Relational Knowledge Graph System (RKGS)
Relational Knowledge Graph System (RKGS) is an interesting idea that combines the relational paradigm and the knowledge graph paradigm. This documentation, Why RKGS, explains the idea.
This gets even more interesting with the notion of "relational AI". RelationalAI is described as follows by the company of the same name, Relational.ai: “RelationalAI is a cloud-based relational knowledge graph management system, with state of the art probabilistic processing and declarative reasoning at scale to make developing Data Applications a superpower for your business.”
This notion of knowledge graphs represented in relational databases fits into my belief that knowledge graphs have two aspects: the expression SYNTAX and the logic of what is expressed or SEMANTICS. While the LOGIC of a knowledge graph is always the same regardless of technical syntax used to express that logic; there are many, many different technical syntaxes that can be used to represent a knowledge graph.
There seems to be different groups trying to hijack the term "knowledge graph". The semantic web people say that only RDF+OWL+SHACL can be used to represent knowledge graphs. The graph database camp says that only graph databases are knowledge graphs. The XBRL camp tends to not even realize that XBRL is a means to represent a knowledge graph and they have a branding problem in that people think that XBRL is only for financial reports (which is not true).
Additional Information:
- Relational Knowledge Graphs
- Introduction to the Relational Knowledge Graph System (this discusses the notion of accidental complexity)
- Graph Normal Form
- Sixth Normal Form
- REL language
- Tutorial D (appears to be the basis for REL)
- TerminusDB
- RDFox
Comments
Post a Comment