Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

Enterprise knowledge graphs, however, include the metadata and semantic benefits of MDM hubs but link all data together in adherence to semantic standards.

This means big changes for enterprise data and employees. ... The knowledge graph keeps data, analysis, and everything people need to find, understand, and use data quickly together at all times.

But the big data challenge of variety has mostly been ignored until recently. Perhaps knowledge graphs biggest contribution is to solve the variety problem by providing a consistent view across ...

When Google launched Knowledge Graph in 2012, they hailed it as a breakthrough. Instantly get information that’s relevant to your query. This is a critical first step towards building the next ...

The extraordinary growth in complex data has left many enterprises struggling to create an integrated, comprehensive view of that data. In recent years, knowledge graphs have emerged as a powerful ...

So, calling knowledge encoded on top of a graph structure a "knowledge graph" sounds natural. And the people doing this, the data modelers, have been called knowledge engineers, or ontologists.

Data.world, a vendor offering a knowledge graph powered, cloud-native enterprise data catalog solution, has announced it has closed a $26 million round of venture capital funding led by Tech ...

Once those descriptions are defined according to W3C’s Resource Description Framework (RDF) standards, the semantic graph database can do wonderful things via SPARQL, the query language used by ...

Google’s Knowledge Graph is going to massively increase the number of direct answers shown, which will almost certainly renew concerns. Singhal’s response is that publishers shouldn’t worry.