A graph database stores information as nodes and relationships — the same building blocks you learn about in Network Literacy. The technology behind this competition is itself a network.
In the Network Literacy framework, you learn that networks have nodes (things) and edges (connections between things). A graph database works exactly the same way. In Neo4j — the graph database this competition uses — data has three building blocks:
The things. An entry, a school, a concept, a network topic. Each node has a label that tells you what kind of thing it is.
The connections. "Submitted from," "demonstrates," "in domain." Each relationship has a type and a direction.
The details. A school's name and location. An entry's description and grade. Properties are the data attached to nodes and relationships.
This maps directly to Concept 2 of Network Literacy: networks have parts. The graph database simply makes those parts explicit and queryable.
When you submit your entry to the NetSciEd Challenge, it becomes a node in our graph database hosted on Neo4j AuraDB. Here's what happens:
(:Entry) node with your title, description, and answers.
(:School) node with its name, URL, and location on the map.
(:Concept) nodes, and your entry connects to them.
The Live Graph page lets you see this structure directly. You can explore entries by concept, by domain, by school, or browse the entire network of networks.
A spreadsheet stores data in rows and columns. It can tell you that Entry #47 is from Lincoln High School. But it cannot easily show you that Lincoln High School submitted three entries across two domains, both of which share structural properties with entries from a school in Brazil.
A graph database makes these connections first-class citizens — they are as real and as queryable as the data itself. When your data is fundamentally about relationships, a graph database is the natural tool.
And that's the point: the NetSciEd Challenge is fundamentally about relationships. Between nodes and edges. Between students and networks. Between schools and concepts. The graph database doesn't just store the competition data — it embodies the Network Literacy framework.
Here's what a query looks like in Cypher, Neo4j's query language. This finds all entries that demonstrate Concept 2 (Nodes & Edges) and were submitted by schools in the same country:
Notice how the query reads almost like English: "Find entries that demonstrate the 'Nodes and Edges' concept, and the schools they were submitted from." The pattern-matching syntax mirrors the way you think about networks.
Explore the live graph of competition entries, or submit your own and become part of the network.