S.J.C. Janssen

Publications (31)0 Total impact

• Source

  Available from: Andrea-Emilio Rizzoli

  Article: Defining projects and scenarios for integrated assessment modelling using ontology

  S J C Janssen, J J F Wien, Hongtao Li, I N Athanasiadis, F Ewert, M J R Knapen, D Huber, O Thérond, A E Rizzoli, H Belhouchette, M Svensson, M K Van Ittersum
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  ABSTRACT: EXTENDED ABSTRACT Integrated Assessment Modelling provides a systematic inter-disciplinary approach to support coherent ex-ante decision-making by a flexible integration of (reusable) models and datasets across scales. Within integrated assessment modelling a coherent and robust description of projects and scenarios is required to facilitate data preparation, model integration and the graphical user-interface development. This paper explains our experiences with a challenging and time-consuming task, e.g. arriving at a shared understanding on the definition of projects, experiments and scenarios among researchers coming from different disciplines, who have been exposed to dissimilar education and research experience. We demonstrate the use of ontologies in building this shared set of definitions and the relationship between the ontology and the human computer interaction through a case study. With a common ontology that represents the joint conceptualization of the projects, experiments and scenarios each researcher can refer at any later stage to the semantics of the concepts used. A collaborative approach was used to build such a common ontology in the SEAMLESS-Integrated Project, funded through the EU sixth Framework Programme, which aims at developing an integrated modelling framework (SEAMLESS-IF) to assess, ex-ante, agricultural and environmental policy options, allowing cross-scale analysis of a broad range of sustainability issues. Through several iterations a common ontology for projects, experiments and scenarios was built. In our common ontology a project has one and only one problem definition, and it can handle at least one or more Experiments. Experiments represent the assessment of one or a combination of policy options in a given context and outlook on the future. The indicator(s) should be the same between experiments which are part of the same project, allowing the comparison of different experiments. Each of the concepts Policy Option, Context and Outlook capture one part of the input parameters required for running each of the models. As a first validation of the project ontology, a set of four fictitious sample projects were made. One of these sample projects is an integrated assessment for one region Midi-Pyrénées in the South of France concerning the impacts of the CAP2003 reform, which is described in this paper The common project ontology highlighted the imprecise meaning of the word scenario and it links projects to problems, outlooks on the future, indicators, context of the problem, policies and ultimately to model runs in experiments. Also, by this common ontology the assumptions in building the assessment are clarified, moving the focus away from the tools to the assumptions underlying models and scenarios. In any integrated assessment project, it is recommended to clarify with its participants the meaning of scenario and associated concepts. We achieved this by the use of a common ontology, which forces participants to be clear, precise and coherent in their description of concepts and relationships between concepts, while the common ontology can be directly used for development of databases, models and graphical user interfaces.
  01/2008;
• Article: A web-based software system for model integration in impact assessments of agricultural and environmental policies

  J.E. Wien, A. Rizzoli, M.J.R. Knapen, I. Athanasiadis, S.J.C. Janssen, L. Ruinelli, F. Villa, M. Svensson, P. Wallman, B. Jonsson, Ittersum, M.K
  Environmental and Agricultural Modelling: Integrated Approaches for Policy Impact Assessment.
• Article: Ex-ante assessment of the abolishment of the EU set aside policy: Results from a bio-economic farm analysis

  A. Kanellopoulos, H. Hengsdijk, S.J.C. Janssen, Ittersum, M.K
• Article: The environmental component, the farming systems component and the socio-economic component of the final version of the SEAMLESS database

  E. Andersen, B.S. Elbersen, G.W. Hazeu, Diepen, C.A, B. Baruth, A.D. Verhoog, I.J. Terluin, N. Borkowski, S.J.C. Janssen
• Article: How to manage models outputs aggregation for indicator quantification within SEAMLESS integrated framework

  O. Therond, N. Turpin, H. Belhouchette, I. Bezlepkina, C. Bockstaller, S.J.C. Janssen, J. Alkan Olsson, J.E. Bergez, J. Wery, F. Ewert
• Source

  Available from: Andrea-Emilio Rizzoli

  Article: Semantic modelling in farming systems research, The case of the Agricultural Management Definition Module

  I.N. Athanasiadis, S.J.C. Janssen, D. Huber, A.E. Rizzoli, Ittersum, M.K
  Information Technologies in Environmental Engineering.
• Article: Surveying crop management data for bio-economic farm models

  N. Borkowski, J.M. Hecker, K. Louhichi, M.B. Fonseca, S.J.C. Janssen, Ittersum, M.K, G. Stokstad, P. Zander
• Article: FSSIM, a bio-economic farm model for simulating the response of EU farming systems to agricultural and environmental policies

  K. Louhichi, A. Kanellopoulos, S.J.C. Janssen, G. Flichman, M. Blanco, H. Hengsdijk, T. Heckelei, P. Berentsen, A.G.J.M. Oude Lansink, Ittersum, M.K
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  ABSTRACT: The disciplinary nature of most existing farm models as well as the issue specific orientation of most of the studies in agricultural systems research are main reasons for the limited use and re-use of bio-economic modelling for the ex-ante integrated assessment of policy decisions. The objective of this article is to present a bio-economic farm model that is generic and re-usable for different bio-physical and socio-economic contexts, facilitating the linking of micro and macro analysis or to provide detailed analysis of farming systems in a specific region. Model use is illustrated in this paper with an analysis of the impacts of the CAP reform of 2003 for arable and livestock farms in a context of market liberalization. Results from the application of the model to representative farms in Flevoland (the Netherlands) and Midi-Pyrenees (France) shows that CAP reform 2003 under market liberalization will cause substantial substitution of root crops and durum wheat by vegetables and oilseed crops. Much of the set-aside area will be put into production intensifying the existing farming systems. Abolishment of the milk quota system will cause an increase of the average herd size. The average total gross margin of farm types in Flevoland decreases while the average total gross margin of farms in Midi-Pyrenees increases. The results show that the model can simulate arable and livestock farm types of two regions different from a bio-physical and socio-economic point of view and it can deal with a variety of policy instruments. The examples show that the model can be (re-)used as a basis for future research and as a comprehensive tool for future policy analysis
  Agricultural Systems 103 (2010) 8.
• Article: Using the SEAMLESS Integrated Framework for exante assessment of trade policies

  I. Bezlepkina, M.H. Kuiper, S.J.C. Janssen, M.J.R. Knapen, A. Kanellopoulos, F.M. Brouwer, J.J.F. Wien, J. Wolf, Ittersum, M.K
  Towards effective food chains; models and apllications.
• Article: Assessing farmer behaviour as affected by policy and technological innovations: bio-economic farm models

  S.J.C. Janssen, Ittersum, M.K
• Source

  Available from: athanasiadis.info

  Article: Semantic mediation for environmental model components integration

  I.N. Athanasiadis, S.J.C. Janssen
  Information Technologies in Environmental Engineering 1 (2008) 1.
• Article: Architecture of SEAMLESS-IF as framework application for integrated modelling

  J.J.F. Wien, A.E. Rizzoli, M.J.R. Knapen, I.N. Athanasiadis, S.J.C. Janssen, L. Ruinelli, F. Villa, M. Svensson, P. Wallman, B. Jonsson
• Article: Generation of artifical crop rotation schemes as cyclic permutations

  I.N. Athanasiadis, A.E. Rizzoli, S.J.C. Janssen, Ittersum, M.K
• Article: A methodology for enhanced flexibility of integrated assessment in agriculture

  F. Ewert, Ittersum, M.K, I. Bezlepkina, O. Therond, E. Andersen, H. Belhouchette, C. Bockstaller, F.M. Brouwer, T. Heckelei, S.J.C. Janssen, R. Knapen, M. Kuiper, K. Louhichi, J.A. Olsson, N. Turpin, J. Wery, J.E. Wien, J. Wolf
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  ABSTRACT: Agriculture is interrelated with the socio-economic and natural environment and faces increasingly the problem of managing its multiple functions in a sustainable way. Growing emphasis is on adequate policies that can support both agriculture and sustainable development. Integrated Assessment and Modelling (IAM) can provide insight into the potential impacts of policy changes. An increasing number of Integrated Assessment (IA) models are being developed, but these are mainly monolithic and are targeted to answer specific problems. Approaches that allow flexible IA for a range of issues and functions are scarce. Recently, a methodology for policy support in agriculture has been developed that attempts to overcome some of the limitations of earlier IA models. The proposed framework (SEAMLESS-IF) integrates relationships and processes across disciplines and scales and combines quantitative analysis with qualitative judgments and experiences. It builds on the concept of systems analysis and attempts to enable flexible coupling of models and tools. The present paper aims to describe progress in improving flexibility of IAM achieved with the methodology developed for SEAMLESS-IF. A brief literature review identifying limitations in the flexibility of IAM is followed by a description of the progress achieved with SEAMLESS-IF. Two example applications are used to illustrate relevant capabilities of SEAMLESS-IF. The examples refer to (i) the impacts on European agriculture of changes in world trade regulations and (ii) regional impacts of the EU Nitrates Directive in combination with agro-management changes. We show that improving the flexibility of IAM requires flexibility in model linking but also a generic set up of all IA steps. This includes problem and scenario definition, the selection and specification of indicators and the indicator framework, the structuring of the database, and the visualization of results. Very important is the flexibility to integrate, select and link models, data and indicators depending on the application. Technical coupling and reusability of model components is greatly improved through adequate software architecture (SEAMLESS-IF uses OpenMI). The use of ontology strongly supports conceptual consistency of model linkages. However, the scientific basis for linking models across disciplines and scales is still weak and requires specific attention in future research. We conclude that the proposed framework significantly advances flexibility in IAM and that it is a good basis to further improve integrated modelling for policy impact assessment in agriculture
  Environmental Science and Policy 12 (2009) 5.
• Article: Assessing farm innovations and responses to policies: a review of bio-economic farm models

  S.J.C. Janssen, Ittersum, M.K
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  ABSTRACT: Bio-economic farm models (BEFMs) are developed to enable assessment of policy changes and technological innovations, for specific categories of farming systems. A rapidly growing number of research projects is using these models and there is increasing interest for application. The paper critically reviews past publications and applications of BEFMs on their strengths and weaknesses in assessing technological innovation and policy changes for farmers and policy makers and highlights key issues that require more attention in the use and methodology of BEFMs. A BEFM is defined as a model that links formulations describing farmers¿ resource management decisions to formulations that represent current and alternative production possibilities in terms of required inputs to achieve certain outputs, both yield and environmental effects. Mechanistic BEFMs are based on available theory and knowledge of farm processes and these were the focus of our study. Forty-eight applications of mechanistic BEFMs were reviewed as to their incorporation of farmer decision making and agricultural activities, comprehensiveness, model evaluation, and transferability. A clear description of end-use of the BEFM, agricultural activities, model equations and model evaluation are identified as good practices and a research agenda is proposed including the following issues: 1. development of a thorough and consistent procedure for model evaluation; 2. better understanding and modelling of farmer decision making and possible effects of the social milieu; 3. inclusion of several economic and environmental aspects of farming including multifunctionality and 4. development of a generic, modular and easily transferable BEFM.
  Agricultural Systems 94 (2007) 3.
• Source

  Available from: psu.edu

  Article: Translating disciplinary knowledge: model coupling through ontologies

  S.J.C. Janssen, I. Bezlepkina, I. Perez, I.N. Athanasiadis
• Source

  Available from: Andrea-Emilio Rizzoli

  Article: Semantic mediation of an integrated assessment tool for agicultural systems

  S.J.C. Janssen, I.N. Athanasiadis, E. Andersen, A.E. Rizzoli, J.J.F. Wien, Ittersum, M.K
• Source

  Available from: P.J.F.M. Verweij

  Article: Using Ontology to Harmonize Knowledge Concepts in Data and Models

  J.J.F. Wien, M.J.R. Knapen, S.J.C. Janssen, P.J.F.M. Verweij, I.N. Athanasiadis, H. Li, A.E. Rizzoli, F. Villa
• Article: Farming Systems SIMulator: First generic bio-economic farm model

  S.J.C. Janssen, K. Louhichi, A. Kanellopoulos, P. Zander, G. Flichman, H. Hengsdijk, Li Hongtao, T. Heckelei, G. Stokstad, N. Borkowski, J.M. Hecker, A.G.J.M. Oude Lansink, M. Blanco, E.C. Meuter, Ittersum, M.K
• Article: Assessing economic, social and environmental processes in agriculture with a computerized framework for the EU (SEAMLESS-IF)

  I. Bezlepkina, Ittersum, M.K, F. Ewert, J. Alkan Olsson, E. Andersen, F. Brouwer, M. Donatelli, G. Flichman, S.J.C. Janssen, T. Heckelei, L. Olsson, A. Oude Lansink, A. Rizzoli, J. Wery, J.E. Wien, J. Wolf