IDEANet: Integrating Data Exchange and Analysis for Networks

IDEANet aims to maximize scientific discovery in network science by significantly lowering the analytic and access barriers-to-entry for researchers. To do so, we offer a set of five integrated modules to securely host, process, analyze, and visualize existing network data using expert-level analytics while conforming to requirements set by source institutions. Our hope is that this project will increase collaboration on intensive, cross-disciplinary data science questions across the social and behavioral sciences.

IDEANet is currently in development. You can try the development version of both our core computer engine and graphical user interface by installing them from Github:

For the core compute engine:

devtools::install_github(“https://github.com/Tom-Wolff/ideanet”)

For the graphical user interface:

devtools::install_github(“kieranlele/IDEANETViz”)

We would love to hear your feedback so we can focus our improving the right sections of our tool. Share your thoughts by completing the following form or emailing the team at gv42@duke.edu. Let us know what you think!

Core documentation is currently available for the majority of functions, with a vignette and video tutorial coming soon.