Also, there are sections on:
- model databases;
- simulation and modelling organisations;
- other web resources on modelling;
- documents relevant to metamodelling.
AME
Combines System Dynamics and object-based modelling; supports spatial
modelling; generates efficient compiled models. Users can program
their own input/output utilities.
http://helios.bto.ed.ac.uk/ierm/ame
Analytica
Intended as a visual-modelling alternative to the conventional tabular
format of the spreadsheet.
http://www.lumina.com/software/index.html
Extend
For discrete-event, continuous and hybrid simulations.
Features the ability for the user to package up a submodel with its onw
icon, which can then be used as a higher-level component.
http://www.imaginethatinc.com/
Madonna
A System Dynamics visual modelling package, generating very efficient
models.
http://www.kagi.com/authors/madonna/default.html
ModelMaker
ModelMaker is a visual simulation modeling package designed for scientists
and engineers. Based on System Dynamics.
http://www.cherwell.com/ProdHome/mmhome.html
PowerSim
Powersim offers a range of tools for building simulation models based
on the System Dynamics paradigm. Primarily aimed at the business
market.
http://www.powersim.com/
Stella
The best-established of the System Dynamics visual modelling packages.
Offers a range of components in addition to the standard 'stock' symbol,
and majors on user-customisable interfaces. Two special issues of
Ecological Modelling - 110(1)
and 112(2+3)
- was devoted to the use of Stella in this field.
http://www.hps-inc.com/products/STELLA/STELLA.html
Vensim
Originally designed as a tool for running Stella models more efficiently,
now a modelling package in its own right, combining causal loop and System
Dynamics elements.
http://www.std.com/vensim/VENSIM.HTM
CSMP
Fortran-based continuous-systems simulation language; once quite commonly
used for ecological modelling, but I can't find any information on its
current availability.
ModSim III:
Object-oriented simulation
MODSIM III provides both object oriented programming and discrete event
simulation capabilities in one language.
http://www.caciasl.com/ms_product_des.html
SimScript II.5
Principally used for discrete-event simulation, though capable of mixed
discrete/continuous simulations.
http://www.caciasl.com/simscript.html
EcoBeaker
EcoBeaker is an ecological simulation program, designed for use by
students in the classroom. EcoBeaker provides a two-dimensional world in
the computer, into which students can place creatures whose behaviors they
design. As the creatures eat, reproduce, move around, and die, students
can observe patterns and compare them against real-world and theoretical
predictions. Students can also graph many different statistical measurements
from the EcoBeaker world, and sample the populations using a variety of
common sampling techniques. The core of EcoBeaker is a set of 12 laboratories
that cover such subjects as logistic growth, competitive exclusion, the
intermediate disturbance hypothesis, keystone predation, topics in conservation
biology, and various sampling techniques. Each lab has undergone extensive
classroom testing, and is written as an experiment that the student conducts.
Instructors and students can also easily construct their own novel models.
Smile:
The Smile Simulation Environment
Once a mathematical model of a physical system is conceived, it is
expressed in a specification language called ZimOO. ZimOO is an object-oriented
specification language for hybrid systems in which continuous aspects are
modeled by differential equations. A ZimOO specification of a simulation
model is not directly executable, but serves as the basis for implementing
the model in the simulation language Smile. A simulation experiment description
specifies a particular Smile model that is to be simulated and instantiates
both specific parameters of this model (e.g. start values) and certain
global simulation parameters (e.g. simulation time, type of numerical solver
to be used). This information is then used to link the compiled Smile model
to the runtime system, and possibly further external code, producing an
efficient, executable simulation program.
Spatial Modeling
Environment, Version 2
"In an attempt to address the conceptual and computational complexity
barriers to spatio-temporal model development, we have developed a spatial
modeling environment (SME), which links icon-based graphical modeling environments
with parallel supercomputers and a generic object database ( Costanza and
Maxwell 1991 ; Maxwell and Costanza 1994 ; Maxwell and Costanza 1995 ;
SME2 1995 ). This system allows users to create and share modular, reusable
model components, and utilize advanced parallel computer architectures
without having to invest unnecessary time in computer programming or learning
new systems. The following sections give a brief description of the current
design of the SME.
The SME design has arisen from the need to support collaborative model
development among a large, distributed network of scientists involved in
creating a global-scale ecological/economic model. It is intended that
it's design be progressively more inclusive of the full range of relevant
ologic/economic modeling activities. In the interest of maximizing accessibility
to a distributed network of ollaborators, the system is designed to support
a range of platforms, both in the front-end development environment and
in the back-end parallel computing environment. We are thus led to the
formulation of a three-part Modelbase-View-Driver architecture. The three
components are displayed in the Figure and described below.
StarLogo
StarLogo is a programmable modeling environment for exploring the behaviors
of decentralized systems, such as bird flocks, traffic jams, and ant colonies.
It is designed especially for use by students. StarLogo is a specialized
version of the Logo programming language. With traditional versions of
Logo, you can create drawings and animations by giving commands to graphic
"turtles" on the computer screen. StarLogo extends this idea by allowing
you to control thousands of graphic turtles in parallel. In addition, StarLogo
makes the turtles' world computationally active: you can write programs
for thousands of "patches" that make up the turtles' environment. Turtles
and patches can interact with one another -- for example, you can program
the turtles to "sniff" around the world, and change their behaviors based
on what they sense in the patches below. StarLogo is particularly well-suited
for Artificial Life projects.
Swarm
"Swarm is a software package for multi-agent simulation of complex
systems being developed at The Santa Fe Institute. Swarm is intended to
be a useful tool for researchers in a variety of disciplines, especially
artificial life. The basic architecture of Swarm is the simulation of collections
of concurrently interacting agents: with this architecture, we can implement
a large variety of agent based models. Our initial target is Unix machines
running GNU Objective C and X windows: the source code is freely available
under GNU Licensing terms."
JanuSys:
a generic, object-oriented modelling framework
"The JanuSys framework provides a superstructure for building complex
models of agricultural and ecological systems. The framework provides a
set of rules for designing model objects and simulating their interactions.
The generic nature of JanuSys permits applications in which the number
of hierarchical levels and the number of objects in each level are determined
dynamically -- as the simulation is running. This approach is efficient
in terms of memory usage, and opens up a variety of simulation possibilities
that were essentially impossible using FORTRAN-77. Modelers using the framework
are encouraged to concentrate on very small modeling problems (i.e., the
model for a single object at a single hierarchical level) and leave the
integration of the model to the framework.
ModMed Modelling Mediterranean Ecosystem Dynamics
COM:
Component Object Model
This site introduces the potential of COM for ecological/environmental
modelling. COM - the Component Object Model - was developed by MicroSoft
to permit the integration of software written in many different programming
languages. Control of COm has now been handed over to OSF,
the Open Software Foundation, and it is now available on Unix/Linux platforms
as well as MicroSoft. Its potential for ecological/environmental
modelling lies in the fact that a component can be a submodel - anything
from a single equation to a model for vegetation dynamics - written in
any language, but useable by anyone else in their own models.
SESAME
"A set of computer programs designed to solve sets of parallel ordinary
differential equations within a framework which facilitates participation
of multiple partners in the construction and development of large ecosystem
models..
(Ecol.Modelling 86: 265-270)
(used in the ERSEM project: no web material to speak of)
UFIS - the Environmental Research
Information System
One part of UFIS is designed to offer information on ecological models
as a whole. The goal of UFIS is to provide a tool that supports interdisciplinary
work among modellers as well as to give administrative bodies an overview
over national and international activities in ecological modelling. The
availability of such an information system is believed to be crucial to
international coordination of modelling activities. Due to increasing ecological
problems on a global scale coordination has become a key issue to the scientific
community and has led e. g. to the formation of the International Geosphere-Biosphere
Program (IGBP). Model comparisons and questions of model coupling have
been defined as key goals in many IGBP activities (see e. g. [igb94]).
Consequently UFIS will pay particular attention to data requirements of
models, areas of application, and scales of the model. The second part
of UFIS which is closely linked to the model documentation focuses on the
description of data. Since there is no modelling without data it is natural
to combine information systems on data and models in one unit. This is
exactly UFIS' goal. UFIS does not intend to keep data, but will keep information
on where and how to access data (``metadata''). Descriptions of data in
the model information system will be compatible with the ones in the metadata
information system such that relations between models and data can be easily
recovered.
Ref: Ecol. Modelling 86: 141-144
The CAMASE
Register of Agro-ecosystems Models
CAMASE has started to develop a comprehensive register of agro-ecosystems
models, in order to: increase awareness among scientists of existing models;
increase accessibility of these models; stimulate harmonization and compatibility
of models; stimulate use of models. We will attempt to collect 80% of relevant
models used in Europe for research, education and application in: intensively
and extensively produced agricultural crops, grasslands, forests, and their
environments; cropping and farming systems, farm households, land use;
shells for such models; tools for such models in DSS-applications (e.g.
microclimate profiles for irrigation scheduling). The CAMASE Register of
Agro-ecosystems Models will contain only simulation or optimization models
that are documented, at least at a scientific level, and 'validated', at
least partially; it will also contain some software tools that are directly
related to the simulation activities.
REM
The Register of Ecological Models (REM) is a meta-database for existing
mathematical models in ecology.
http://dino.wiz.uni-kassel.de/model_db/server.html
SOMNET
Catalogue of models in the GCTE Focus 3 Soil Organic Matter Network
(SOMNET).
http://yacorba.res.bbsrc.ac.uk/cgi-bin/somnet
ECOBAS_MIF
Documentation of mathematical formulations of ecological processes.
http://dino.wiz.uni-kassel.de/model_db/server.html
Spatio-Temporal
Modeling Page
This page describes Spatio-Temporal Modeling in the context of ecosystem
simulation and discusses the importance of this type of modelling and some
of the computational and conceptual complexity issues involved in building
complex spatio-temporal models.
WWW
Virtual Library: Computer-based Simulations.
Simulation Interoperability
Working Group (SWIG): Other web pages
Landscape Modeling
Has pointers to simulation tools and modelling environments
Related
Projects
Pointers to quite a lot on spatial/distributed simulation
University of Magdeburgh list of Simulation Web Sites and Departments Worldwide"
The Simulation Interoperability
Standards Organization (SISO)
The Simulation Interoperability Standards Organization (SISO) focuses
on facilitating simulation interoperability and component reuse across
DoD, other government, and non-government applications. SISO seeks to provide
a forum for the interchange of new ideas, concepts, and technology across
the broad Modeling and Simulation community; to disseminate these ideas;
to educate M&S practitioners and sponsors regarding their implementation;
and to support the development of standards, practices, and guides for
use in various applications. As part of this effort, SISO sponsors activities
which provide education, technology exchange and standards activities for
the modeling and simulation community.
DEVS:
Discrete Event Specified Systems
"The DEVS formalism provides a means of specifying a mathematical object
called a system. Basically, a system has a time base, inputs, states, and
outputs, and functions for determining next states and outputs given current
states and inputs. Discrete event systems represent certain constellations
of such parameters just as continuous systems do.
The DEVS formalism is more than just a means of constructing simulation
models. It provides a formal representation of discrete event systems capable
of mathematical manipulation just as differential equations serve this
role for continuous systems. Within such a formalism, complex systems may
be modelled, designed, analyzed and simulated. Even software components
maybe implemented all in the same formalism. "
Design
of C++ Classes For Structured Modeling and Sensitivity Analysis of Dynamical
Systems
This paper presents the design and implementation in C++ of an object--oriented
class library for dynamic, continuous-time systems simulation. Using this
library, the user defines hierarchical models of dynamical systems. Using
inheritance hierarchy, the user can build specific models from general
ones and, using the part--whole relationship, can build models consisting
of submodels. A support for model communication using ports is also provided.
The library implements the table algorithm for calculating analytical derivatives
of arithmetic expressions. This algorithm is used to provide tools for
sensitivity analysis of dynamical models. Finally, the library provides
an interface to standard ordinary differential equation (ODE) solvers,
making it possible to use currently existing libraries of such solvers.
Metamodeling
Techniques and Applications
Metamodeling is a very new statistics-based field of Modeling and Simulation,
whereby mathematical approximations -- equations -- are built between a
model's set of input factors and its output response(s). Iterative order-reduction
techniques are performed on the chosen model (and its subsequent reduced-order
approximations) to eventually arrive at a "statistically acceptable" abstraction
of the original, detailed model. It is an extremely difficult problem,
and therefore, has not been widely explored. However, it is believed by
Dr. Caughlin and a handful of prominent authors in the modeling community
that it could have enormous application in resolving the multi-level fidelity
problem; currently the biggest stumbling block in hierarchical simulation.
Metamodeling
Aspects of Model Conceptualization
This paper suggests a technique for improving the conceptual-ization
of models. The key aspect of this technique is to set aside the main model
for a period of time during the model conceptualization process and focus
on building a "watchdog" submodel. The primary purpose of the watchdog
submodel is to assure that the main model remains internally consistent
during its operation. In the experience of this author, such a submodel
can help to identify model conceptualization errors and to determine if
a model is sufficiently "robust" to adequately replicate the behavior of
the system being modeled. This paper suggests a technique for improving
the conceptual-ization of models. The key aspect of this technique is to
set aside the main model for a period of time during the model conceptualization
process and focus on building a "watchdog" submodel. The primary purpose
of the watchdog submodel is to assure that the main model remains internally
consistent during its operation. In the experience of this author, such
a submodel can help to identify model conceptualization errors and to determine
if a model is sufficiently "robust" to adequately replicate the behavior
of the system being modeled.
Metamodeling
and method specifications
In the MetaPHOR project the objectives for developing metamodeling
principles and formal method specifications are the following:
to develop general guidelines and frameworks to support method engineers'
work,
to study and test metamodeling languages for specifying ISD methods,
to apply and test metamodeling approaches for comparing ISD methods
and supporting their use in CASE tools
by a set of metrics and frameworks, that allows for comparison and
analysis of new and existing methods .
to develop ISD methods with an emphasis on new fields and unexplored
possibilities for IS modelling which lack extensive and rigorous support,
such as inter-organisational networks.