Networks are everywhere: social networks, power grids, emails, financial transactions or gene-protein interactions are just a few examples. Started as a student project itself at the university four years ago, Gephi has quickly become the open source software leader in the visualization and analysis of large networks. It is an important contribution to the ecosystem of tools used by researchers and big data analysts to explore and extract value from the deluge of relational data, and disseminate a better ability for the people to think about a “connected” world.
Gephi is a “Photoshop” for such data: designed to make data navigation and manipulation easy, it covers the entire process from data importing to aesthetics refinements and communication. Users interact with the visualization and manipulate structures, shapes and colors to reveal the properties of complex and messy data. The goal is to help data analysts to make hypotheses and intuitively discover patterns or errors in large data collections. Gephi is built with Java SE 6 on top of the NetBeans Platform, and uses a large number of Java libraries, including JOGL for its 3-D rendering engine.
The strength of Gephi is its usability, performance, and modularity. Modules are loosely coupled, and extensible with plug-ins. Data-centered companies such as LinkedIn, Xerox, Elsevier, and many research laboratories have already used Gephi for visualizing their data. Gephi is supported by the Gephi Consortium, a non-profit organization created to ensure future developments of the technology.
- Cloud Gephi This message contains my application proposal for the Cloud Gephi Project.
- Force Directed Edge Bundling Implementing Force Directed Edge Bundling algorithm in Gephi as a Preview plugin
- Graph Streaming This project aims to implement the Gephi Graph Streaming API by interconnecting GraphStream’s dynamic graph event model with Gephi so as to have Gephi visualize ongoing graph evolutions and measurements. This proposal gives an introduction of GraphStream’s dynamic graph event model and Gephi’s support for dynamic graph. Then a method based on the source, sink and pipe model in GraphStream is provided for integrating GraphStream with Gephi. At last, the time line and milestones are listed.
- Legend Module Legends are of great importance when interpreting graphs. Missing or wrong legends could lead to misunderstandings and reduce the importance of a research's objective. The Legend Module implementation solves this problem, providing a highly customizable module, that allows the user to explore and interpret some representative data patterns, and also allows the developers to extend its functionality by creating news plugins.