6533b860fe1ef96bd12c3a82

RESEARCH PRODUCT

Dimension enrichment with factual data during the design of multidimensional models: application to bird biodiversity

Lucile SautotBruno FaivreLudovic JournauxSandro Bimonte

subject

Multidimensional design[SDE] Environmental SciencesComputer science0102 computer and information sciences02 engineering and technologycomputer.software_genre01 natural sciencesData warehouseSchema (psychology)0202 electrical engineering electronic engineering information engineeringDesign methodsData miningConstellation[ SDE.BE ] Environmental Sciences/Biodiversity and Ecology[STAT.AP]Statistics [stat]/Applications [stat.AP]OLAPOnline analytical processing[ STAT.AP ] Statistics [stat]/Applications [stat.AP]Functional requirementData warehouse010201 computation theory & mathematics[SDE]Environmental Sciences020201 artificial intelligence & image processingData miningMultidimensional design[SDE.BE]Environmental Sciences/Biodiversity and Ecologycomputer

description

20 pages; International audience; Data warehouses (DW) and OLAP systems are technologies allowing the on-line analysis of huge volume of data according to decision-makers’ needs. Designing DW involves taking into account functional requirements and data sources (mixed design methodology) [1]. But, for complex applications, existing automatic design methodologies seem inefficient. In some cases, decision-makers need querying, as a dimension, data which have been defined as facts by actual automatic mixed approachs. Therefore, in this paper, we offer a new mixed refinement methodology relevant to constellation multidimensional schema. The proposed methodolgy allows to decision-makers to enrich a dimension with factual data. In order to validate our theoretical proposals, we have implemented an enrichment tool and we have tested it on a real case study from bird biodiversity.

yearjournalcountryeditionlanguage
2015-04-27
https://hal.inrae.fr/hal-02602516