Data warehouse; Business Intelligence; OLAP; SOLAP; GIS; Social economy; Entrepôt de données; Informatique décisionnelle; SIG; Economie sociale
Abstract :
[en] Due to their multiple sources and structures, big spatial data require adapted tools to be efficiently collected, summarized and analyzed. For this purpose, data are archived in data warehouses and explored by spatial online analytical processing (SOLAP) through dynamic maps, charts and tables. Data are thus converted in data cubes characterized by a multidimensional structure on which exploration is based. However, multiple sources often lead to several data cubes defined by heterogeneous dimensions. In particular, dimensions definition can change depending on analyzed scale, territory and time. In order to consider these three issues specific to geographic analysis, this research proposes an original data cube metamodel defined in unified modeling language (UML). Based on concepts like common dimension levels and metadimensions, the metamodel can instantiate constellations of heterogeneous data cubes allowing SOLAP to perform multiscale, multi-territory and time analysis. Afterwards, the metamodel is implemented in a relational data warehouse and validated by an operational tool designed for a social economy case study. This tool, called “Racines”, gathers and compares multidimensional data about social economy business in Belgium and France through interactive cross-border maps, charts and reports. Thanks to the metamodel, users remain independent from IT specialists regarding data exploration and integration.
Research Center/Unit :
Sphères - SPHERES
Disciplines :
Computer science Human geography & demography
Author, co-author :
Kasprzyk, Jean-Paul ; Université de Liège - ULiège > Département de géographie > Serv. d'étude en géographie éco. fond. et appliquée (Segefa)
Devillet, Guénaël ; Université de Liège - ULiège > Département de géographie > Serv. d'étude en géographie éco. fond. et appliquée (Segefa)
Language :
English
Title :
A Data Cube Metamodel for Geographic Analysis Involving Heterogeneous Dimensions
Alternative titles :
[fr] Un métamodèle de cube de données pour l'analyse géographique impliquant des dimensions hétérogènes
Publication date :
17 February 2021
Journal title :
ISPRS International Journal of Geo-Information
eISSN :
2220-9964
Publisher :
MDPI AG, Basel, Switzerland
Special issue title :
Special issue "GIS Software and Engineering for Big Data"
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