Friday, August 21, 2009

New publication explains openModeller in detail

If you want to know how openModeller works and why it was created, GeoInformatica has just published a new paper as an electronic Online First article with this information:

http://www.springerlink.com/content/n805714x26265573/

Now the following reference can be used to cite openModeller:

Muñoz, M.E.S., Giovanni, R., Siqueira, M.F., Sutton, T., Brewer, P., Pereira, R.S., Canhos, D.A.L. & Canhos, V.P. (2009) "openModeller: a generic approach to species' potential distribution modelling". GeoInformatica. DOI: 10.1007/s10707-009-0090-7

As soon as it gets published in a paginated issue, you will be able to add volume number and page range to the citation. The publications section will be updated accordingly when the corresponding journal issue gets compiled.

Friday, May 22, 2009

openModeller 1.0 is available

This release contains only a few adjustments and minor feature enhancements, but it consolidates all work that was done during the last 4 years as part of a thematic project funded by Fapesp. Some people are still working on additional features that will hopefully be incorporated in future releases, such as a new version of the maximum entropy algorithm (Maxent), a new algorithm called Niche Mosaic and paralellized versions of GARP.

Version 1.0 includes adjustments in algorithms (ANN and SVM), command line tools (om_model and om_niche) and ROC curve procedures. It also contains improvements in the modelling protocol, and model statistics (possibility to use lowest presence threshold).

More details about this release can be seen here.

Thursday, January 15, 2009

Version 0.7.0 of the openModeller library released

Version 0.7.0 of the openModeller library is now available. This release contains the following main changes/features:
  • New algorithm using Artificial Neural Networks;
  • New option to generate distribution maps directly in ARC/Info ASCII grid format (byte or floating point);
  • New keywords "Spatially unique" and "Environmentally unique" can be used to filter input points when using om_console;
  • Change in AUC calculation: when no absences are provided, instead of using 1-specificity after generating pseudo-absences, it now uses the proportion of points predicted present for a large number of random background points;
  • New method in the RocCurve class to calculate partial area ratio;
  • New parameters to om_test: --calc-matrix, --calc-roc, --num-background and --max-omission.

Please note that the previous release (0.6.1) also includes these changes:
  • Many adjustments in the command line tools;
  • New method in the modelling service to perform external tests;
  • Possibility for the modelling server to submit jobs to Cluster nodes via Condor.

More details about the latest release can be found here .