IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v103y2010i7p463-477.html
   My bibliography  Save this article

Ontology-based simulation in agricultural systems modeling

Author

Listed:
  • Beck, Howard
  • Morgan, Kelly
  • Jung, Yunchul
  • Grunwald, Sabine
  • Kwon, Ho-young
  • Wu, Jin

Abstract

A methodology and applications of ontology-based simulation are presented. An environment for building simulations based on the Lyra ontology management system is described which includes web-based visual design tools for constructing models and automatically generating simulation code. The ontology is used for representing all equations and all symbols appearing in these equations that are needed to describe a model. The example applications presented are models of soil, water, and nutrient management in citrus and sugarcane. Results thus far show that the ontology-based approach has advantages for representing the model structure, equations, and symbols, that complex models can be described in this format, and that efficient simulation code can be generated automatically from the ontology definition of the model. Potential applications, not yet fully explored, include ability to automatically connect models and data sources, using the ontology to organize model bases containing many models and model components, and using ontology reasoners to search for models, automatically discover model similarities and differences, and generate model instances from general principles.

Suggested Citation

  • Beck, Howard & Morgan, Kelly & Jung, Yunchul & Grunwald, Sabine & Kwon, Ho-young & Wu, Jin, 2010. "Ontology-based simulation in agricultural systems modeling," Agricultural Systems, Elsevier, vol. 103(7), pages 463-477, September.
    • Handle: RePEc:eee:agisys:v:103:y:2010:i:7:p:463-477
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308-521X(10)00059-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kwon, Ho-Young & Grunwald, Sabine & Beck, Howard W. & Jung, Yunchul & Daroub, Samira H. & Lang, Timothy A. & Morgan, Kelly T., 2010. "Ontology-based simulation of water flow in organic soils applied to Florida sugarcane," Agricultural Water Management, Elsevier, vol. 97(1), pages 112-122, January.
    2. Jones, J. W. & Keating, B. A. & Porter, C. H., 2001. "Approaches to modular model development," Agricultural Systems, Elsevier, vol. 70(2-3), pages 421-443.
    3. van Ittersum, Martin K. & Ewert, Frank & Heckelei, Thomas & Wery, Jacques & Alkan Olsson, Johanna & Andersen, Erling & Bezlepkina, Irina & Brouwer, Floor & Donatelli, Marcello & Flichman, Guillermo & , 2008. "Integrated assessment of agricultural systems - A component-based framework for the European Union (SEAMLESS)," Agricultural Systems, Elsevier, vol. 96(1-3), pages 150-165, March.
    4. Moore, A.D. & Holzworth, D.P. & Herrmann, N.I. & Huth, N.I. & Robertson, M.J., 2007. "The Common Modelling Protocol: A hierarchical framework for simulation of agricultural and environmental systems," Agricultural Systems, Elsevier, vol. 95(1-3), pages 37-48, December.
    5. Caldwell, Robert M. & Fernandez, Anthony A. J., 1998. "A generic model of hierarchy for systems analysis and simulation," Agricultural Systems, Elsevier, vol. 57(2), pages 197-225, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Robert, Marion & Dury, Jérôme & Thomas, Alban & Therond, Olivier & Sekhar, Muddu & Badiger, Shrini & Ruiz, Laurent & Bergez, Jacques-Eric, 2016. "CMFDM: A methodology to guide the design of a conceptual model of farmers' decision-making processes," Agricultural Systems, Elsevier, vol. 148(C), pages 86-94.
    2. Bert, Federico E. & Podestá, Guillermo P. & Rovere, Santiago L. & Menéndez, Ángel N. & North, Michael & Tatara, Eric & Laciana, Carlos E. & Weber, Elke & Toranzo, Fernando Ruiz, 2011. "An agent based model to simulate structural and land use changes in agricultural systems of the argentine pampas," Ecological Modelling, Elsevier, vol. 222(19), pages 3486-3499.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Parsons, David & Nicholson, Charles F. & Blake, Robert W. & Ketterings, Quirine M. & Ramírez-Aviles, Luis & Fox, Danny G. & Tedeschi, Luis O. & Cherney, Jerome H., 2011. "Development and evaluation of an integrated simulation model for assessing smallholder crop-livestock production in Yucatán, Mexico," Agricultural Systems, Elsevier, vol. 104(1), pages 1-12, January.
    2. Adam, M. & Corbeels, M. & Leffelaar, P.A. & Van Keulen, H. & Wery, J. & Ewert, F., 2012. "Building crop models within different crop modelling frameworks," Agricultural Systems, Elsevier, vol. 113(C), pages 57-63.
    3. Kanter, David R. & Musumba, Mark & Wood, Sylvia L.R. & Palm, Cheryl & Antle, John & Balvanera, Patricia & Dale, Virginia H. & Havlik, Petr & Kline, Keith L. & Scholes, R.J. & Thornton, Philip & Titton, 2018. "Evaluating agricultural trade-offs in the age of sustainable development," Agricultural Systems, Elsevier, vol. 163(C), pages 73-88.
    4. Sadeeka L. Jayasinghe & Dean T. Thomas & Jonathan P. Anderson & Chao Chen & Ben C. T. Macdonald, 2023. "Global Application of Regenerative Agriculture: A Review of Definitions and Assessment Approaches," Sustainability, MDPI, vol. 15(22), pages 1-49, November.
    5. Ephrem Habyarimana & Faheem S Baloch, 2021. "Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
    6. Schreefel, L. & de Boer, I.J.M. & Timler, C.J. & Groot, J.C.J. & Zwetsloot, M.J. & Creamer, R.E. & Schrijver, A. Pas & van Zanten, H.H.E. & Schulte, R.P.O., 2022. "How to make regenerative practices work on the farm: A modelling framework," Agricultural Systems, Elsevier, vol. 198(C).
    7. Viaggi, Davide & Raggi, Meri & Gomez y Paloma, Sergio, 2011. "Farm-household investment behaviour and the CAP decoupling: Methodological issues in assessing policy impacts," Journal of Policy Modeling, Elsevier, vol. 33(1), pages 127-145, January.
    8. Negm, L.M. & Youssef, M.A. & Skaggs, R.W. & Chescheir, G.M. & Jones, J., 2014. "DRAINMOD–DSSAT model for simulating hydrology, soil carbon and nitrogen dynamics, and crop growth for drained crop land," Agricultural Water Management, Elsevier, vol. 137(C), pages 30-45.
    9. Xiao, Rui & Yu, Xiaoyu & Xiang, Ting & Zhang, Zhonghao & Wang, Xue & Wu, Jianguo, 2021. "Exploring the coordination between physical space expansion and social space growth of China’s urban agglomerations based on hierarchical analysis," Land Use Policy, Elsevier, vol. 109(C).
    10. Gerrard, Catherine L. & Padel, Susanne & Simon, Moakes, 2012. "The use of Farm Business Survey data to compare the environmental performance of organic and conventional farms," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 2(1), pages 1-12, October.
    11. Gärtner, Dominique & Keller, Armin & Schulin, Rainer, 2013. "A simple regional downscaling approach for spatially distributing land use types for agricultural land," Agricultural Systems, Elsevier, vol. 120(C), pages 10-19.
    12. Dono, Gabriele & Cortignani, Raffaele & Giraldo, Luca & Doro, Luca & Roggero, Pier Paolo, 2014. "Assessing the awareness of climate change as a factor of adaptation in the agricultural sector," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173110, Italian Association of Agricultural and Applied Economics (AIEAA).
    13. Britz, Wolfgang & Ciaian, Pavel & Gocht, Alexander & Kanellopoulos, Argyris & Kremmydas, Dimitrios & Müller, Marc & Petsakos, Athanasios & Reidsma, Pytrik, 2021. "A design for a generic and modular bio-economic farm model," Agricultural Systems, Elsevier, vol. 191(C).
    14. Huber, Robert & Bakker, Martha & Balmann, Alfons & Berger, Thomas & Bithell, Mike & Brown, Calum & Grêt-Regamey, Adrienne & Xiong, Hang & Le, Quang Bao & Mack, Gabriele & Meyfroidt, Patrick & Millingt, 2018. "Representation of decision-making in European agricultural agent-based models," Agricultural Systems, Elsevier, vol. 167(C), pages 143-160.
    15. Valdivia, Roberto O. & Antle, John M. & Stoorvogel, Jetse J., 2012. "Coupling the Tradeoff Analysis Model with a market equilibrium model to analyze economic and environmental outcomes of agricultural production systems," Agricultural Systems, Elsevier, vol. 110(C), pages 17-29.
    16. Leng Liu & Bo Liu & Wei Song & Hao Yu, 2023. "The Relationship between Rural Sustainability and Land Use: A Bibliometric Review," Land, MDPI, vol. 12(8), pages 1-25, August.
    17. Louhichi, Kamel & Flichman, Guillermo & Blanco Fonseca, Maria, 2009. "A generic template for FSSIM," Reports 57463, Wageningen University, SEAMLESS: System for Environmental and Agricultural Modelling; Linking European Science and Society.
    18. Jeder, Houcine & Hamza, Emna Ben & Belhouchette, Hatem & Mzoughi, Aida, 2019. "Resilience of irrigated agricultural systems to climate change challenges in central-eastern region of Tunisia," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 0(Issue 1).
    19. Leah Grout & Simon Hales & Nigel French & Michael G. Baker, 2018. "A Review of Methods for Assessing the Environmental Health Impacts of an Agricultural System," IJERPH, MDPI, vol. 15(7), pages 1-27, June.
    20. Wolf, Joost & Kanellopoulos, Argyris & Kros, Johannes & Webber, Heidi & Zhao, Gang & Britz, Wolfgang & Reinds, Gert Jan & Ewert, Frank & de Vries, Wim, 2015. "Combined analysis of climate, technological and price changes on future arable farming systems in Europe," Agricultural Systems, Elsevier, vol. 140(C), pages 56-73.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agisys:v:103:y:2010:i:7:p:463-477. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.