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.

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.

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 .

How to add new algorithms in openModeller

A new document is available to help those who are interested in adding new algorithms in openModeller. All algorithms must be written in C++. Apart from that, the framework is quite flexible to accommodate new algorithms since they are completely free to decide how distribution models will be represented. The new manual is available here.

openModeller being used by the GBIF data portal

The Global Biodiversity Information Facility (GBIF) recently released a new version of its data portal allowing users to generate niche models in real time. After searching for occurrence records, users have the option to create a niche model when visualizing results.

The data portal uses a Java client that can communicate with a remote modelling service through the openModeller Web Service protocol (OMWS). The Java client was developed by the University of Colorado, and the modelling service by CRIA. Initially, models are being generated only for present time using the Envelope Score algorithm.

GBIF is the world largest biodiversty data portal, currently serving more than 140 million specimen/observation records of which 80% are georeferrenced.

Version 0.6.0 of the openModeller library released

Version 0.6.0 of the openModeller library is now available. This release contains mainly new features, including:

• Drivers to directly read occurrences from GBIF or TAPIR/DarwinCore providers.
• A new command-line tool (om_points) that can be used to retrieve occurrence data using any of the available drivers.
• A new command-line tool (om_algorithm) to get information about the available algorithms.
• A new Maximum Entropy algorithm with two training methods: GIS (Generalized Iterative Scaling) and L-BFGS (Limited-Memory Variable Metric).

The GARP Best Subsets algorithm was also changed to accept the "max threads" parameter, which can be used to speed up the modelling process in multi-processor machines.

More details about this release can be found here:

https://sourceforge.net/project/showfiles.php?group_id=101808&release_id=611859

Released version 0.5.3 of the library

A new version of the openModeller library is available. This release (0.5.3) contains many bugfixes and a new algorithm called Aquamaps. The algorithms "minimum distance" and "distance to average" were removed since EnvironmentalDistance now provides the same functionality. The TerraLib drivers were updated for compatibility with TerraLib 3.2.0. There are two new classes for pre-analysis on input layers to perform jackknife and chi-square (only available as library classes - their functionality still need to be exposed in the command-line and/or Desktop interfaces).

More details about this release can be found here:

http://sourceforge.net/project/shownotes.php?group_id=101808&release_id=587262