Mailing List: https://gephi.org/developers/
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 five years ago, Gephi has quickly become the open source software leader in the visualization and analysis of large networks (+135,000 downloads of the previous release). 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.
Introduction in video: http://gephi.org/2010/video-introducing-gephi-0-7/
Gephi was officially presented at the 3rd Int'l AAAI Conference on Weblogs and Social Media (ICWSM'09) conference (http://www.icwsm.org).
Award: Oracle Duke's Choice 2010 winner http://www.oracle.com/technetwork/articles/java/dukeschoicewinners-171159.html
- Completing Legend Module The Legend module is an already started project in Gephi. The current module implementation already covers the basic legends models and their rendering. However, the module requires extra effort to reach a higher level of maturity before being camera-ready for release. The primary goals of this year’s project include upgrading to a better UI, revising the legend API, rewriting the legend serialization modules, making the default aspects more appealing and extending the interaction possibilities with legends. The secondary goals of this project include the introduction of two new legends and the integration of legends with the available statistical data.
- Graphstore benchmark and Tuning Graphstore is New graph API that is introduced to core graph structure of Gephi. The graph structure is at heart of the Gephi, so it should be robust and require the optimum memory requirement, thus set of well defined benchmarks is needed in order to test the speed of the core and check the various boundary cases.
- Statistics Unit Tests I would like to impelement some unit testing functionality for statistics package to test existing statistical measures, such as average shortest path, betweenness centrality, page rank and so on.