Visualizing network data
Released in 2012, the sigma.js plugin for Gephi allows for the interactive display of network data in a web browser using open-source technologies, principally sigma.js. The HTML framework and Gephi plugin were a collaborative effort by Scott A. Hale, Joshua Melville, and Kunika Kono at the Oxford Internet Institute as part of a small summer project funded by Jisc.
We have been overjoyed by the enthusiastic reception of the plugin/code. Visualizations produced with the plugin have been used on over 10,000 websites including Elsevier, Harvard, the Wikimedia Foundation, and MastodonC. Collectively, these visualizations have been viewed over one billion times by more than one million unique users.1
Since the initial release of our plugin, the size/scale and types of data people wish to visualize have changed, and the technologies for displaying and summarizing data have also evolved. Nonetheless, we believe our core goal of creating easy-to-use alternatives to static images remains just as relevant, and we will be continuing to develop the plugin as part of the Nexus project at the OII.
The Nexus team—Jonathan Bright, Scott Hale, and Graham McNeill—are testing alternative ways to visualize network data with geographic and/or temporal properties. As a first step of this project, we have released an updated plugin for Gephi 0.9.x. For the moment, this plugin simply reproduces all the behaviour of the previous plugin for Gephi 0.8.x, but more updates will be coming. The largest update will be a switch to the newer 1.1 version of Sigma.js, which greatly improves support for mobile devices. Later, some of the features for geospatial and/or temporal data created within the Nexus project will also be incorporated.
Users of our plugin may also be interested in a separate development direction towards capturing self-reported network/friendship data in a rich and detailed way through technology and structured interviews, for which Josh Melville has developed Network Canvas.
1. Statistics are from Google Analytics and represent a lower bound as the code can be easily modified (as we hope people do!) and the analytics removed. Figures are from January 1 2013 to January 1 2016. Unique users are unique across all outputs produced with the plugin.
Note: This post was originally published on the OII's Smart Cities project blog on . It might have been updated since then in its original location. The post gives the views of the author(s), and not necessarily the position of the Oxford Internet Institute.