neo4j-hp-viz

This project is a demo application for network visualizations using the GRANDstack (GraphQL, React, Apollo, Neo4j Database) application. The dataset consists of characters and their interactions from the first Harry Potter book. If you want to learn more about how the dataset was created check out my blog post.

The GraphQL endpoint is using the Neo4j Graphql library. For the network visualizations, VisJS is being used. I have also added click events to network visualization to make it an interactive explorer of your graph data. Hopefully, this project will help you get started with implementing your own network visualizations with the GRANDstack.

Start the project with:

docker-compose up

Macbook M1 users

Pull arm neo4j image

docker pull neo4j/neo4j-arm64-experimental:4.2.11-arm6

Replace in docker-compose.yml

neo4j:
    image: neo4j/neo4j-arm64-experimental:4.2.11-arm64

Seed data

Run the following command

cat seed_data.cql | docker exec -i neo4j cypher-shell -u neo4j -p letmein

Or if you are on windows

Open Neo4j Browser at localhost:7474. Login using username "neo4j" and password "letmein". Execute the queries stored in the seed_data.cql

Graph schema

Graph consists of characters from the first Harry Potter book, their interactions, to which house they belong, and to which group they are loyal.

UI components

Frontend consists of the following components:

Exploration

Figure 1. Exploration component

This components features an autocomplete function using a Full-Text index. Once you select a character, a small character subgraph is visualized. If you click on any other characters a popup will show. The popup has an option to expand relationships for a selected characters, giving it a bit of an interactivity.

Timeline

Figure 2. Timeline component

This component fetches all the interaction data from GraphQL. When you click on the start button, it then adds a new relationship every 200ms, giving it a dynamic network visualization. The relationships are ordered in the order they first appeared in the book, so in theory, you should see how relationships formed through time in the HP book.

Network visualization

Figure 3. Network component

This component visualizes a classic network analysis. Nodes are colored based on the community they belong to and their size is calculated by how central in the network they are (pagerank).