seamframe, a proposal for an integrated modelling framework for

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SEAMFRAME aims to deliver such an environment, following examples such as Simile. (Muetzelfeldt and Massheder, 2003), ModCom (Hillyer et al. 2003), the ...
Proc. of the 8th ESA Congress, 2004, 331-332

SEAMFRAME, A PROPOSAL FOR AN INTEGRATED MODELLING FRAMEWORK FOR AGRICULTURAL SYSTEMS Andrea E. Rizzoli1, Marcello Donatelli2, Robert Muetzelfeldt3, Tonny Otjens4, Mats G. E. Svensson5, Frits van Evert6, Ferdinando Villa7, John Bolte8 1

IDSIA, Galleria 2, 6928, Manno, Switzerland. Email: [email protected] ISCI, Via di Corticella 133, 40128 Bologna, Italy 3 Simulistics Ltd. Edinburgh Technology Transfer Centre, King’s Buildings, Edinburgh EH9 3JL, UK 4 Alterra - Wageningen Software Labs, P.O. Box 47, 6700 AA, Wageningen, The Netherlands 5 Centre for Environmental Studies, P O Box 170, Lund University, SE-221 00, Sweden 6 Plant Research International, P.O. Box 16, 6700 AA, Wageningen, The Netherlands 7 University of Vermont, Ecoinformatics Collaboratory, 590 Main St,, Burlington, VT 05401, USA 8 Department of Bioengineering, Oregon State University, Corvallis, OR 97331, USA 2

Issues facing the EC such as the enlargement of the EU, depopulation of rural areas and improving the quality of ground and surface water can only be resolved through integrated analysis of the subsystems of a socio-agro-economic system. Integrated analyses frequently involve integrated modelling, but models of these subsystems have typically been developed by researchers from different scientific disciplines, with little attention to the integration across spatial and temporal scales. The path toward creating integrated models is therefore beset with technical, scientific and social hurdles. SEAMFRAME, an integrated modelling framework within the SEAMLESS project (Van Ittersum et al., these proceedings), aims to overcome these hurdles. Aims and scope of the SEAMFRAME modelling framework The discipline of integrated modelling and assessment is drawing remarkable interest in areas where humans and climate interact with the environment (Rizzoli and Jakeman, 2002). Integrated modelling and assessment requires the support of dedicated software tools, Integrated Modelling Environments, which allow for the composition of models across domains and scales. SEAMFRAME aims to deliver such an environment, following examples such as Simile (Muetzelfeldt and Massheder, 2003), ModCom (Hillyer et al. 2003), the Integrated Modelling Architecture (Villa, 2001), TIME (Rahman et al. 2003), and OpenMI (Gijsbers et al. 2002), but it will extend the existing work with regard to the number of disciplines covered, the range of scales addressed, the way knowledge is represented, and the degree to which workflow management is supported and different data sources used. The software components in SEAMFRAME will enable the identification and use of appropriate models and model combinations, and policy evaluation of agricultural systems, from the perspective of two major user classes: policy and decision makers; and researchers and modellers. SEAMFRAME will provide a set of pre-packaged applications for decision makers. Researchers, modellers and systems analysts will use the Modelling Environment to process models and data, within a graphical user interface aimed at minimising the model coding effort, in order to make them available for re-use within SEAMFRAME. Moreover, the Processing Environment will be used to package and deliver SEAMFRAME applications to Decision Makers that enable transparent use of the models, focused on problems and decisions rather than mechanical details. The SEAMFRAME architecture SEAMFRAME recognizes three components in modelling: data, models and tools; and provides a repository in which these are stored for access by all project members, thus overcoming the problem of knowing which data, models and tools exist and obtaining access to them. SEAMFRAME will employ ontologies (Guarino and Giaretta, 1995) to enable the coupling of data, models and tools at the conceptual level. An ontology is an authoritative description of the concepts and relationships that exist in a given domain. Ontologies may overlap, that is, a concept such as

Proc. of the 8th ESA Congress, 2004, 331-332

"crop" may have a place in an agronomic ontology as well as in an economic ontology. Ontologies also structure the modelling domain, providing a way to express facts and relations that are true about the model. Model elements such as variables, equations, and parameters, will also represented declaratively and kept separate from the implementation of numerical routines. These elements, mapped to their corresponding concepts in a set of ontologies, will allow SEAMFRAME to guide the coupling of data, models and tools, or (in some cases) make these couplings automatically. The use of ontological descriptions in SEAMFRAME is instrumental in overcoming the problem of coupling models that, for example, address different spatial scales (point, field, farm, region), that originate from different scientific problems, or that use different conventions to denote, perhaps, positive direction of mass flow. In practice, using a declarative model in a simulation involves transforming it into executable form and, likely, linking it with other models and data sources. Model executables will be able to communicate through adherence to a set of pre-defined interfaces. Thus, executables derived from a declaratively specified model are fully compatible with legacy executables derived from a procedural specification. Last, SEAMFRAME will provide a mechanism to store comments, discussions and citations about models, data and workflows. An intelligent search agent will enable users to retrieve and combine information from 1) model specifications, 2) model, data, or workflow metadata and their place in an ontology, 3) comments, discussions and citations. Thus, a researcher faced with the task of modelling a certain system can find not only all suitable models, but also the assumptions underlying those models, experiences of other researchers in using those models, and the outcomes of other studies in which those models were used. A decision maker faced with an analysis in which modelling was used, can use SEAMFRAME to find other studies in which the same models were used, other models that could have been used, and discussions about the history and suitability of the models that were used. Final Remarks The proposal is still in its infancy, yet the discussions between the authors has converged on a set of requirements and produced an initial design for SEAMFRAME. The final goal is to develop a much-needed environment for agro-ecological systems in which to develop models and define complex simulation systems, transparently sharing and distributing modelling/system resources of verified quality, References Gijsbers, P. J. A., Moore, R. V. and Tindall, C. I. (2002). In: Hydroinformatics 2002. Fifth International Conference on Hydroinformatics: Cardiff, UK, IAHR. Guarino, N. and Giaretta, P. (1995). In: N. J. I. Mars (ed.), Towards Very Large Knowledge Bases, IOS Press: 25-32. Hillyer, C., Bolte, J., van Evert, F. and Lamaker, A. (2003). Eur. J. Agron. 18 (3-4): 333-343. Muetzelfeldt, R. and J. Massheder (2003). Eur. J. Agron. 18 (3-4): 345-358. Rahman, J. M., Seaton, S. P., Perraud, J.-M., Hotham, H., Verrelli, D. I. and Coleman, J. R. (2003). In: Post, D. A., (Ed.), MODSIM 2003 International Congress on Modelling and Simulation: Townsville, Modelling and Simulation Society of Australia and New Zealand Inc.: 1727-1732. Rizzoli, A.E. and Jakeman, A.J. (Eds.) (2002). Proceedings of the First Biennial Meeting of the International Environ. Modelling and Software Society: Manno, Switzerland, iEMSs, ISBN 88-900787-0-7. Villa, F. (2001). Ecological Modelling 137(1): 23-42. Van Ittersum et al. (2004). These proceedings.