Knowledge Graphs provide a neat and easy way to segment your data, called ‘Named Graphs‘. This post shows how you access them, and different uses they may be put to.
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OWL2 Snippets for VSCode
I put together a list of OWL2 snippets for Visual Studio Code, for use with Turtle (*.ttl) files.
https://github.com/aabs/owl-2-turtle-snippets
The shortcuts cover most of the OWL2 Reference Card. Enjoy.
Continue readingKnowledge Graphs 6 – Semantics
With this installment we finally get to the part of knowledge graphs that I personally find really exciting: Semantics. In this installment, I will introduce some of the simple rules of entailment that are a part of the RDFS standard.
Continue readingKnowledge Graphs 5 – Modelling with RDFS
This installment moves beyond the simple graph model of RDF to introduce the modelling support of RDF Schema. I will go on to show you how using the W3C Standard RDFS imbues your data with another layer of meaning, and makes it easier for you to enrich your raw data with meaning over time.
Continue readingKnowledge Graphs 4 – Querying your knowledge graph using .NET
This installment leaves the CLI behind to show how we consume a knowledge graph within our programmatic environments. The framework I use to work with RDF is dotNetRdf.
Continue readingKnowledge Graphs 3 – Using a Triple Store
Last time I showed you how to use CLI tools to build out your RDF data to more depth using Turtle files and how to query it using the Apache Jena CLI toolchain using SPARQL Query language. This time I’ll show how to insert and retrieve data from a remote triple store. I’ll continue using the CLI tools for now.
Continue readingKnowledge Graphs 2 – Playing on the CLI
Last time I showed how to write RDF in Turtle, and how to make very simple queries in SPARQL. What I didn’t show was how to get your hands dirty. Specifically, I want to show you how to try things out on the cheap command line. I will show examples of how to build out your RDF data to more depth using Turtle files, and how to use the Jena framework to create queries against that data, so you can work out ahead of time how to navigate your graph of data.
