Towards a semantic framework for exploiting heterogeneous environmental data

Abstract

This paper presents the Environment and landscape geo-knowledge (GEMINAT) project which aims to build an infrastructure favouring the cross-analysis of spatio-temporal heterogeneous data sources recorded at the Chizé environmental observatory since 1994. From a case study, we summarise the difficulties encountered by biologists and ecologists when maintaining and analysing collected environmental data, essentially the spatial organisation of the landscape, crop rotation, and wildlife data. We show how a framework which uses a spatiotemporal ontology as a semantic mediator can solve challenges related to the analysis and maintenance of these heterogeneous data.

A model-driven methodology for integrating heterogeneous 3D geospatial urban entities

“…Solutions to solve geospatial data integration problem, i.e, combining data from different sources to provide users a unified view of the data (Tran et al, 2016), can be classified into five categories (Fosu et al, 2015): conversion (Stouffs et al, 2018;Chen et al, 2018;Donkers, 2013), creation of a unified data model to represent all objects of multiple data models (El-Mekawy et al, 2012;Yan et al, 2021;Kumar et al), data integration using semantic web and linked data (Karan et al, 2016;Hor et al, 2016;Huang et al, 2020;Pauwels et al;Radulovic et al). The last category is integration for web visualization in a 3D geospatial context (La Guardia et al;Gaillard et al, 2015;Colin et al, 2022).…”

“…Our objective is to provide users with integrated and navigable views of available representation of urban objects through a data integration process (Tran et al, 2016). This process must support the different navigation needs or use cases.…”