Figure 6 Odum's formalism for energy-based conceptual diagrams: (a) source of energy, (b) sink (loss of energy from system), (c) storage tank, (d) production unit (takes in energy and information to create other quality of energy), (e) consumption unit, and (f) energy mixer of work gate.

subwatersheds, river reaches, and reservoirs. The Stella interface can be used as a drawing board to put together various conceptual diagrams and discuss them with other people in a process known as participatory modeling. In

this case the major value of the interface is that one can easily add or delete variables and processes, and immediately see what impact this may have on the model performance. The model itself becomes a tool for deliberations and consensus building.

Very similar diagrams can be put together using other system dynamics software such as Madonna, Vensim, Powersim, or Simile. In these software packages the 'stock-and-flow' formalism is used to describe the system. The diagrams are also known as flow diagrams because they represent how material flows through the system.

A somewhat different formalism is used in packages such as GoldSim, Simulink, and Extend. Here we have more flexibility in describing what we wish to do in the model and the model does not need to be presenting only the stocks and flows. Groups of processes can be defined as submodels and encapsulated into special icons that become part of the icon set used to put together the diagrams. As usual, we get more functionality and versatility at the expense of a steeper learning curve and higher complexity of design.

Yet another option in building conceptual diagrams is given by the Universal Modeling Language (UML), which is a standardized specification language for object modeling. It is designed as a diagrammatic tool that can be used to build models as diagrams, which can be then automatically converted into a number ofobject-oriented languages, such as Java, C++, Python, etc. In this case, one is actually almost writing computer code when developing the conceptual model. Once again, even more universality and almost infinite flexibility is achieved at a price of yet more efforts one will need to make mastering the tool. Figure 8 presents a sample conceptual diagram created in UML to formulate an agent-based model of a landscape used by sheep farmers, foresters, and National Park rangers that are interacting on very different temporal and spatial scales with different development objectives (sheep production, timber production, and nature conservation).

There are several types ofdiagrams that one can create using UML. One of them is the activity diagram, which describes the temporal dimension of the model. The class




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Figure 8 A UML class diagram of a system can be used both as a conceptual diagram and as a way to program the model. From Etienne M, Le Page C, and Cohen M (2003) A step-by-step approach to building land management scenarios based on multiple viewpoints on multi-agent system simulations. Journal ofArtificalSocieties and Social Simulation 6(2), http://jasss.soc.surrey.ac.uk/672/ 2.html (accessed December 2007).

diagram presented in Figure 8 in a way corresponds to the structural dimension, but may also have elements of the spatial representation, like in the Lake model in Figure 4. Most of software tools designed to create UML diagrams, such as Visual Paradigm (http://www. visual-paradigm.com) would also provide code generators that would convert the UML diagram into computer code in a language of choice.

More recently, there have been attempts to standardize the conceptual, diagrammatic representation of system using domain ontologies. A domain ontology represents a certain domain, ecosystem, or part of an ecosystem by defining the meaning of various terms or names as they apply to those ecosystems. The idea was to define all the various components of ecosystems and present their interactions in a hierarchical way, so that once one needs to model some part of the world one could pull out the appropriate set of definitions and connections and have the desired conceptual model. Several formal languages have been proposed to describe such ontologies.

Among them OWL is probably best known, and designed to work over the World Wide Web. So far it is yet to be seen how these ontological approaches will be accepted by the modeling community. As with other attempts to streamline and automate the modeling process, we may be compromising its most essential part, that is, the exploration and research of the system, its elements and processes, at the level of detail needed for a particular study goal. Any attempt to automate this part of the modeling process may forfeit the exploratory part of modeling and may diminish the new understanding about the system that the modeling process usually offers.

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