Omnigram Explorer

A Simple Interactive Tool for Exploring Complex Computational Models

Documentation

User Guide: version 1.1.1 (.pdf format) (older versions: v1.1, v1.0)
Technical Documentation: version 1.0 (.pdf format)

Introductory Video

Downloads

Windows 64-bit	omnigram-v1p1p1-windows-64bit.zip (v1.1.1)
Windows 32-bit	omnigram-v1p1p1-windows-32bit.zip (v1.1.1)
Mac OS X	omnigram-v1p1p1-macosx.zip (v1.1.1)	(See note 1)
Linux 64-bit	omnigram-v1p1p1-linux-64bit.tar.gz (v1.1.1)
Linux 32-bit	omnigram-v1p1p1-linux-32bit.tar.gz (v1.1.1)
Source package	omnigram-v1p1p1-source.zip (v1.1.1)	(See note 2)

Notes:

You will see warnings about running an app from an unsigned developer if you run this version. It is safe to ignore these warnings.
If you prefer, you can install Processing and the Omnigram source package, and run Omnigram from within Processing.
Not a standalone app, requires Processing to be installed.

Source Code

Omnigram Explorer is written in Processing. The source code is available on GitHub at https://github.com/tim-taylor/omnigram

Publications

Kevin Korb and Tim Taylor. "Omnigram Explorer: An Interactive Tool for Understanding Bayesian Networks". Presented at the Seventh Annual Conference of the Australasian Bayesian Network Modelling Society (ABNMS2015), Melbourne, Australia, November 2015.
- Download presentation slides (.pdf)

R. F. Ropero, Ann E. Nicholson and Kevin Korb. "Using a New Tool to Visualize Environmental Data for Bayesian Network Modelling". In Proceedings of the 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015, LNCS volume 9422, Springer, 2015 (pp. 175-184).
- Download paper (.pdf)

Tim Taylor, Alan Dorin and Kevin Korb. "Omnigram Explorer: A Simple Interactive Tool for the Initial Exploration of Complex Systems". In Proceedings of the European Conference on Artificial Life 2015, MIT Press, 2015 (pp. 381-388).

Acknowledgements

Omnigram Explorer was developed by Tim Taylor, Alan Dorin and Kevin Korb at the Faculty of Information Technology, Monash University, in collaboration with Jodie McVernon, James McCaw, Nicholas Geard and Patricia Campbell at the Melbourne School of Population and Global Health at the University of Melbourne.

The project was funded by ARC grant number DP110101758 ("Development of an 'ageing household' model for assessing medium to long-term vaccine impact in populations", Dr Jodie McVernon, Dr Kevin B Korb, Dr Kathryn Glass, Dr James McCaw, Dr Emma McBryde).

Page last updated: 9 January 2016