Sandro Bimonte

Sandro Bimonte
French National Institute for Agriculture, Food, and Environment (INRAE) | INRAE · Unité de recherche Technologies et systèmes d’information pour les agrosystèmes (TSCF)

Doctor of computer science

About

186
Publications
22,048
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
952
Citations

Publications

Publications (186)
Chapter
The ability to query vast amount of historical data for statistical analysis and reporting is provided by Data Warehouses. They facilitate Business Intelligence for effective decision-making significantly. In recent years, great progress has been made in movement monitoring devices, such as smart phones and GPSs. The storing and managing of spatio-...
Article
The Internet of Things is currently one of the most representative sources of Big Data. It can acquire real-time data from multiple spatially distributed points, allowing for the extraction of valuable insights. However, an appropriate integration, processing, and analysis of these data depends on several factors starting from the correct definitio...
Conference Paper
The design and implementation of agro-ecology IoT applications is a non-trivial task since the data processed in such applications are typically complex and heterogeneous. Moreover, these applications are implemented using different systems and technologies, over complex IoT communication network layers (edge, fog, cloud). The existing system desig...
Article
Full-text available
With the maturity of crowdsourcing systems, new analysis possibilities appear where volunteers play a crucial role by bringing the implicit knowledge issued from practical and daily experience. At the same time, data warehouse and OLAP systems represent the first citizen of decision-support systems. They allow analyzing a huge volume of data accord...
Article
Full-text available
The design of data warehouses (DWs) is based on both their data sources and users’ requirements. The more closely the DW multidimensional schema reflects the stakeholders’ needs, the more effectively they will make use of the DW content for their OLAP analyses. Thus, considerable attention has been given in the literature to DW requirements analysi...
Article
Multi-model DBMSs (MMDBMSs) have been recently introduced to store and seamlessly query heterogeneous data (structured, semi-structured, graph-based, etc.) in their native form, aimed at effectively preserving their variety. Unfortunately, when it comes to analyzing these data, traditional data warehouses (DWs) and OLAP systems fall short because t...
Article
Multidimensional modeling, i.e., the design of cube schemata, has a key role in data warehouse (DW) projects, in self-service business intelligence, and in general to let users analyze data via the OLAP paradigm. Though an effective involvement of users in multidimensional modeling is crucial in these projects, not much has been said about how to e...
Article
In France and Europe, farmland represents a large fraction of land cover. The study and assessment of biodiversity in farmland is therefore a major challenge. To monitor biodiversity across wide areas, citizen science programs have demonstrated their effectiveness and relevance. The involvement of citizens in data collection offers a great opportun...
Chapter
In the era of Big Data, more and more stream data is available. In the same way, Decision Support Systems (DSS) tools, such as data warehouses and alert systems, become more and more sophisticated, and conceptual modeling tools are consequently mandatory for successfully DSS projects. Formalisms such as UML and ER have been widely used in the conte...
Chapter
Data Warehouse (DW) and OLAP systems are acknowledged as first citizens of Business Intelligence (BI) technologies, allowing the on-line analysis of huge volumes of data. However, traditional data-driven BI might not be enough to compete in the context of Industry 4.0, since the collection and analysis of data from the Internet of Things (IoT) requ...
Article
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 (MD...
Article
Data Warehouse (DW) and OLAP systems are first citizens of Business Intelligence tools. They are widely used in the academic and industrial communities for numerous different fields of application. Despite the maturity of DW and OLAP systems, with the advent of Big Data, more and more sources of data are available, and warehousing this data can lea...
Conference Paper
Full-text available
RESUME. La conservation de la biodiversité et sa relation avec les pratiques agricoles représentent actuellement un défi majeur, car elles touchent à des enjeux environnementaux, sociaux et économiques. Les systèmes VGI ne fournissent pas d'outils graphiques d'analyses complexes. Dans cet article nous présentons donc l'implémentation d'un entrepôt...
Conference Paper
Full-text available
Les méthodes de la géovisualisation intégrées dans les systèmes OLAP ne concernent que des données spatiales classiques (points, lignes et polygones). Notre objectif dans cet article est de définir une nouvelle méthodologie d'analyse visuelle qui intègre le space-time cube, cartes animées et le tableau croisé dyna-mique pour considérer les données...
Article
Full-text available
Le secteur agroalimentaire est confronté à des défis mondiaux. Le premier concerne l'alimentation d'une population mondiale qui, selon les prévisions de l'ONU, atteindra 9,3 milliards de personnes en 2050. Le deuxième défi est la demande des consommateurs pour des produits de haute qualité obtenus par des chaînes agroalimentaires plus durables, plu...
Article
A decision support system is used by decision makers for a long time. But, in some cases, the originally designed multidimensional schema does not cover the entire needs of decision makers, which can change over time. One such unfulfilled needs, is using facts to describe dimension members. In this article, we propose a methodology to transform the...
Chapter
In this paper we present a user experience report on a Group Decision Support System. The used system is a Collaborative framework called GRoUp Support (GRUS). The experience consists in three user tests conducted in three different countries. While the locations are different, all three tests were run in the same conditions: same facilitator and t...
Article
Full-text available
Modelling WSN data behaviour is relevant since it would allow to evaluate the capacity of an application for supplying the user needs, moreover, it could enable a transparent integration with different data-centric information systems. Therefore, this article proposes a data-centric UML profile for the design of wireless sensor nodes from the user...
Article
In the era of Big Data, more and more stream data is available. In the same way, Decision Support Systems (DSS) tools, such as data warehouses and alert systems, become more and more sophisticated, and conceptual modeling tools are consequently mandatory for successfully DSS projects. Formalisms such as UML and ER have been widely used in the conte...
Article
The emergence of spatial or geographic data in DW Systems defines new models that support the storage and manipulation of the data. The need to build an SDW and to optimize SOLAP queries continues to attract the interest of researchers in recent years. Several spatial data models have been investigated to extend classical multidimensional data mode...
Chapter
In the context of Volunteered Geographic Information (VGI), volunteers are not involved in the decisional processes. Moreover, VGI systems do not offer advanced historical analysis tools. Therefore, in this work, we propose to use Data Warehouse (DW) and OLAP systems to analyze VGI data, and we define a new DW design methodology that allows involvi...
Conference Paper
Full-text available
Spatial OLAP systems are GeoBusiness Intelligence systems allowing the exploration and analysis of huge volume of spatial data by means of tabular, graphic and cartographic displays. Although map readability is crucial for decision-making processes, readability of SOLAP maps has not been deeply investigated. In this paper, a initial study on readab...
Conference Paper
Full-text available
Motivated by the importance of the analysis of farmland biodiversity data, and the lack of advanced analysis tools of VGI systems, in this paper we present main issues related to the analysis of VGI farmland biodiversity data using SOLAP systems. We develop challenges related to volunteers and crowd sourced data. Then, we present some possible solu...
Article
Full-text available
Olive tree is one of the most important crop at global scale. Apulia is the first olive-producing region in Italy, with a huge amount of farms that generate Integrated Pest Management (IPM) data. IPM requires the simultaneous use of different crop protection techniques to control pests through an ecological and economic approach. The crop protectio...
Article
Full-text available
The Agri-Food sector is facing global challenges. The first challenge is feeding a world population that will reach 9.3 billion people in 2050, according to UN projections. The second challenge is the demand from consumers for high-quality products obtained through more sustainable, safe and clear agri-food chains. Integrated pest management (IPM)...
Chapter
Spatial OLAP (SOLAP) systems are powerful GeoBusiness Intelligence tools for analysing massive volumes of geo-referenced datasets. Therefore, these technologies are receiving considerable attention in the research community and in the database industry as well. Applications of these technologies are current in several domains such as ad marketing,...
Chapter
Spatial OLAP (SOLAP) technologies are dedicated to multidimensional analysis of large volumes of (spatial) data. Spatal data are subject to different types of uncertainty, in particular spatial vagueness. Although several researches propose new models to cope with spatial vagueness, their integration in SOLAP systems is still in an embryonic state....
Conference Paper
The Agri-Food sector is facing global challenges. The first concerns feeding a world population that in 2050, according to UN projections, will reach 9.3 billion people. The second challenge is the request by consumers for high quality products obtained by more sustainable, safely and clear agri-food chains. The Integrated Pest Management (IPM) cou...
Conference Paper
Full-text available
Les entrepôts des données spatiales (EDS) et OLAP Spatial (SOLAP) intègrent les outils d'analyse spatiale et de géovisualisation offerts par les Systèmes d'Information Géographique (SIG) aux fonctionnalités OLAP. Peu de travaux étudient les problèmes de géovisualisation dans les systèmes SOLAP et aucun travail ne propose d'outils pour des affichage...
Article
Designing and building a Data Warehouse (DW), and associated OLAP cubes, are long processes, during which decision-maker requirements play an important role. But decision-makers are not OLAP experts and can find it difficult to deal with the concepts behind DW and OLAP. To support DW design in this context, we propose: (i) a new rapid prototyping m...
Article
Full-text available
Les questions énergétiques liées aux exploitations agricoles constituent un sujet de recherche qui préoccupe la communauté internationale et ce, pour des questions environnementales et économiques. En matière de systèmes d'information, la technologie des entrepôts de données et les bases de données multidimensionnelles font émerger de nouvelles sol...
Article
Spatial online analytical processing (OLAP) and spatial data warehouse (SDW) systems are geo-business intelligence technologies that enable the analysis of huge volumes of geographic data. In the last decade, the conceptual design and implementation of SDWs that integrate spatial data, which are represented using the vector model, have been extensi...
Conference Paper
Full-text available
RESUME. La conception d'applications OLAP Spatial (SOLAP) consiste en (i) la conception du modèle d'entrepôt de données spatiales (EDS), et (ii) la définition de la visualisation de SOLAP, car un ensemble spécifique de visualisations cartographiques compréhensibles et lisibles correspond à un type particulier de requêtes SOLAP. Malheureusement, peu...
Conference Paper
Full-text available
The design of Spatial OLAP (SOLAP) applications consists of (i) Spatial Data Warehouse (SDW) model design and (ii) SOLAP visualization definition because a specific set of understandable and readable cartographic visualizations corresponds to a particular type of SOLAP query. Unfortunately few works investigate geovisualization issues in SOLAP syst...
Article
Farm Management Information Systems provide decision-makers (farmers) with a set of predefined Key Performance Indicators (KPIs) that are issued manually from collected data or via sensors installed on farm equipment. However, agricultural decision-makers need ad-hoc KPIs issued from low-cost sensors. Therefore, we present our VBoxReporting system...
Article
Spatial OLAP (SOLAP) systems are powerful GeoBusiness Intelligence tools for analysing massive volumes of geo-referenced datasets. Therefore, these technologies are receiving considerable attention in the research community and in the database industry as well. Applications of these technologies are current in several domains such as ad marketing,...
Article
Nowadays, more and more data are available for decisional analysis and decision-making based on different indicators. Although different decision-making technologies have been developed, the authors note the lack of a conceptual framework for the definition and implementation of these indicators. In this paper, they propose a first classification o...
Conference Paper
Full-text available
Un système OLAP Spatial (SOLAP) vise à analyser interactivement les données géoréférencées. Il permet aux décideurs d'explorer et de visualiser les entrepôts de données spatiales en utilisant des tables multidimensionnelles « pivot table » et d'affichage cartographique des faits sur des cartes interactives. Dans cet article, nous présentons un prot...
Conference Paper
Spatial OLAP (SOLAP) systems are decision-support systems for the analysis of huge volumes of spatial data. Usually, SOLAP clients provide decision-makers with a set of graphical, tabular and cartographic displays to visualize warehoused spatial data. Geovisualization methods coupled with existing SOLAP systems are limited to interactive (multi) ma...
Article
Full-text available
Data Warehouse and OLAP systems allow analyzing huge volumes of data represented according to the multidimensional model. In the era of Big Data, NoSQL systems have been proved to be an effective Business Intelligence solution. Some works recently study warehousing and OLAPing Big Data. (Un)Lucky these works exclusively investigate time performance...
Conference Paper
Full-text available
Les hiérarchies sont des structures cruciales dans un entrepôt de don-nées puisqu'elles permettent l'agrégation de mesures dans le but de proposer une vue analytique plus ou moins globale sur les données entreposées, selon le niveau hiérarchique auquel on se place. Cependant, peu de travaux s'intéressent à la construction de hiérarchies, via un alg...
Article
OLAP and datawarehouse (DW) systems are technologies intended to support the decision-making process, enabling the analysis of a substantial volume of data. One of the goals of recommender systems is to help users navigate large amounts of data. OLAP recommender systems have recently been proposed in the literature because the multidimensional anal...
Book
More and more data are collected via sensors. Wireless networks can be implemented to facilitate the collection of sensors data and to reduce the cost of their acquisition. In this chapter, we present a general architecture combining Wireless Sensor Network (WSN) and Spatial Data Warehouse (SDW) technologies. This innovative solution is used to col...
Article
Spatial OLAP (SOLAP) systems are decision-support systems for the analysis of huge volumes of spatial data. Usually, SOLAP clients provide decision-makers with a set of graphical, tabular and cartographic displays to visualize warehoused spatial data. Geovisualization methods coupled with existing SOLAP systems are limited to interactive (multi) ma...
Chapter
Spatial data warehouses (SDW) and spatial OLAP (SOLAP) systems are well-known business intelligence technologies that aim to support a multidimensional and online analysis for a large volume of geo-referenced datasets. SOLAP systems are already used in the context of natural hazards for analyzing sensor data and experts' measurements. Recently, new...
Chapter
Spatial-OLAP (SOLAP) technologies are dedicated to multidimensional analysis of large volumes of (spatial) data. Spatial data are subject to different types of uncertainty, in particular spatial vagueness. Although several researches propose new models to cope with spatial vagueness, their integration in SOLAP systems is still in an embryonic state...
Chapter
More and more data are collected via sensors. Wireless networks can be implemented to facilitate the collection of sensors data and to reduce the cost of their acquisition. In this chapter, we present a general architecture combining Wireless Sensor Network (WSN) and Spatial Data Warehouse (SDW) technologies. This innovative solution is used to col...
Chapter
DBMS is a traditional technology for the storage of business application data. In this chapter, we show that this technology can be of interest in scientific fields. We present a survey of the emergence of the concept of simulation result database. Scientific simulation models become more complex, use more data and produce more outputs. Stochastic...
Conference Paper
Data Warehouse (DW) and OLAP systems are effective solutions for the online analysis of large volumes of data structured as cubes. Usually organizations and enterprises require several cubes for their activities. In this context, we define a new kind of queries: “Top-k Cubes queries”. Top-K cubes queries allow searching the most relevant k-cubes am...
Article
Spatial Data Warehouses (SDWs) and Spatial On-Line Analytical Processing (SOLAP) systems are new technologies for the integration and the analysis of huge volume of data with spatial reference. Spatial vagueness is often neglected in these types of systems and the data and analysis results are considered reliable. In a previous work, the authors pr...
Article
Spatial Data warehouses and Spatial OLAP (SOLAP) systems allow analyzing huge volumes of georeferenced datasets. SOLAP has been successfully applied in several domains such as marketing, health, urbanism, etc. Few of SOLAP applications in the agricultural context have been proposed. The analysis of work reveals specific issues related to spatio-mul...
Article
Spatial-OLAP (SOLAP) technologies are dedicated to multidimensional analysis of large volumes of (spatial) data. Spatial data are subject to different types of uncertainty, in particular spatial vagueness. Although several researches propose new models to cope with spatial vagueness, their integration in SOLAP systems is still in an embryonic state...
Article
Cet article décrit un système décisionnel développé pour permettre l'analyse des don-nées concernant le fonctionnement des hydro-écosystèmes ; ces données sont nombreuses, di-verses 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,...
Conference Paper
Full-text available
Data warehouses (DW) and OLAP systems are business intelligence technologies allowing the on-line analysis of huge volume of data according to users' needs. The success of DW projects essentially depends on the design phase where functional requirements meet data sources (mixed design methodology) (Phipps and Davis, 2002). However, when dealing wit...
Conference Paper
Full-text available
Les entrepôts de données (DW) et les systèmes OLAP sont des technologies d’analyse en ligne pour de grands volumes de données, basés sur les besoins des utilisateurs. Leur succès dépend essentiellement de la phase de conception où les exigences fonctionnelles sont confrontées aux sources de données (méthodologie de conception mixte). Cependant, les...
Conference Paper
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. I...
Book
More and more agricultural and environmental data are now available. These data are produced by numerous methods: Terrestrial sensors, remote sensing systems, simulation models, Internet of things, etc. Agricultural and environmental Information Systems (IS) and Decision Support Systems (DSS) are two complementary approaches to use these data – the...
Book
Tasks such as monitoring and managing the ecological status of rivers, sharing environmental information, and helping farmers in their decision making are challenges for which information and decision support systems (DSS) represent effective solutions. New theoretical and technical challenges emerge from the integration of several scientific domai...
Book
DBMS is a traditional technology for the storage of business application data. In this chapter, we show that this technology can be of interest in scientific fields. We present a survey of the emergence of the concept of simulation result database. Scientific simulation models become more complex, use more data and produce more outputs. Stochastic...
Article
Spatial-OLAP (SOLAP) technologies are dedicated to multidimensional analysis of large volumes of (spatial) data. Spatial data are subject to different types of uncertainty, in particular spatial vagueness. Although several researches propose new models to cope with spatial vagueness, their integration in SOLAP systems is still in an embryonic state...
Article
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). But, for complex applications, existing automatic design methodologies seem inecient. In some...
Article
The problem of storage and querying of large volumes of spatial grids is an issue to solve. In this paper, we propose a method to optimize queries to aggregate raster grids stored in databases. In our approach, we propose to estimate the exact result rather than calculate the exact result. This approach reduces query execution time. One advantage o...
Article
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 wat...
Article
Volunteered Geographic Information (VGI) has great potential for enhancing analysts’ capabilities, assuming that VGI data quality issues, such as credibility and precision, are properly addressed. In this paper, we study the integration of VGI in Spatial OLAP (SOLAP) systems, which allow the integration and analysis of large volumes of good quality...
Article
Spatial Data Warehouse (SDW) and Spatial On-Line Analytical Processing (SOLAP) systems are technologies intended to support geographic business intelligence. SOLAP clients provide a cartographic representation of facts on maps, and perform SOLAP operations through simple user interactions with the maps. Services are unassociated, loosely coupled un...