Abstract
This paper presents the software Omnigram Explorer, a visualization tool developed for interactive exploration of relations between variables in a complex system. Its objective is to help users gain an initial knowledge of their data and the relationships between variables. As an example, we apply it to the water reservoir data for Andalusia, Spain. Two Bayesian networks are learned using causal discovery, both with and without the information gleaned from this exploration process, and compared in terms of the Logarithmic loss and causal structure. Even though they show the same predictive accuracy, the initial exploration with Omnigram Explorer supported the use of prior information to achieve a more informative causal structure.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Omnigram Explorer is an open-source tool developed in Processing (http://processing.org). The source code, executables (for Windows, Mac and Linux), documentation and related material are available at http://www.tim-taylor.com/omnigram/.
- 2.
References
Coreau, A., Treyer, S., Cheptou, P., Thompson, J.D., Mermet, L.: Exploring the difficulties of studying futures in ecology: what to do ecological scientists think? Oikos 119, 1364–1376 (2010)
Heer, J., Bostock, M., Ogievetsky, V.: A tour through the visualization zoo. Commun. ACM 53(6), 59–67 (2010)
Kelly, R., Jakeman, A.J., Barreteau, O., Borsuk, M., ElSawah, S., Hamilton, S., Henriksen, H.J., Kuikka, S., Maier, H., Rizzoli, E., Delden, H., Voinov, A.: Selecting among five common approaches for integrated environmental assessment and management. Environ. Model. Softw. 47, 159–181 (2013)
Korb, K.B., Nicholson, A.E.: Bayesian Artificial Intelligence. CRC Press, Boca Raton (2011)
Méndez-Jiménez, M.: Estudio Básico de Adaptación al Cambio Climático (2012)
O’ Donnell, R.: Flexible Causal Discovery with MML. Ph.D. thesis, Faculty of Information Technology (Clayton). Monash University, Australia, 3800, September 2000
Parrott, L.: Hybrid modelling of complex ecological systems for decision support: recent successes and future perspectives. Ecol. Inf. 6, 44–49 (2011)
Ricci, P.F., Rice, D., Ziagos, J., LA Jr., C.: Precaution, uncertainty and causation in environmental decisions. Environ. Int. 29, 1–19 (2003)
Spence, R., Tweedie, L.: The attribute explorer: information synthesis via exploration. Interact. Comput. 11, 137–146 (1998)
Taylor, T., Dorin, A., Korb, K.: Omnigram explorer: a simple interactive tool for the initial exploration of complex systems. In: Proceedings of the European Conference on Artificial Life 2015, pp. 381–388, MIT Press (2015)
Teegavarapu, R.S.V.: Modeling climate change uncertainties in water resources management models. Environ. Model. Softw. 25, 1261–1265 (2010)
Acknowledgements
This work has been supported by ARC grant number DP110101758R. F. Ropero is supported by the FPU research grant, AP2012-2117, funded by the Spanish Ministry of Education, Culture and Sport.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Ropero, R.F., Nicholson, A.E., Korb, K. (2015). Using a New Tool to Visualize Environmental Data for Bayesian Network Modelling. In: Puerta, J., et al. Advances in Artificial Intelligence. CAEPIA 2015. Lecture Notes in Computer Science(), vol 9422. Springer, Cham. https://doi.org/10.1007/978-3-319-24598-0_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-24598-0_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24597-3
Online ISBN: 978-3-319-24598-0
eBook Packages: Computer ScienceComputer Science (R0)