Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

Graph technology is allowing pharma to model data in a way that offers invaluable insights for marketing, R&D and compliance teams alike.

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

From eBay and NASA to investigative journalists and independent data scientists, graph analytics power real-world use cases and make a difference every day in areas of recommendations and fraud ...

Enterprises that want to use powerful graph algorithms to discover relationships hidden in their data now have an easier path to get there thanks to the new data science library unveiled today by ...

Graph data science is an emerging field with a lot of promise, but it’s being hamstrung by the need for practitioners to have lots of data engineering and ETL skills. Now Neo4j is hoping to drive that ...

And there have been over 28,000 peer-reviewed scientific publications about graph data science in recent years.

Today, much of data science is founded on precisely these high-dimensional spaces. They’re dizzying to contemplate, but the fundamental principles are the same as those of their nineteenth ...

A semantic database is a set of interconnected resources, where each node (the starting and ending point of an arrow) is some kind of resource and each edge is a relationship.The graphs created by ...

Drawing and interpreting graphs and charts is a skill used in many subjects. Learn how to do this in science with BBC Bitesize. For students between the ages of 11 and 14.