Boulil Kamal

Irstea − Copain
9 avenue Blaise Pascal − CS 20085
63178 Aubière − France

Contact

I am a PhD student on spatial data warehouse constraint modeling at Irstea. I was born in 1982 in Tizi-Ouzou, Algeria. I received my master degree in Databases and Artificial Intelligence in 2009 (University of Burgundy, France) and my engineering degree in Information Systems in 2007 (National School of Computer Science, Algeria). My current research interests include spatial data warehouse modeling; constraint definition to control warehoused data quality, data aggregation quality and Spatial OLAP exploration process for better Spatial OLAP Analysis.

Publications

Journal Articles (11)

S. Bimonte, K. Boulil, F. Pinet
Cohérence logique dans les systèmes OLAP spatiaux : un état de l’art
International Journal of Geomatics and Spatial Analysis-Revue Internationale de Géomatique 26 (1), 2016
abs doi web bib

Les systèmes d'Entrepôts de Données et « OnLine Analytical Process » spatiaux (EDS et SOLAP) sont des technologies d'aide à la décision permettant l’agrégation et l'analyse multidimensionnelle de gros volumes de données spatiales. En réponse à des actions utilisateurs sur l'interface cliente (exploration), les systèmes SOLAP agrègent les données de l'EDS le long de différentes hiérarchies des dimensions pour calculer des indicateurs d'analyse à différents niveaux de détails. La qualité des indicateurs d'analyse dépend donc de trois facteurs : la qualité des données entreposées, la qualité des agrégations et la qualité de l’exploration des données. La qualité des données entreposées dépend de critères comme la précision, l'exhaustivité et la cohérence logique. La cohérence logique des données est généralement contrôlée par les contraintes d'intégrité qui définissent les conditions que les données doivent satisfaire. La qualité d'agrégation peut être ramenée à la cohérence logique entre les natures des éléments qui sont impliqués dans l'agrégation SOLAP (par ex., mesure, fonction d'agrégation). Cette cohérence d'agrégation est affectée par des problèmes structurels et de problèmes sémantiques. La qualité d'exploration dépend essentiellement de la consistance des requêtes utilisateur (par ex. quelles ont été les valeurs de température en URSS en 2010 ?). Dans cette article nous étendons la notion de cohérence logique des données aux deux autres composantes fondamentales des systèmes SOLAP, à savoir l'agrégation et la requête. Nous présentons un état de l'art et des travaux sur la définition des contraintes d’intégrité pour garantir la cohérence logique au niveau des trois composantes (données, agrégations, et requêtes), ainsi qu' une évaluation de ces travaux et de notre proposition par rapport à un ensemble de critères que nous avons définis. Cette évaluation montre que notre proposition satisfait tous les critères contrairement aux autres.
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@article{PUB00050619, author = {Bimonte, S. and Boulil, K. and Pinet, F.}, title = {Cohérence logique dans les systèmes OLAP spatiaux : un état de l’art}, journal = {International Journal of Geomatics and Spatial Analysis-Revue Internationale de Géomatique}, volume = {26}, number = {1}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00050619}, doi = {http://dx.doi.org/10.3166/RIG.26.97-131}, year = {2016}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; UNIVERSITE DE STRASBOURG FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA}, abstract = {Les systèmes d'Entrepôts de Données et « OnLine Analytical Process » spatiaux (EDS et SOLAP) sont des technologies d'aide à la décision permettant l’agrégation et l'analyse multidimensionnelle de gros volumes de données spatiales. En réponse à des actions utilisateurs sur l'interface cliente (exploration), les systèmes SOLAP agrègent les données de l'EDS le long de différentes hiérarchies des dimensions pour calculer des indicateurs d'analyse à différents niveaux de détails. La qualité des indicateurs d'analyse dépend donc de trois facteurs : la qualité des données entreposées, la qualité des agrégations et la qualité de l’exploration des données. La qualité des données entreposées dépend de critères comme la précision, l'exhaustivité et la cohérence logique. La cohérence logique des données est généralement contrôlée par les contraintes d'intégrité qui définissent les conditions que les données doivent satisfaire. La qualité d'agrégation peut être ramenée à la cohérence logique entre les natures des éléments qui sont impliqués dans l'agrégation SOLAP (par ex., mesure, fonction d'agrégation). Cette cohérence d'agrégation est affectée par des problèmes structurels et de problèmes sémantiques. La qualité d'exploration dépend essentiellement de la consistance des requêtes utilisateur (par ex. quelles ont été les valeurs de température en URSS en 2010 ?). Dans cette article nous étendons la notion de cohérence logique des données aux deux autres composantes fondamentales des systèmes SOLAP, à savoir l'agrégation et la requête. Nous présentons un état de l'art et des travaux sur la définition des contraintes d’intégrité pour garantir la cohérence logique au niveau des trois composantes (données, agrégations, et requêtes), ainsi qu' une évaluation de ces travaux et de notre proposition par rapport à un ensemble de critères que nous avons définis. Cette évaluation montre que notre proposition satisfait tous les critères contrairement aux autres.}, }
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S. Bimonte, K. Boulil, A. Braud, S. Bringay, F. Cernesson, X. Dolques, M. Fabrègue, C. Grac, N. Lalande, F. Le Ber, M. Teisseire
A decisional system for analysing water quality of watercourses
Ingenierie des Systemes d'Information 20 (3), 2015
abs doi web bib

This article describes a decisional system developed to allow the analysis of data about hydro-ecosystem functioning; there are numerous and various data, from several sources. The implemented system includes an integrated database, a datawarehouse for exploring data dimensions, and data mining tools for answering hydroecologists' questions. / Cet article décrit un système décisionnel développé pour permettre l'analyse de données sur le fonctionnement des écosystèmes; Il existe de nombreuses et diverses données provenant de plusieurs sources. Le système implanté comprend une base de données intégrée, un datawarehouse pour explorer les dimensions des données et des outils de data mining pour répondre aux questions des hydroécologues.
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@article{PUB00054282, author = {Bimonte, S. and Boulil, K. and Braud, A. and Bringay, S. and Cernesson, F. and Dolques, X. and Fabrègue, M. and Grac, C. and Lalande, N. and Le Ber, F. and Teisseire, M.}, title = {A decisional system for analysing water quality of watercourses}, journal = {Ingenierie des Systemes d'Information}, volume = {20}, number = {3}, pages = {143-167}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00054282 / https://www.scopus.com/inward/record.uri?eid=2-s2.0-84965133730&doi=10.3166%2fISI.20.3.143-167&partnerID=40&md5=1527e8545c46a9a5428db6983328664b}, doi = {http://dx.doi.org/10.3166/ISI.20.3.143-167}, year = {2015}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; LI UNIVERSITE DE TOURS FRA ; ICUBE UNIVERSITE DE STRASBOURG ENGEES CNRS FRA ; UNIVERSITE DE MONTPELLIER II UMR 5506 LIRMM MONTPELLIER FRA ; AGROPARISTECH UMR TETIS MONTPELLIER FRA ; ICUBE UNIVERSITE DE STRASBOURG ENGEES CNRS FRA ; ICUBE UNIVERSITE DE STRASBOURG ENGEES CNRS FRA ; LIVE UNIVERSITE DE STRASBOURG ENGEES CNRS FRA ; IRSTEA MONTPELLIER UMR TETIS FRA ; ICUBE UNIVERSITE DE STRASBOURG ENGEES CNRS FRA ; -}, abstract = {This article describes a decisional system developed to allow the analysis of data about hydro-ecosystem functioning; there are numerous and various data, from several sources. The implemented system includes an integrated database, a datawarehouse for exploring data dimensions, and data mining tools for answering hydroecologists' questions. / Cet article décrit un système décisionnel développé pour permettre l'analyse de données sur le fonctionnement des écosystèmes; Il existe de nombreuses et diverses données provenant de plusieurs sources. Le système implanté comprend une base de données intégrée, un datawarehouse pour explorer les dimensions des données et des outils de data mining pour répondre aux questions des hydroécologues.}, }
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S. Bimonte, K. Boulil, A. Braud, S. Bringay, F. Cernesson, X. Dolques, M. Fabregue, C. Grac, N. Lalande, F. Le Ber, M. Teisseire
Un système décisionnel pour l’analyse de la qualité des eaux de rivières
Ingénierie des Systèmes d'Information 20 (3), 2015
abs doi web bib

Cet article décrit un système décisionnel développé pour permettre l’analyse des données concernant le fonctionnement des hydro-écosystèmes ; ces données sont nombreuses, diverses et issues de sources variées. Le système mis en place comporte une base de données intégrée, un entrepôt permettant l’exploration des dimensions associées aux données, et des outils de fouille permettant de répondre aux questions des hydro-écologues
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@article{PUB00046020, author = {Bimonte, S. and Boulil, K. and Braud, A. and Bringay, S. and Cernesson, F. and Dolques, X. and Fabregue, M. and Grac, C. and Lalande, N. and Le Ber, F. and Teisseire, M.}, title = {Un système décisionnel pour l’analyse de la qualité des eaux de rivières}, title = {A decision-making system for the analysis of water quality of rivers}, journal = {Ingénierie des Systèmes d'Information}, volume = {20}, number = {3}, pages = { 143-167}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00046020 / http://isi.revuesonline.com/article.jsp?articleId=20889}, doi = {http://dx.doi.org/10.3166/isi.20.3.143-167 }, year = {2015}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; UNIVERSITE DE TOURS FRA ; UNIVERSITE DE STRASBOURG FRA ; UNIVERSITE DE MONTPELLIER II UMR 5506 LIRMM MONTPELLIER FRA ; IRSTEA MONTPELLIER UMR TETIS FRA ; UNIVERSITE DE STRASBOURG FRA ; UNIVERSITE DE STRASBOURG FRA ; UNIVERSITE DE STRASBOURG FRA ; IRSTEA MONTPELLIER UMR TETIS FRA ; UNIVERSITE DE STRASBOURG FRA ; IRSTEA MONTPELLIER UMR TETIS FRA}, abstract = {Cet article décrit un système décisionnel développé pour permettre l’analyse des données concernant le fonctionnement des hydro-écosystèmes ; ces données sont nombreuses, diverses et issues de sources variées. Le système mis en place comporte une base de données intégrée, un entrepôt permettant l’exploration des dimensions associées aux données, et des outils de fouille permettant de répondre aux questions des hydro-écologues}, }
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K. Boulil, S. Bimonte, F Pinet
Conceptual model for spatial data cubes: A UML profile and its automatic implementation
Computer Standards & Interfaces 38, 2015
abs doi web bib

The increasing availability of geo-referenced data has increased the need to enrich OLAP with spatial analysis, leading to the concept of Spatial OLAP (SOLAP). The conceptual modelling of spatial data cubes requires the definition of two kinds of metadata: (i) warehouse metadata that model data structures that maintain integrated data from multiple data sources and (ii) aggregation1 metadata that specify how the warehoused data should be aggregated to meet the analysis goals of decision makers. In this paper we provide a review of existing conceptual spatial data cube models. We highlight some limits of these models concerning the aggregation model design, and their implementation in existing CASE tools and SOLAP architectures. Firstly, we propose a new UML (Unified Modeling Language) profile for modelling complex Spatial Data Warehouses and aggregations. Our profile is implemented in the MagicDraw CASE tool. Secondly, we propose a tool for the automatic implementation of conceptual spatial data cube models, designed using our profile, in a SOLAP architecture. In particular, our solution allows: (i) generating different logical representations of the SDW (Spatial Data Warehouse) model (star schema and snow-flake schema) and (ii) implementing complex SOLAP analysis indicators using MDX (MultiDimensional eXpressions language).
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@article{PUB00046022, author = {Boulil, K. and Bimonte, S. and Pinet, F}, title = {Conceptual model for spatial data cubes: A UML profile and its automatic implementation}, title = {Modèle conceptuel de cubes de données spatiales : un profil UML et son application automatique}, journal = {Computer Standards & Interfaces}, volume = {38}, pages = {113-132}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00046022}, doi = {http://dx.doi.org/10.1016/j.csi.2014.06.004}, year = {2015}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA}, abstract = {The increasing availability of geo-referenced data has increased the need to enrich OLAP with spatial analysis, leading to the concept of Spatial OLAP (SOLAP). The conceptual modelling of spatial data cubes requires the definition of two kinds of metadata: (i) warehouse metadata that model data structures that maintain integrated data from multiple data sources and (ii) aggregation1 metadata that specify how the warehoused data should be aggregated to meet the analysis goals of decision makers. In this paper we provide a review of existing conceptual spatial data cube models. We highlight some limits of these models concerning the aggregation model design, and their implementation in existing CASE tools and SOLAP architectures. Firstly, we propose a new UML (Unified Modeling Language) profile for modelling complex Spatial Data Warehouses and aggregations. Our profile is implemented in the MagicDraw CASE tool. Secondly, we propose a tool for the automatic implementation of conceptual spatial data cube models, designed using our profile, in a SOLAP architecture. In particular, our solution allows: (i) generating different logical representations of the SDW (Spatial Data Warehouse) model (star schema and snow-flake schema) and (ii) implementing complex SOLAP analysis indicators using MDX (MultiDimensional eXpressions language).}, }
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S. Bimonte, K. Boulil, M. Pradel, G. André, J.P. Chanet
Analyse des indicateurs énergétiques des entreprises agricoles : une approche spatial OLAP
2014
abs doi web bib

Spatial data warehouses and Spatial OLAP systems are business solutions that can be used for environmental applications. Indeed, in order to better assess the impacts of human activities on the environment, many spatio-temporal data should be collected in order to calculate indicators at different levels of aggregation. Spatial OLAP tools are well adapted to analyze these indicators in a multi-dimensional way for identifying and implementing policies to improve practices in order to minimize impacts. In this study, we focus on farms energy consumption in order to identify the tasks and work environments that consume the most energy. We show how SOLAP tools can be used for the spatio-multidimensional analysis of these indicators, and the research issues related to agricultural data warehousing and analysis process.
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@article{PUB00050618, author = {Bimonte, S. and Boulil, K. and Pradel, M. and André, G. and Chanet, J.P.}, title = {Analyse des indicateurs énergétiques des entreprises agricoles : une approche spatial OLAP}, pages = {37-65}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00050618}, doi = {http://dx.doi.org/10.3166/rig.24.37-65}, year = {2014}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA}, abstract = {Spatial data warehouses and Spatial OLAP systems are business solutions that can be used for environmental applications. Indeed, in order to better assess the impacts of human activities on the environment, many spatio-temporal data should be collected in order to calculate indicators at different levels of aggregation. Spatial OLAP tools are well adapted to analyze these indicators in a multi-dimensional way for identifying and implementing policies to improve practices in order to minimize impacts. In this study, we focus on farms energy consumption in order to identify the tasks and work environments that consume the most energy. We show how SOLAP tools can be used for the spatio-multidimensional analysis of these indicators, and the research issues related to agricultural data warehousing and analysis process.}, }
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K. Boulil, F. Le Ber, S. Bimonte, C. Grac, F. Cernesson
Multidimensional modeling and analysis of large and complex watercourse data: An OLAP-based solution
Ecological Informatics 24, 2014
abs doi web bib

This 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.
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@article{PUB00041337, author = {Boulil, K. and Le Ber, F. and Bimonte, S. and Grac, C. and Cernesson, F.}, title = {Multidimensional modeling and analysis of large and complex watercourse data: An OLAP-based solution}, title = {Modelisation et analyse multidimensionnelle pour l'analyse des données des bassins versants}, journal = {Ecological Informatics}, volume = {24}, pages = {90-106}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00041337}, doi = {http://dx.doi.org/10.1016/j.ecoinf.2014.07.001}, year = {2014}, affiliation = {UNIVERSITE DE STRASBOURG FRA ; UNIVERSITE DE STRASBOURG FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; UNIVERSITE DE STRASBOURG FRA ; AGROPARISTECH UMR TETIS MONTPELLIER FRA}, abstract = {This 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.}, }
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K. Boulil, S. Bimonte, F. Pinet
Spatial OLAP integrity constraints: From UML-Based specification to automatic implementation: Application to energetic data in agriculture
Journal of Decision Systems 23 (4), 2014
abs doi web bib

Spatial OLAP systems are Business Intelligence technologies allowing efficient and interactive analysis of large spatial data cubes. In this type of systems the correctness of analysis depends on: The warehoused data quality, how aggregations are performed and how data cubes are explored. In this paper we study quality control techniques (based on integrity constraints) related to exploration of spatial data cubes. We extend our UML framework previously proposed with a UML profile allowing the conceptual design of several classes of exploration integrity constraints. We also propose a tool for their automatic implementation. We validate our proposal in the context of a real case study concerning the analysis of energetic farm energetic indicators.
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@article{PUB00040809, author = {Boulil, K. and Bimonte, S. and Pinet, F.}, title = {Spatial OLAP integrity constraints: From UML-Based specification to automatic implementation: Application to energetic data in agriculture}, title = {Contraintes d’intégrité SOLAP : du modèle UML à l’implémentation automatique}, journal = {Journal of Decision Systems}, volume = {23}, number = {4}, pages = {460-480}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00040809}, doi = {http://dx.doi.org/10.1080/12460125.2014.934120}, year = {2014}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA}, abstract = {Spatial OLAP systems are Business Intelligence technologies allowing efficient and interactive analysis of large spatial data cubes. In this type of systems the correctness of analysis depends on: The warehoused data quality, how aggregations are performed and how data cubes are explored. In this paper we study quality control techniques (based on integrity constraints) related to exploration of spatial data cubes. We extend our UML framework previously proposed with a UML profile allowing the conceptual design of several classes of exploration integrity constraints. We also propose a tool for their automatic implementation. We validate our proposal in the context of a real case study concerning the analysis of energetic farm energetic indicators.}, }
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K. Boulil, F. Pinet, S. Bimonte, N. Carluer, C. Lauvernet, B. Cheviron, A. Miralles, J.P. Chanet
Guaranteeing the quality of multidimensional analysis in data warehouses of simulation results: application to pesticide transfer data produced by the MACRO Model
Ecological Informatics 16, 2013
abs web bib

Currently, the vital impact of environmental pollution on economic, social and health dimensions has been recognized. The need for theoretical and implementation frameworks for the acquisition, modeling and analysis of environmental data as well as tools to conceive and validate scenarios is becoming increasingly important. For these reasons, different environmental simulation models have been developed. Researchers and stakeholders need efficient tools to store, display, compare and analyze data that are produced by simulation models. One common way to manage simulation results is to use text files; however, text files make it difficult to explore the data. Spreadsheet tools (e.g., OpenOffice, MS Excel) can help to display and analyze model results, but they are not suitable for very large volumes of information. Recently, some studies have shown the feasibility of using Data Warehouse (DW) and On-Line Analytical Processing (OLAP) technologies to store model results and to facilitate model visualization, analysis and comparisons. These technologies allow model users to easily produce graphical reports and charts. In this paper, we address the analysis of pesticide transfer simulation results by warehousing and OLAPing data, for which the data results from the MACRO simulation model. This model simulates hydrological transfers of pesticides at the plot scale. We demonstrate how the simulation results can be managed using DW technologies. We also demonstrate how the use of integrity constraints can improve OLAP analysis. These constraints are used to maintain the quality of the warehoused data as well as to maintain the aggregations and queries, which will lead to better analysis, conclusions and decisions.
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@article{PUB00038438, author = {Boulil, K. and Pinet, F. and Bimonte, S. and Carluer, N. and Lauvernet, C. and Cheviron, B. and Miralles, A. and Chanet, J.P.}, title = {Guaranteeing the quality of multidimensional analysis in data warehouses of simulation results: application to pesticide transfer data produced by the MACRO Model}, title = {Garantir la qualité de l'analyse multi-dimensionnelle dans les entrepôts de données de résultats de simulation : application aux données de transfert de pesticide produites par le modèle MACRO }, journal = {Ecological Informatics}, volume = {16}, pages = {41-52}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00038438 / http://www.sciencedirect.com/science/article/pii/S1574954113000307}, year = {2013}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA LYON UR MALY FRA ; IRSTEA LYON UR MALY FRA ; IRSTEA MONTPELLIER UR IRMO UMR G-EAU FRA ; IRSTEA MONTPELLIER UR LCMO UMR TETIS FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA}, abstract = {Currently, the vital impact of environmental pollution on economic, social and health dimensions has been recognized. The need for theoretical and implementation frameworks for the acquisition, modeling and analysis of environmental data as well as tools to conceive and validate scenarios is becoming increasingly important. For these reasons, different environmental simulation models have been developed. Researchers and stakeholders need efficient tools to store, display, compare and analyze data that are produced by simulation models. One common way to manage simulation results is to use text files; however, text files make it difficult to explore the data. Spreadsheet tools (e.g., OpenOffice, MS Excel) can help to display and analyze model results, but they are not suitable for very large volumes of information. Recently, some studies have shown the feasibility of using Data Warehouse (DW) and On-Line Analytical Processing (OLAP) technologies to store model results and to facilitate model visualization, analysis and comparisons. These technologies allow model users to easily produce graphical reports and charts. In this paper, we address the analysis of pesticide transfer simulation results by warehousing and OLAPing data, for which the data results from the MACRO simulation model. This model simulates hydrological transfers of pesticides at the plot scale. We demonstrate how the simulation results can be managed using DW technologies. We also demonstrate how the use of integrity constraints can improve OLAP analysis. These constraints are used to maintain the quality of the warehoused data as well as to maintain the aggregations and queries, which will lead to better analysis, conclusions and decisions.}, }
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K. Boulil, S. Bimonte, F. Pinet
Un modèle UML et des contraintes OCL pour les entrepôts de données spatiales : de la représentation conceptuelle à l'implémentation
Ingénierie des Systèmes d'Information 16 (6), 2011
abs doi web bib

Spatial Data Warehouses (SDW) and Spatial OLAP (SOLAP) systems represent an effec-tive solution to perform spatial analysis on geographical phenomena. However, the quality of such analysis heavily depends on the quality of stored data and how these data are explored: how the different indicators are computed (What aggregate functions are applied to summa-rize the measures and in what order these functions are applied?). In this context, a number of studies have been attempted to address the issues of data quality in SDW by using Integ-rity Constraints (IC). In this paper, motivated by the lack of Model Driven Architecture (MDA)-based implementations, we propose a conceptual framework based on two new clas-sifications to ease identification and implementation of SDW IC. Moreover, following an MDA approach, we propose the MDA-based modeling of most IC categories using the UML (Unified Modeling Language) and OCL (Object Constraint Language) standard languages; and show the automatic implementation of some IC classes using an MDA-based code gen-erator, called Spatial OCL2SQL. / Les Entrepôts de Données Spatiales (EDS) et les systèmes SOLAP représentent une solution efficace pour l'analyse spatiale de phénomènes géographiques. Cependant, la qualité de cette analyse dépend fortement de la qualité des données entreposées et de la manière dont l'exploration de ces données est réalisée : comment les différents indicateurs ou agrégats sont calculés ? (i.e. quels opérateurs d'agrégation sont appliqués aux différentes mesures ? Et dans quel ordre ils sont appliqués ?). Dans ce contexte, quelques travaux essaient de mieux maîtriser la qualité des informations dans les entrepôts de données (spatiales) par exemple par le biais de contraintes d'intégrité. Dans cet article, motivé par le manque d'implémentations basées sur une approche MDA (Model Driven Architecture), nous proposons un «framework» conceptuel basé sur deux nouvelles classifications pour faciliter l'identification et l'implémentation des contraintes d'EDS ; dans le cadre de l'approche MDA, nous proposons la modélisation et l'implémentation de la plupart des types de contraintes en utilisant les standards UML(Unified Modeling Language) et OCL (Object Constraint Language), et le générateur de code Spatial OCL2SQL.
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@article{PUB00031873, author = {Boulil, K. and Bimonte, S. and Pinet, F.}, title = {Un modèle UML et des contraintes OCL pour les entrepôts de données spatiales : de la représentation conceptuelle à l'implémentation }, title = {A UML Model and OCL constraints for spatial data warehouses: From the conceptual design to the implementation }, journal = {Ingénierie des Systèmes d'Information}, volume = {16}, number = {6}, pages = {11-39}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00031873}, doi = {http://dx.doi.org/doi:10.3166/isi.16.6.11-39 }, year = {2011}, affiliation = {CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA}, abstract = {Spatial Data Warehouses (SDW) and Spatial OLAP (SOLAP) systems represent an effec-tive solution to perform spatial analysis on geographical phenomena. However, the quality of such analysis heavily depends on the quality of stored data and how these data are explored: how the different indicators are computed (What aggregate functions are applied to summa-rize the measures and in what order these functions are applied?). In this context, a number of studies have been attempted to address the issues of data quality in SDW by using Integ-rity Constraints (IC). In this paper, motivated by the lack of Model Driven Architecture (MDA)-based implementations, we propose a conceptual framework based on two new clas-sifications to ease identification and implementation of SDW IC. Moreover, following an MDA approach, we propose the MDA-based modeling of most IC categories using the UML (Unified Modeling Language) and OCL (Object Constraint Language) standard languages; and show the automatic implementation of some IC classes using an MDA-based code gen-erator, called Spatial OCL2SQL. / Les Entrepôts de Données Spatiales (EDS) et les systèmes SOLAP représentent une solution efficace pour l'analyse spatiale de phénomènes géographiques. Cependant, la qualité de cette analyse dépend fortement de la qualité des données entreposées et de la manière dont l'exploration de ces données est réalisée : comment les différents indicateurs ou agrégats sont calculés ? (i.e. quels opérateurs d'agrégation sont appliqués aux différentes mesures ? Et dans quel ordre ils sont appliqués ?). Dans ce contexte, quelques travaux essaient de mieux maîtriser la qualité des informations dans les entrepôts de données (spatiales) par exemple par le biais de contraintes d'intégrité. Dans cet article, motivé par le manque d'implémentations basées sur une approche MDA (Model Driven Architecture), nous proposons un «framework» conceptuel basé sur deux nouvelles classifications pour faciliter l'identification et l'implémentation des contraintes d'EDS ; dans le cadre de l'approche MDA, nous proposons la modélisation et l'implémentation de la plupart des types de contraintes en utilisant les standards UML(Unified Modeling Language) et OCL (Object Constraint Language), et le générateur de code Spatial OCL2SQL.}, }
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F. Pinet, M.A. Kang, K. Boulil, S. Bimonte, G. De Sousa, C. Roussey, M. Schneider, J.P. Chanet
Using OCL to model constraints in data warehouses
International Journal of Technology Diffusion 2 (3), 2011
abs doi web bib

Recent research works propose to use the Object-Oriented (OO) approach such as UML to model data warehouses. First, the present paper overviews these recent OO techniques. They aim to describe the facts and the different analysis dimensions of the data. Second, we will propose a tutorial of the Object Constraint Language (OCL) and we will show how this language can be used to specify constraints in OO-based models of data warehouse. Up to now, OCL has been only applied to describe constraints in software applications and transactional databases. So, we demonstrate in this paper how to use OCL to represent the different types of data warehouse constraints. Our paper is addressed to researchers working in the fields of business intelligence and decision support systems, who wish to learn about the major possibilities that OCL offer in the context of data warehouse, and to find citations that will allow them to learn about this formalism in greater detail. We also provide general information about the possible types of implementation of multi-dimensional models and their constraints.
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@article{PUB00034693, author = {Pinet, F. and Kang, M.A. and Boulil, K. and Bimonte, S. and De Sousa, G. and Roussey, C. and Schneider, M. and Chanet, J.P.}, title = {Using OCL to model constraints in data warehouses}, title = {Utilisation d'OCL pour modéliser les contraintes dans les entrepôts de données}, journal = {International Journal of Technology Diffusion}, volume = {2}, number = {3}, pages = {11}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00034693}, doi = {http://dx.doi.org/10.4018/jtd.2011070104}, year = {2011}, affiliation = {CEMAGREF CLERMONT FERRAND UR TSCF FRA ; UNIVERSITE DE CLERMONT FERRAND LIMOS ISIMA AUBIERE FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA ; UNIVERSITE DE CLERMONT FERRAND LIMOS ISIMA AUBIERE FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA}, abstract = {Recent research works propose to use the Object-Oriented (OO) approach such as UML to model data warehouses. First, the present paper overviews these recent OO techniques. They aim to describe the facts and the different analysis dimensions of the data. Second, we will propose a tutorial of the Object Constraint Language (OCL) and we will show how this language can be used to specify constraints in OO-based models of data warehouse. Up to now, OCL has been only applied to describe constraints in software applications and transactional databases. So, we demonstrate in this paper how to use OCL to represent the different types of data warehouse constraints. Our paper is addressed to researchers working in the fields of business intelligence and decision support systems, who wish to learn about the major possibilities that OCL offer in the context of data warehouse, and to find citations that will allow them to learn about this formalism in greater detail. We also provide general information about the possible types of implementation of multi-dimensional models and their constraints.}, }
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K. Boulil, S. Bimonte, H. Mahboubi, F. Pinet
Vers la définition des contraintes d'intégrité d'entrepôts de données spatiales avec OCL
Revue des Nouvelles Technologies de l'Information B6, 2010
abs web bib

Les Entrepôts de Données Spatiales (EDS) et les systèmes SOLAP représentent une solution efficace pour l'analyse spatiale de phénomènes géographiques. Cependant, la qualité de cette analyse dépend fortement de la qualité des données stockées. Dans ce contexte, quelques travaux se sont intéressés à la définition et la spécification des contraintes d'intégrité spécifiques aux EDS. Dans cet article, motivé par le manque d'implémentation basée sur une approche MDA (Model Driven Approach), nous proposons deux classifications de contraintes d'EDS ainsi que leurs spécifications et implémentations en utilisant le standard OMG OCL (Object Constraint Language).
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@article{PUB00029286, author = {Boulil, K. and Bimonte, S. and Mahboubi, H. and Pinet, F.}, title = {Vers la définition des contraintes d'intégrité d'entrepôts de données spatiales avec OCL}, title = {Towards the definition of integrity constraints of spatial data warehouses with OCL}, journal = {Revue des Nouvelles Technologies de l'Information}, volume = {B6}, pages = {121-136}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00029286 / http://www.cepadues.com/docs/942/RNTI%20B-6%20EDA10.pdf}, year = {2010}, affiliation = {CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA}, abstract = {Les Entrepôts de Données Spatiales (EDS) et les systèmes SOLAP représentent une solution efficace pour l'analyse spatiale de phénomènes géographiques. Cependant, la qualité de cette analyse dépend fortement de la qualité des données stockées. Dans ce contexte, quelques travaux se sont intéressés à la définition et la spécification des contraintes d'intégrité spécifiques aux EDS. Dans cet article, motivé par le manque d'implémentation basée sur une approche MDA (Model Driven Approach), nous proposons deux classifications de contraintes d'EDS ainsi que leurs spécifications et implémentations en utilisant le standard OMG OCL (Object Constraint Language).}, }
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In Proceedings (5)

S. Bimonte, K. Boulil, F. Pinet, M.A. Kang
Design of complex spatio-multidimensional models with the ICSOLAP UML Profile: An implementation in MagicDraw
15th International Conference on Enterprise Information Systems (ICEIS), 04/07/2013-07/07/2013, Angers, FRA (p. 310-315), 2013
abs web bib

Spatial Data Warehouse and SOLAP systems allow analyzing huge volume of georeferenced data. SOLAP applications are usually complex needing advanced static and dynamic modelling properties. In particular, SOLAP applications require: multi-granular measures and complex aggregations based on aggregate functions depending on dimensions, hierarchies and levels. In this demo paper, motivated by the lack of conceptual spatio-multidimensional models based on standard languages and supporting such complex modelling requirements, we present a new UML profile for complex spatial data cubes. We implement our profile in the commercial CASE tool called MagicDraw. Using a real environmental case study, we show the theoretical and technical effectiveness of our proposal.
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@inproceedings{PUB00040429, author = {Bimonte, S. and Boulil, K. and Pinet, F. and Kang, M.A.}, title = {Design of complex spatio-multidimensional models with the ICSOLAP UML Profile: An implementation in MagicDraw }, bookTitle = {15th International Conference on Enterprise Information Systems (ICEIS), 04/07/2013-07/07/2013, Angers, FRA}, pages = {310-315}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00040429}, year = {2013}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; UNIVERSITE BLAISE PASCAL LIMOS CLERMONT FERRAND FRA}, abstract = {Spatial Data Warehouse and SOLAP systems allow analyzing huge volume of georeferenced data. SOLAP applications are usually complex needing advanced static and dynamic modelling properties. In particular, SOLAP applications require: multi-granular measures and complex aggregations based on aggregate functions depending on dimensions, hierarchies and levels. In this demo paper, motivated by the lack of conceptual spatio-multidimensional models based on standard languages and supporting such complex modelling requirements, we present a new UML profile for complex spatial data cubes. We implement our profile in the commercial CASE tool called MagicDraw. Using a real environmental case study, we show the theoretical and technical effectiveness of our proposal. }, }
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S. Bimonte, K. Boulil, J.P. Chanet, M. Pradel
Definition and analysis of new agricultural farm energetic indicators using spatial OLAP
International Conference on Geographical Analysis, Urban Modeling, Spatial Statistics, 18/05/2012-20/05/2012, Salvador de Bahia, BRA (p. 14), 2012
abs web bib

Agricultural energy consumption is an important environmental and social issue. Several diagnoses have been proposed to define indicators for analyzing energy consumption at large scale of agricultural farm activities (year, farm, family of production, etc.). However, to define ad-hoc environmental energetic policies to better monitor and control energy consumption, new indicators at a most detailed scale are needed. Moreover, by defining detailed scale indicators, large quantities of geo-referenced data need to be collected to feed these energetic diagnoses. This huge volume of data represents another important limitation of systems that implement these diagnoses because they are usually based on classical data storage systems (such as spreadsheet tools and Database Management Systems). These systems do not allow for interactive analysis at different granularities/scales of huge volumes of data and do not provide any cartographic representation. By contrast, Spatial OLAP (SOLAP) and spatial data warehouse (SDW) systems allow for the analysis of huge volumes of geo-referenced data by providing aggregated numerical values visualized by means of interactive tabular, graphical and cartographic displays. Thus, in this paper, we (i) propose new appropriate indicators to analyze agricultural farm energy performance at a detailed scale and (ii) show how SDW and SOLAP technologies can be used to represent, store and analyze these indicators by simultaneously producing expressive reports.
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@inproceedings{PUB00035350, author = {Bimonte, S. and Boulil, K. and Chanet, J.P. and Pradel, M.}, title = {Definition and analysis of new agricultural farm energetic indicators using spatial OLAP}, title = {Définition et analyse des nouveaux indicateurs énergétiques avec le spatial OLAP}, bookTitle = {International Conference on Geographical Analysis, Urban Modeling, Spatial Statistics, 18/05/2012-20/05/2012, Salvador de Bahia, BRA}, pages = {14}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00035350}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA}, abstract = {Agricultural energy consumption is an important environmental and social issue. Several diagnoses have been proposed to define indicators for analyzing energy consumption at large scale of agricultural farm activities (year, farm, family of production, etc.). However, to define ad-hoc environmental energetic policies to better monitor and control energy consumption, new indicators at a most detailed scale are needed. Moreover, by defining detailed scale indicators, large quantities of geo-referenced data need to be collected to feed these energetic diagnoses. This huge volume of data represents another important limitation of systems that implement these diagnoses because they are usually based on classical data storage systems (such as spreadsheet tools and Database Management Systems). These systems do not allow for interactive analysis at different granularities/scales of huge volumes of data and do not provide any cartographic representation. By contrast, Spatial OLAP (SOLAP) and spatial data warehouse (SDW) systems allow for the analysis of huge volumes of geo-referenced data by providing aggregated numerical values visualized by means of interactive tabular, graphical and cartographic displays. Thus, in this paper, we (i) propose new appropriate indicators to analyze agricultural farm energy performance at a detailed scale and (ii) show how SDW and SOLAP technologies can be used to represent, store and analyze these indicators by simultaneously producing expressive reports.}, }
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K. Boulil, S. Bimonte, F. Pinet
Un cadre conceptuel basé sur UML et Spatial OCL pour la définition des contraintes d’intégrité dans les systèmes SOLAP
8èmes Journées francophones sur les Entrepôts de Données et l'Analyse en ligne , 12/06/2012-13/06/2012, Bordeaux, FRA (p. 15), 2012
abs web bib

Les entrepôts de données spatiales et les systèmes Spatial OLAP sont des technologies d’aide à la décision permettant l’analyse en ligne des gros jeux de données géo-référencées. Dans un tel type de systèmes, la qualité de l’analyse dépend : de la qualité des données entreposées, de comment les agrégations sont effectuées, et de comment les données entreposées sont explorées. Dans cet article, nous proposons une méthode pour garantir la qualité de ces trois facteurs, fondée sur un profil UML et sur des contraintes d’intégrité définies avec Spatial OCL. Afin de valider notre proposition, nous proposons également une implémentation automatique dans une architecture ROLAP.
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@inproceedings{PUB00035404, author = {Boulil, K. and Bimonte, S. and Pinet, F.}, title = {Un cadre conceptuel basé sur UML et Spatial OCL pour la définition des contraintes d’intégrité dans les systèmes SOLAP}, title = {A conceptual framework based on UML and Spatial OCAL to handle integrity constraints in SOLAP systems}, bookTitle = {8èmes Journées francophones sur les Entrepôts de Données et l'Analyse en ligne , 12/06/2012-13/06/2012, Bordeaux, FRA}, pages = {15}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00035404}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA}, abstract = {Les entrepôts de données spatiales et les systèmes Spatial OLAP sont des technologies d’aide à la décision permettant l’analyse en ligne des gros jeux de données géo-référencées. Dans un tel type de systèmes, la qualité de l’analyse dépend : de la qualité des données entreposées, de comment les agrégations sont effectuées, et de comment les données entreposées sont explorées. Dans cet article, nous proposons une méthode pour garantir la qualité de ces trois facteurs, fondée sur un profil UML et sur des contraintes d’intégrité définies avec Spatial OCL. Afin de valider notre proposition, nous proposons également une implémentation automatique dans une architecture ROLAP.}, }
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K. Boulil, S. Bimonte, F. Pinet
A UML & Spatial OCL based approach for handling quality issues in SOLAP systems
ICEIS 2012 14th International Conference on Enterprise Information Systems , 28/06/2012-01/07/2012, Wroclaw, POL (p. 6), 2012
abs web bib

Spatial Data warehouses and Spatial OLAP systems are Business Intelligence technologies allowing efficient and interactive analysis of large geo-referenced datasets. In such a kind of systems the goodness of analysis depends on: The warehoused data quality, how aggregations are performed, and how warehoused data are explored. In this paper, we propose a framework based on a UML profile and OCL-defined integrity constraints to grant quality in the whole SOLAP system. We also propose an automatic implementation in a classical ROLAP architecture to validate our proposal.
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@inproceedings{PUB00035388, author = {Boulil, K. and Bimonte, S. and Pinet, F.}, title = {A UML & Spatial OCL based approach for handling quality issues in SOLAP systems }, title = {Une approche basée sur UML et Spatial OCL pour la gestion de la qualité dans les systèmes SOLAP}, bookTitle = {ICEIS 2012 14th International Conference on Enterprise Information Systems , 28/06/2012-01/07/2012, Wroclaw, POL}, pages = {6}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00035388}, year = {2012}, affiliation = {IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA ; IRSTEA CLERMONT FERRAND UR TSCF FRA}, abstract = {Spatial Data warehouses and Spatial OLAP systems are Business Intelligence technologies allowing efficient and interactive analysis of large geo-referenced datasets. In such a kind of systems the goodness of analysis depends on: The warehoused data quality, how aggregations are performed, and how warehoused data are explored. In this paper, we propose a framework based on a UML profile and OCL-defined integrity constraints to grant quality in the whole SOLAP system. We also propose an automatic implementation in a classical ROLAP architecture to validate our proposal.}, }
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K. Boulil, S. Bimonte, H. Mahboubi, F. Pinet
Towards the definition of spatial data warehouses integrity constraints with spatial OCL
ACM thirteenth international workshop on data warehousing and OLAP (DOLAP 2010) , 30/10/2010-30/10/2010, Toronto, CAN (p. 5), II-Yeol Song & Carlos Ordonez, 2010
abs web bib

Spatial Data Warehouse (SDW) and Spatial OLAP systems (SOLAP) are now an effective solution to perform multidimensional spatial analysis on geographical data. However, the quality of such analysis heavily depends on the quality of stored data. Due to this, some works have been attempted to address the issues of data quality of SDW using Integrity Constraints (IC). In this paper, we propose a conceptual framework for SDW IC based on two new classifications. Moreover, we describe the specification and implementation of some IC classes using the Object Constraint Language (OCL) and an automatic code generator, called Spatial OCL2SQL.
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@inproceedings{PUB00029624, author = {Boulil, K. and Bimonte, S. and Mahboubi, H. and Pinet, F.}, title = {Towards the definition of spatial data warehouses integrity constraints with spatial OCL}, title = {Vers la définition des contraintes d'intégrité d'entrepôts de données spatiales avec spatial OCL}, bookTitle = {ACM thirteenth international workshop on data warehousing and OLAP (DOLAP 2010) , 30/10/2010-30/10/2010, Toronto, CAN}, publisher = {II-Yeol Song & Carlos Ordonez}, pages = {5}, url = {http://irsteadoc.irstea.fr/cemoa/PUB00029624}, year = {2010}, affiliation = {CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA ; CEMAGREF CLERMONT FERRAND UR TSCF FRA}, abstract = {Spatial Data Warehouse (SDW) and Spatial OLAP systems (SOLAP) are now an effective solution to perform multidimensional spatial analysis on geographical data. However, the quality of such analysis heavily depends on the quality of stored data. Due to this, some works have been attempted to address the issues of data quality of SDW using Integrity Constraints (IC). In this paper, we propose a conceptual framework for SDW IC based on two new classifications. Moreover, we describe the specification and implementation of some IC classes using the Object Constraint Language (OCL) and an automatic code generator, called Spatial OCL2SQL.}, }
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Irstea Motive

Boulil Kamal

Publications

Journal Articles (11)

In Proceedings (5)