capture the dependence of graphs via message passing between the nodes of graphs. Unlike standard neural networks, GNN retains a state that can represent information from its neighborhood with arbitrary depth.
Source: https://www.liveai.eu/knowledge-graph-and-graph-neural-networks/
" In computing, an ontology is then a concrete, formal representation — a convention—on what terms mean within the scope in which they are used (e.g., a given domain). Like all conventions, the usefulness of an ontology depends on how broadly and consistently it is adopted and how detailed it is. Knowledge graphs that use a shared ontology will be more interoperable. Given that ontologies are formal representations, they can further be used to automate entailment."
Extracted from
Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia D’amato, Gerard De Melo, Claudio Gutierrez, Sabrina Kirrane, José Emilio Labra Gayo, Roberto Navigli, Sebastian Neumaier, Axel-Cyrille Ngonga Ngomo, Axel Polleres, Sabbir M. Rashid, Anisa Rula, Lukas Schmelzeisen, Juan Sequeda, Steffen Staab, and Antoine Zimmermann. 2021. Knowledge Graphs. ACM Comput. Surv. 54, 4, Article 71 (May 2022), 37 pages. DOI:https://doi.org/10.1145/3447772
Ontology Rules can be used for reasoning in order to deduce implicity knowledge based on existing KG data.
But an ontology itself can contain data (called individuals or instances or concrete objects). So what is the difference between an ontology and an ontology-based KG? Maybe data size.
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