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Towards The Use of Probabilistic Spatial Relation Databases in Business Process Modeling
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Author(s): Haizhou Li (LIMOS, Université Blaise Pascal, Aubière, France), François Pinet (Irstea Centre de Clermont-Ferrand, Aubière, France)and Farouk Toumani (LIMOS, Université Blaise Pascal, Aubière, France)
Copyright: 2015
Volume: 6
Issue: 3
Pages: 13
Source title:
International Journal of Agricultural and Environmental Information Systems (IJAEIS)
Editor(s)-in-Chief: Frederic Andres (National Institute of Informatics, Japan), Chutiporn Anutariya (Asian Institute of Technology, Thailand), Teeradaj Racharak (Japan Advanced Institute of Science and Technology, Japan)and Watanee Jearanaiwongkul (National institute of Informatics, Japan)
DOI: 10.4018/IJAEIS.2015070104
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Abstract
In this paper, the authors combine the methods of probabilistic databases, GIS (Geographical Information Systems) and business process modelling to evaluate the agricultural activities. The authors provide a technique to evaluate the risk of agricultural activities among the hydrological objects (lakes, rivers, etc.) and agricultural plots. The spatial relation is an important information needed in the evaluation processes. This type of information is usually uncertain and the available data are often not precise. Consequently, probabilistic database is used to capture the uncertainty of the spatial objects in order to estimate the level of possible water and soil contamination (by agricultural inputs). Probabilistic spatial relations provide information on the layout of spatial objects. Probabilities are stored in a probabilistic database. Probabilistic database is a finite number of complete databases that are assigned with a set of probabilities. Probabilistic data-aware business processes integrate the theory of probabilistic database with business processes modeling methods. This new formalism of business processes helps the experts to model the environmental risks in terms of probabilistic spatial relations.
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