Information Science on Property Graphs

As promised here are my thoughts on property graphs and how they are different from RDF graphs or knowledge graphs from an Information Science perspective. The concept of the knowledge graph is not new to me. I was first introduced to the subject in graduate school with the different data structuring methods that are put together like a puzzle to create a knowledge graph. These methods are otherwise known as taxonomies, thesauri, and ontologies. And one can argue that an ontology is all of these data structures put together with the end result being a knowledge graph when put to use in a RDF graph database.

So what is a property graph and how is it different from a knowledge graph? Property graphs are made up of nodes that do not differentiate between data types such as classes and categories. And it is that ability that is going to make your data structure semantic giving you the most out of your data. Property graph nodes resemble a collection of classes as they use properties throughout which resemble attributes. This kind of approach does not use the data rules discussed in SKOS and OWL and to a larger extent W3C, the organization that governs Semantic Web rules. Using Semantic Web rules means that your data will be interoperable for maximum usage, and you will be ready for Web 3.0.