Résumé
Nowadays, data on wastewater networks covering the same geographical territory areavailable from different sources. The fusion of multi-source spatial data provides a new andricher dataset that can serve several purposes such as quality improvement, decision making,or delivery of new services. It has given rise to several research works focused on thevisualization, analysis, and fusion of spatial databases. However, the original data is oftenimperfect: imprecise, uncertain, vague, incomplete, etc. Therefore, it is essential to useformalisms allowing the modeling of imperfections and to propose adapted fusionmechanisms.In this work, we aim to handle data imperfections in a generic way. We first propose acategorization, according to several dimensions, of data imperfections encountered whenfusing multi-source spatial data. We then propose to model these imperfections according tothe formalism of the belief theory. We consider our conducted experiments that allowed us to match nodes and edges in the different cases of data imperfection, as promising.