User:TimAngus/sandbox/Graphia (software)

Graphia is an open source data visualization software package that uses graph drawing for the interpretation of large and complex datasets.

History
Created by researchers hailing from the Roslin Institute, Graphia was developed by a company spun out from the University of Edinburgh. Unable to make a commercial success of it, the company folded in 2020 and the software was subsequently released under an open source license.

Usage
Graphia was originally designed to create and visualize correlation graphs from the primary data that is produced in the life sciences. In this sense it may be considered a bioinformatics tool, indeed this is is primary use case. Nevertheless, Graphia is data type agnostic and has also been used in other fields such as Social network analysis and Blockchain analysis. Architecturally, a plugin system is used, meaning that Graphia can be extended beyond what is available by default.

Functionality
Graphia has a focus on interactivity, with its layout process occurring in real time and graph construction parameters adjustable on the fly. The latter is realised through a parametric style transformation system whereby individual processes which permute the graph are chained together, the results of which are immediately visible to the user. This approach reduces the round trip time that might be experienced compared to a process where the graph is repeatedly constructed from scratch, and therefore encourages experimentation. In this way Graphia is highly data driven. A number of transforms are provided for manipulating and analysing the graph, using various algorithms such as Louvain Clustering, Betweenness centrality and k-NN.

Given Graphia's focus on creating graphs from large and complex datasets, it follows that it is able to equivalently visualize very large graphs. This capability is obviously hardware dependent, but at the top end graphs consisting of millions of nodes and edges are successfully rendered. Furthermore, the visualization is (optionally) presented in 3D which can illuminate structure not otherwise apparent using more traditional methods.