Network and Graph Visualization

KnowledgeVis has processed and visualized graph-based datasets for many projects. Graph data structures are a useful model for many types of datasets containing entities and relationships.
Graph algorithms, such as centrality and Page-Rank, can be applied to make it easier to understand unique aspects of a graph's connectivity structure. KnowledgeVis was on the team that created multinet.app, a web-based graph exploration environment currently available on the internet. Knowledge Graphs, a subset of graph organizations, are now used commonly in Retrieval Augmented Generation systems for Large Language Models. Regardless of the graph content, it can be helpful to render the graphs or subgraphs and explore the entities and relationships encoded in the networks. KnowledgeVis has mapped multiple datasets into graph structures and used open-source RAG tools to create knowledge graphs for content retrieval. The images here are of subsets of knowledge graphs in biological and medical applications.