Event Recap – Mapping connections, uncovering complexity: real-world applications of knowledge graphs

Guest post by Jonas Norén*

Imagine trying to understand a complex topic by looking at thousands of scattered puzzle pieces. Now imagine having a map that shows you exactly how each piece connects to every other piece. That’s essentially what a knowledge graph does—it creates a visual web of relationships that helps us make sense of complex information.

At their core, knowledge graphs are structured databases that represent information as networks of interconnected entities and their relationships. Think of them as digital relationship maps that capture not just facts, but the connections between those facts. They’re built using nodes (entities like people, places, concepts) and edges (their relationships), creating rich, interconnected representations of knowledge that mirror how we naturally think about the world—in terms of relationships and connections rather than isolated facts. These powerful tools have become increasingly essential across many sectors, excelling at revealing complex relationships and networks that would otherwise remain hidden in traditional data formats.

On August 26th, the Sandbox working group at the NLP-CoP, hosted by The MERL Tech Initiative, held an online session on knowledge graphs, bringing together three experts who showed how relationship mapping is transforming work across different fields.

What We Covered

Understanding the Basics 

Nicolas Dickinson kicked us off by explaining that knowledge graphs are essentially digital relationship maps—webs of connected information that reveal how entities relate to each other. From search engines to forensic investigations, these tools are already working behind the scenes in systems we use daily. Nicolas’ slides can be accessed here.

Cities as Living Networks 

Shruti Syal demonstrated how cities can be understood as complex, interconnected systems. Using KUMU, she showed how network mapping transforms abstract urban relationships into visual formats that city planners can actually use. The key insight: cities are like living organisms where resilience comes from how all the parts work together. See Shruti Syal’s presentation here.

Networks for Social Impact 

Mario Marais closed with a “Social Capitalist” perspective on building networks for change. His approach: map the system before you try to change it. By identifying key people, organizations, and their value exchanges, relationship mapping reveals the dependencies that shape any initiative’s success. Mario’s presentation is available here.

Key Takeaway

Knowledge graphs aren’t just technical tools—they’re powerful ways to understand complexity in any field. Whether you’re researching urban resilience, building social movements, or simply trying to make sense of interconnected data, these relationship maps help reveal patterns that might otherwise stay hidden.

The session reinforced that in our interconnected world, success often depends on understanding relationships, not just individual components. In case you are interested, you can watch the session recording here.

*This blog post was written by Jonas Norén using Claude as a tool to support the writing process.