Why Knowledge Graphs for Industrial Interoperability

Let’s face it, “ontology” and “knowledge graph” sound like they belong in an academic paper, not on a factory floor.

But here’s the thing: if you’re in industrial manufacturing and serious about interoperability and analytics, you need to get familiar with these concepts.

They’re reshaping how we understand, connect, and use data.

Let’s break it down in very basic terms.

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𝐎𝐧𝐭𝐨𝐥𝐨𝐠𝐲 = 𝐒𝐜𝐡𝐞𝐦𝐚

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An ontology gives you the structure of how things are related.

Think of it as a map or blueprint that defines the relationships between different concepts, like parts, systems, and processes in manufacturing.

It’s not just about what a part is. It’s about how that part connects to other parts, systems, or stages in the lifecycle.

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𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐆𝐫𝐚𝐩𝐡 = 𝐃𝐚𝐭𝐚

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A knowledge graph, on the other hand, is what happens when you populate that ontology with real data.

It's a living network of connections that reflects how things are actually functioning in your organization.

Why Does This Matter in Manufacturing?
Let’s use a practical example.

Say you deal with parts that go into building a truck:

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✅ From a logistics point of view, a part is a shipping unit.
✅ From a production point of view, it's a step in the assembly line.
✅ From a design perspective, it’s a 3D model.
✅ From an electronics standpoint, it could contain embedded systems.

Each department sees the same part differently. The context changes everything.

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