Towards The Use of Probabilistic Spatial Relation Databases in Business Process Modeling

Towards The Use of Probabilistic Spatial Relation Databases in Business Process Modeling

Haizhou Li, François Pinet, Farouk Toumani
Copyright: © 2015 |Pages: 13
DOI: 10.4018/IJAEIS.2015070104
OnDemand:
(Individual Articles)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

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.
Article Preview
Top

2. Probabilistic Spatial Relations

Spatial relations can provide information on the layout of spatial objects (Freeman, 1975). As shown in (Egenhofer & Herring, 1990), there are different types of spatial relations. For example, topological relations are invariant under topological transformations. Metric information is provided by distance relations. Partial and total orders can be also modeled by spatial objects (“in the front of”, “behind”, etc.). Numerous spatial relations have been defined between different forms of spatial objects.

Probabilistic spatial relations can be defined between objects. This type of relations is associated to probability. In other words, we are able to assign probabilities on the different spatial relations. We present below three examples to illustrate this concept.

Complete Article List

Search this Journal:
Reset
Volume 15: 1 Issue (2024): Forthcoming, Available for Pre-Order
Volume 14: 1 Issue (2023)
Volume 13: 2 Issues (2022): 1 Released, 1 Forthcoming
Volume 12: 4 Issues (2021)
Volume 11: 4 Issues (2020)
Volume 10: 4 Issues (2019)
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 2 Issues (2012)
Volume 2: 2 Issues (2011)
Volume 1: 2 Issues (2010)
View Complete Journal Contents Listing