Property graphs offer developers a different way to structure their graph model. There are also other, de facto industry standards for graphs. The seminal article on this topic was published in Scientific American in 2001. The World Wide Web Consortium (W3C) has created a set of technical specifications for representing graphs, querying them, and for building graph schemas: the specifications for the Resource Description Framework (RDF) graphs, the SPARQL query language, and the Web Ontology Language (OWL) collectively make up what is known as the Semantic Web, a vision of how knowledge could be structured and managed in a distributed fashion work on the Semantic Web in the early 2000s laid the groundwork for modern knowledge graphs. There are different graph technologies that you may consider.
Graph databases make it easier to model and manage highly connected data, treat relationships as “first class citizens,” have flexible schemas, and provide higher performance for graph traversal queries. Graph databases are purpose-built to store and navigate relationships. The most effective way to build and store a knowledge graph is to use a graph model and a graph database. Logic built into such a model allows us to reason about a graph and information contained within, and to make implicit information in the graph explicitly accessible. This lets us model complex and complicated subject matter.Ī knowledge graph captures the semantics of a particular domain using a set of definitions of concepts, their properties, relations between them, and logical constraints that are expected to hold. Unlike traditional ways of managing data, such as relational databases, graph modeling is very flexible and allows for the real-world diversity and heterogeneity of data. This idea is not new, but has now become more viable via the introduction of scalable graph databases. Graphs are a natural way to model and represent information about the world. It “democratizes” data in an organization by allowing more people to understand and access data. Simply put, a knowledge graph is a means of structuring and organizing information for easier access and understanding. If you searched the web for the longest river in the world, browsed through a list of recommended movies to watch on a Friday, or checked your daily schedule with Alexa, chances are you were interacting with a knowledge graph.
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