Concepts

Knowledge Graph

A knowledge graph is a graph in which entities in your business (e.g. Users, Companies, Wallets) are connected to other entities via relationships.

For instance, user "Alice" "works at" the company "Acme Corp". "Alice" has a "Wallet" for storing currency.

Using a knowledge graph, we're able to find the amount of currency "Acme Corp" has by traversing the graph and summing up all the wallets of all users who work at "Acme Corp".

Typically, knowledge graphs are stored as triples: (Entity A, Relationship, Entity B). Prometheux doesn't force you to conceptualise of your data in this way, allowing you to model relationships that involve multiple properties and entities.

Data Source

A data source is any structured or semistructured data that you wish to connect into a knowledge graph.

Ontology

At the core of Prometheux is an Ontology. This is the set of business rules that you write to define how the entities in your system relate to each other, and how entities are connected to your real data.

These rules are written in Vadalog.

Data Binding

Included in your Ontology is a way to tell Prometheux which data sources power the entities in your ruleset. In Vadalog, there are specific annotations for binding your rules to your data.

Reasoning

By processing the rules and data in your Ontology, Prometheux is able to deduce new facts or specific outcomes by processing your rule program. This processing is known as reasoning.

Chase Graph

When you ask Prometheux to reason over a set of rules, it performs this processing by repeatedly chasing the rules in your ruleset until its logical conclusion.

The steps it takes to get to your answer are known as a Chase Graph, which is a graph of the rules and data that contributed to the answer. This graph itself is a knowledge graph that can be explored and analysed.