University of Konstanz
Algorithmics Group
Prof. Dr. Ulrik Brandes

EgoNet2GraphML

EgoNet is a software to conduct interviews in which the personal networks of respondents are collected. EgoNet2GraphML is a small graphical java program that can (1) convert EgoNet interviews into GraphML files (that can be opened with visone) and (2) cluster, aggregate, and visualize collections of personal networks using the methodology proposed in: Ulrik Brandes, Jürgen Lerner, Miranda J. Lubbers, Chris McCarty, and Jose Luis Molina Visual Statistics for Collections of Clustered Graphs. Proc. IEEE Pacific Visualization Symp. (PacificVis'08), 2008.

Conditions of use

License: EgoNet2GraphML is available under the terms and conditions of the Creative Commons Attribution-ShareAlike 3.0 (CC BY-SA 3.0) license. (Informally, this means that it can be used free of charge; follow the preceeding link for the license terms.)

Citation: "Algorithmics Group. EgoNet2GraphML. Available at http://inf.uni-konstanz.de/exalgo/software/egonet2graphml/. University of Konstanz, 2012-2017."

Disclaimer: EgoNet2GraphML ("software") is developed and maintained in the Algorithmics Group, Department of Computer & Information Science, University of Konstanz, Germany ("author"). Some rights reserved. The software is provided "AS IS", with no warranty, express or implied, including but not limited to the implied warranties of merchantability and fitness for a particular use. In no event shall the author be liable for any damages, direct or indirect, even if advised of the possibility of such damages. If you do not accept these restrictions, you do not have permission to download or use EgoNet2GraphML.

Tutorial

A basic tutorial on how to use EgoNet2GraphML is given in the visone wiki's personal networks (tutorial).

Download

Download the file EgoNet2GraphML.jar to your computer and execute it. You need to have the java runtime environment (JRE 6 or newer) installed on your computer.

Current version:

Previous versions (for reproducability):

Contact

Address questions, comments, bug reports, or feature requests to Jürgen Lerner.