eprintid: 26821
rev_number: 8
eprint_status: archive
userid: 19147
dir: disk0/00/02/68/21
datestamp: 2018-12-07 14:37:03
lastmod: 2021-04-02 15:58:32
status_changed: 2018-12-07 15:20:21
type: article
metadata_visibility: show
creators_name: Ravat, Franck
creators_name: Song, Jiefu
creators_idrefppn: 127663711
title: A Unified Approach to Multisource Data Analyses
ispublished: pub
subjects: subjects_INFO
abstract: Classically, Data Warehouses (DWs) supports business analyses on data coming from the inside of an organization. Nevertheless, Lined Open Data (LOD) might sensibly complete these business analyses by providing complementary perspectives during a decision-making pro-cess. In this paper, we propose a conceptual modeling solution, named Unified Cube, which blends together multidimensional data from DWs and LOD datasets without materializing them in a stationary repository. We complete the conceptual modeling with an implementation frame-work which manages the relations between a Unified Cube and multiple data sources at both schema and instance levels. We also propose an analysis processing process which queries different sources in a transparent way to decision-makers. The practical value of our proposal is illustrated through real-world data and benchmarks.
date: 2018
date_type: published
publisher: Panstwowe Wydawnictwo Naukowe - IOS Press
id_number: 10.3233/FI-2018-1727
official_url: https://content.iospress.com/articles/fundamenta-informaticae/fi1727
faculty: info
divisions: IRIT
keywords: Data Warehouse
keywords: Linked Open Data
keywords: Conceptual Modeling
keywords: Multisource analyses
keywords: Experimental Assessments
language: en
has_fulltext: FALSE
view_date_year: 2018
full_text_status: none
publication: Fundamenta Informaticae
volume: vol. 162
number: n° 4
pagerange: 311-359
refereed: TRUE
issn: 1875-8681
oai_identifier: BibTeX_Ra2018.7
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citation:   Ravat, Franck <https://www.idref.fr/127663711> and Song, Jiefu  (2018) A Unified Approach to Multisource Data Analyses.    Fundamenta Informaticae, vol. 162 (n° 4).  pp. 311-359.