Title: F-perceptory: an approach for handling fuzziness of spatiotemporal data in geographical databases
Authors: Asma Zoghlami; Cyril De Runz; Herman Akdag
Addresses: LIASD, University of Paris 8, 2, Rue de la Liberté, 93526 Saint-Denis Cedex, France ' CReSTIC, University of Reims Champagne-Ardenne, Chemin des Rouliers CS30012, 51687 Reims Cedex 2, France ' LIASD, University of Paris 8, 2, Rue de la Liberté, 93526 Saint-Denis Cedex, France
Abstract: In the literature, several studies have focused on introducing fuzzy extensions to the relational and/or object database models in order to store the imprecision. Indeed, on one hand, fuzzy EER and fuzzy UML are both applied for fuzzy object-oriented database modelling. On the other hand, Fuzzy ER is adapted for fuzzy relational database models. All these previous fuzzy conceptual modelling methods are not adapted to fuzzy spatiotemporal data. In this paper, we propose an approach for modelling imprecise data in object and relational databases based on the representation of data using connected and normalised fuzzy sets stored via α-cuts. The approach is applied to geographical information systems in order to handle imprecise spatiotemporal data.
Keywords: imprecise data modelling; fuzzy sets; geographical information systems; GIS; spatiotemporal data; unified modelling language; UML; fuzziness; geographical databases; relational databases; object-oriented databases; data representations.
International Journal of Spatial, Temporal and Multimedia Information Systems, 2016 Vol.1 No.1, pp.30 - 62
Available online: 29 May 2016 *Full-text access for editors Access for subscribers Free access Comment on this article