Trade-offs in the design of cross-disciplinary software systems
(2005) 2005 International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, MODSIM 2005 In MODSIM 2005 - International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Proceedings p.732-737- Abstract
As researchers we are often faced with the difficult and demanding task of preparing models, and their computer implementations, for decision making, or, more recently, for integrated assessment. Such assessment often involves large scale problems, where the decisions to be made can deeply affect the environment, the social context and the economic background of regions and even nations. Yet, we face the grim reality that a model is a focused representation of the world, and it is always a result of several compromises in terms of details and structure, leading to trade-offs in terms of complexity, flexibility and performance. This trade-off becomes an essential design property. We often wish our models to be as simple as possible,... (More)
As researchers we are often faced with the difficult and demanding task of preparing models, and their computer implementations, for decision making, or, more recently, for integrated assessment. Such assessment often involves large scale problems, where the decisions to be made can deeply affect the environment, the social context and the economic background of regions and even nations. Yet, we face the grim reality that a model is a focused representation of the world, and it is always a result of several compromises in terms of details and structure, leading to trade-offs in terms of complexity, flexibility and performance. This trade-off becomes an essential design property. We often wish our models to be as simple as possible, balancing transparency, understandability and level of detail. Now, we are involved in the SEAMLESS project, an EU FP6 Integrated Project, aims at generating an integrated framework of computer models. This framework can be used for assessment of how future alternative agricultural and environmental polices affect sustainable development in Europe. Thus, we are designing a cross disciplinary software system to deal with different simulation domains. In this, we need to take care of many differences between the different modeling societies. We decided to apply an architecture centric development method and evaluated this with stakeholders based on a so-called Architecture Trade-off Analysis method. When prioritizing the requirements we used a cost-benefit analysis as a weighting factor for deciding what to do first. Requirements were grouped in user-roles, that appeal to differences in user-interface options. The resulting software architecture identified the necessity to identify two major blocks: the modeling environment, to be used by a number of user roles, mostly modelers and coders, and the processing environment, which is oriented towards the needs of those user roles more focused on system analysis, rather than design and implementation. Another key factor of our architecture is the knowledge base, which provides a common repository for all knowledge, data, model sources which are shared by the two environments. When moving on from architecture to design and implementation, we tried to steer clear of the risk of inventing another modelling framework, and therefore in our prototype we use different existing frameworks for different tasks in the overall design. This means that we discussed the view that 'one tool fixes everything', and we chose to rely on specific frameworks for specific needs. We chose a modelling framework with a track record in crop modeling, to target our biophysical modeling needs, and we selected a de facto standard framework for economic modeling to solve agri-economic modelling problems. All of this comes at a price, that is the extra effort required to integrate different frameworks. We chose therefore to develop an evolution of the OpenMI integration framework to target this issue. In this article we describe all the risks we have identified as associated to our architecture centric approach and how we dealt with them. This article describes the design of the modeling framework for SEAMLESS. A first prototype is ready in January 2006.
(Less)
- author
- van der Wal, T. ; Knapen, R. ; Svensson, M. LU ; Athanasiadis, I. and Rizzoli, A. E.
- organization
- publishing date
- 2005
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Integrated assessment frameworks, Modeling, Ontologies, Simulation, Software design
- host publication
- MODSIM 2005 - International Congress on Modelling and Simulation : Advances and Applications for Management and Decision Making, Proceedings - Advances and Applications for Management and Decision Making, Proceedings
- series title
- MODSIM 2005 - International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Proceedings
- editor
- Zerger, Andre and Argent, Robert M.
- pages
- 6 pages
- publisher
- Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ)
- conference name
- 2005 International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, MODSIM 2005
- conference location
- Melbourne, Australia
- conference dates
- 2005-12-12 - 2005-12-15
- external identifiers
-
- scopus:85086311311
- ISBN
- 0975840029
- 9780975840023
- language
- English
- LU publication?
- yes
- id
- 2fd48d26-b33f-4c67-8d20-aec7ddf86d30
- date added to LUP
- 2021-01-11 10:29:39
- date last changed
- 2021-05-07 10:16:43
@inproceedings{2fd48d26-b33f-4c67-8d20-aec7ddf86d30,
abstract = {{<p>As researchers we are often faced with the difficult and demanding task of preparing models, and their computer implementations, for decision making, or, more recently, for integrated assessment. Such assessment often involves large scale problems, where the decisions to be made can deeply affect the environment, the social context and the economic background of regions and even nations. Yet, we face the grim reality that a model is a focused representation of the world, and it is always a result of several compromises in terms of details and structure, leading to trade-offs in terms of complexity, flexibility and performance. This trade-off becomes an essential design property. We often wish our models to be as simple as possible, balancing transparency, understandability and level of detail. Now, we are involved in the SEAMLESS project, an EU FP6 Integrated Project, aims at generating an integrated framework of computer models. This framework can be used for assessment of how future alternative agricultural and environmental polices affect sustainable development in Europe. Thus, we are designing a cross disciplinary software system to deal with different simulation domains. In this, we need to take care of many differences between the different modeling societies. We decided to apply an architecture centric development method and evaluated this with stakeholders based on a so-called Architecture Trade-off Analysis method. When prioritizing the requirements we used a cost-benefit analysis as a weighting factor for deciding what to do first. Requirements were grouped in user-roles, that appeal to differences in user-interface options. The resulting software architecture identified the necessity to identify two major blocks: the modeling environment, to be used by a number of user roles, mostly modelers and coders, and the processing environment, which is oriented towards the needs of those user roles more focused on system analysis, rather than design and implementation. Another key factor of our architecture is the knowledge base, which provides a common repository for all knowledge, data, model sources which are shared by the two environments. When moving on from architecture to design and implementation, we tried to steer clear of the risk of inventing another modelling framework, and therefore in our prototype we use different existing frameworks for different tasks in the overall design. This means that we discussed the view that 'one tool fixes everything', and we chose to rely on specific frameworks for specific needs. We chose a modelling framework with a track record in crop modeling, to target our biophysical modeling needs, and we selected a de facto standard framework for economic modeling to solve agri-economic modelling problems. All of this comes at a price, that is the extra effort required to integrate different frameworks. We chose therefore to develop an evolution of the OpenMI integration framework to target this issue. In this article we describe all the risks we have identified as associated to our architecture centric approach and how we dealt with them. This article describes the design of the modeling framework for SEAMLESS. A first prototype is ready in January 2006.</p>}},
author = {{van der Wal, T. and Knapen, R. and Svensson, M. and Athanasiadis, I. and Rizzoli, A. E.}},
booktitle = {{MODSIM 2005 - International Congress on Modelling and Simulation : Advances and Applications for Management and Decision Making, Proceedings}},
editor = {{Zerger, Andre and Argent, Robert M.}},
isbn = {{0975840029}},
keywords = {{Integrated assessment frameworks; Modeling; Ontologies; Simulation; Software design}},
language = {{eng}},
pages = {{732--737}},
publisher = {{Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ)}},
series = {{MODSIM 2005 - International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Proceedings}},
title = {{Trade-offs in the design of cross-disciplinary software systems}},
year = {{2005}},
}