Knowledge Graph Construction with Ontologies — Part 1
Confused by terms like “Knowledge Graphs,” “Graph Databases,” “Semantic Web,” or “Ontologies”? Don’t worry, this blog post is here to help! I get the overwhelm from these tech terms. Questions like “What are these?” “When to use them?” “Why do they matter?” and “How do ontologies link to knowledge graphs?” can be puzzling. But fear not! I’ll explain in simple terms, making it accessible to all. Let’s explore ontologies and their importance. Plus, I’ll show you how Python can automatically turn flat csv files into a knowledge graph using a set ontology — it’s like adding contacts to your phone. Exciting, right? 🚀📚🔍
We’ll use Protégé, a tool, to create a special structure — imagine it as a recipe for a MovieLens (EDA in my previous blog) dataset. Then, enter Python — we’re getting smart here. We’ll give the computer simple directions, so it can make a knowledge graph from this recipe. It’s like teaching a dog a trick, but Python is the clever one.
But hold on, what’s the reason behind all this effort? Imagine having a huge jigsaw puzzle, and your aim is to piece it together for the full picture. Crafting graphs from data is a bit like that — it helps us organize a ton of information during the data ingestion process. And ontologies? They provide structure and rules, making sure the graph makes perfect sense. Picture this…
