Environments

Up to 80% of a modeling code may be supporting various input/output functionality and interfaces with data and other programs. It makes perfect sense to build software packages that would take care of these data sharing and communication procedures, so that modelers can focus on the actual formalization of processes and systems. There are numerous modeling environments developed to support modeling and to increase model functionality.

• OpenMI - OpenMI Association, http://www. openmi.org/ - open source, platform independent

OpenMI stands for Open Modelling Interface and Environment, a standard for model linkage in the water domain. OpenMI avoids the need to abandon or rewrite existing applications. Making a new component OpenMI compliant simplifies the process of integrating it with many other systems. It provides a method to link models, both legacy code and new ones. OpenMI standardizes the way data transfer is specified and executed; it allows any model to talk to any other model (e.g., from a different developer) without the need for cooperation between model developers or close communication between integrators and model developers. Based on Java and .NET technology, currently OpenMI has some 20+ compliant models in its library.

• SME - UVM, http://www.uvm.edu/ - Open Source, Mac/Linux/UNIX

The Spatial Modeling Environment (SME) links Stella with advanced computing resources. It allows modelers to develop simulations in the Stella user-friendly, graphical interface, and then take equations from several Stella models and automatically generate C++ code to construct modular spatial simulations and enable distributed processing over a network of parallel and serial computers. It also provides a viewserver to present results of spatial simulations in a variety of graphic formats.

• SAMT - ZALF, http://www.zalf.de/ - open source, Linux

Spatial Analysis and Modelling Tool (SAMT) is a modeling system with some GIS features, designed to help with spatial analysis. It is an open system that links to different models (especially fuzzy models, neural networks, etc.). It can also link to a general purpose modeling language DESIRE.

Pros. Added functionality to other models and modeling tools.

Cons. Hardly any, since modeling environments mostly serve other modeling paradigms, instead of imposing any of their own upon the user. In most cases, it is the next level of modeling, which may require quite good modeling and systemic skills. Usually user and developer groups are quite limited and are very much driven by enthusiasm. Therefore future development and support may be quite uncertain.

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