Sandro Bimonte

Dr. Sandro Bimonte

TSCF, INRAE, 63178 Aubière, France

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2015 in Computer Standards & Interfaces
Verified
Journal Article
Closed access
KBKamal Boulil
Kamal Boulil
Sandro BimonteSandro Bimonte
Sandro Bimonte
FPFrançois PINET
François PINET

1 November 2014 in Ecological Informatics
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Journal Article
Open access
KBKamal Boulil
Kamal Boulil
FBFlorence Le Ber
Florence Le Ber
Sandro BimonteSandro Bimonte
Sandro Bimonte
CGCorinne Grac
Corinne Grac
FCFlavie Cernesson
Flavie Cernesson
International audienceThis paper presents the application of Data Warehouse (DW) and On-Line Analytical Processing (OLAP) technologies to the field of water quality assessment. The European Water Framework Directive (DCE, 2000) underlined the necessity of having operational tools to help in the interpretation of the complex and abundant information regarding running waters and their functioning. Several studies have exemplified the interest in DWs for integrating large volumes of data and in OLAP tools for data exploration and analysis. Based on free software tools, we propose an extensible relational OLAP system for the analysis of physicochemical and hydrobiological watercourse data. This system includes: (i) two data cubes; (ii) an Extract, Transform and Load (ETL) tool for data integration; and (iii) tools for OLAP exploration. Many examples of OLAP analysis (thematic, temporal, spatiotemporal, and multiscale) are provided. We have extended an existing framework with complex aggregate functions that are used to define complex analysis indicators. Additional analysis dimensions are also introduced to allow their calculation and also for purposes of rendering information. Finally, we propose two strategies to address the problem of summarizing heterogeneous measurement units by: (i) transforming source data at the ETL tier, and (ii) introducing an additional analysis dimension at the OLAP server tier

11 April 2020 in Requirements Engineering
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Journal Article
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Sandro BimonteSandro Bimonte
Sandro Bimonte
LALeandro Antonelli
Leandro Antonelli
SRStefano Rizzi
Stefano Rizzi

28 January 2022 in Data & Knowledge Engineering
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Journal Article
Closed access
JPJulian Eduardo Plazas
Julian Eduardo Plazas
Sandro BimonteSandro Bimonte
Sandro Bimonte
MSMichel Schneider
Michel Schneider
CVChristophe De Vaulx
Christophe De Vaulx
PBPietro Battistoni
Pietro Battistoni
JCJuan Carlos Corrales
Juan Carlos Corrales

13 August 2020 in IEEE Internet of Things Journal
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Journal Article
Closed access
JPJulian Eduardo Plazas
Julian Eduardo Plazas
Sandro BimonteSandro Bimonte
Sandro Bimonte
CVChristophe De Vaulx
Christophe De Vaulx
MSMichel Schneider
Michel Schneider
QNQuang-Duy NGUYEN
Quang-Duy NGUYEN
JCJuan Carlos Corrales
Juan Carlos Corrales
In the context of Industry 4.0, the analysis of Internet of Things (IoT) data with Business Intelligence (BI) technologies has acquired high relevance. However, designing and implementing IoT-based BI applications is hard for several reasons. Therefore, we propose a novel conceptual data model based on UML Profiles and Model Driven Architecture (MDA) for modelling and implementing IoT-based BI applications. Our approach provides highly readable data models of IoT, which are also compatible with traditional BI data models. Furthermore, it could help in the implementation process of the IoT subsystem through automatic code generation.

14 October 2022 in Cluster Computing
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Journal Article
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GAGeraldine André
Geraldine André
BBBruno Bachelet
Bruno Bachelet
PBPietro Battistoni
Pietro Battistoni
ABAmina Belhassena
Amina Belhassena
Sandro BimonteSandro Bimonte
Sandro Bimonte
RWRobert Wrembel
Robert Wrembel