Knowledge Graphs 7 - Named Graphs

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. This is part 7 of an ongoing series providing a little background on Knowledge Graphs. The aim is to let software developers get up to speed as fast as possible. No theory, no digressions, and no history. Just practical knowledge.
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Knowledge 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. This is part 5 of an ongoing series providing a little background on ‘knowledge graphs‘. The aim is to let software developers get up to speed as fast as possible.
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Knowledge 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. This is part 6 of an ongoing series providing a little background on ‘knowledge graphs‘. The aim is to let software developers get up to speed as fast as possible. No theory, no digressions, and no history.
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Knowledge 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. This is part 4 of an ongoing series providing a little background on ‘knowledge graphs’. The aim is to let software developers get up to speed as fast as possible. No theory, no digressions, and no history, just practical knowledge. Knowledge Graphs 101 Knowledge Graphs 2 – Playing on the CLI Knowledge Graphs 3 – Using a Triple Store Knowledge Graphs 4 – Querying your knowledge graph using .
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Knowledge 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. Knowledge Graphs 101 Knowledge Graphs 2 – Playing on the CLI Knowledge Graphs 3 – Using a Triple Store Knowledge Graphs 4 – Querying your knowledge graph using .
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Knowledge 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.
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Knowledge Graphs 101

This is the first in a short series introducing Knowledge Graphs. It covers just the basics, showing how to write, store, query and work with graph data using RDF (short for Resource Description Format). I will keep it free of theory and interesting but unnecessary digressions. Let me know in the comments if you find it useful, and also tell me what other Knowledge Graph topics you would like to know more about.
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