MPI - Modelització i Processament de la Informació
http://hdl.handle.net/2117/3570
2016-02-13T02:31:39ZSupporting data integration tasks with semi-automatic ontology construction
http://hdl.handle.net/2117/82774
Supporting data integration tasks with semi-automatic ontology construction
Touma, Rizkallah; Romero Moral, Óscar; Jovanovic, Petar
Data integration aims to facilitate the exploitation of heterogeneous data by providing the user with a unified view of data residing in different sources. Currently, ontologies are commonly used to represent this unified view in terms of a global target schema due to their flexibility and expressiveness. However, most approaches still assume a predefined target schema and focus on generating the mappings between this schema and the sources.
In this paper, we propose a solution that supports data integration tasks by employing semi-automatic ontology construction to create a target schema on the fly. To that end, we revisit existing ontology extraction, matching and merging techniques and integrate them into a single end-to-end system. Moreover, we extend the used techniques with the automatic generation of mappings between the extracted ontologies and the underlying data sources. Finally, to demonstrate the usefulness of our solution, we integrate it with an independent data integration system.
2016-02-10T12:58:30ZTouma, RizkallahRomero Moral, ÓscarJovanovic, PetarData integration aims to facilitate the exploitation of heterogeneous data by providing the user with a unified view of data residing in different sources. Currently, ontologies are commonly used to represent this unified view in terms of a global target schema due to their flexibility and expressiveness. However, most approaches still assume a predefined target schema and focus on generating the mappings between this schema and the sources.
In this paper, we propose a solution that supports data integration tasks by employing semi-automatic ontology construction to create a target schema on the fly. To that end, we revisit existing ontology extraction, matching and merging techniques and integrate them into a single end-to-end system. Moreover, we extend the used techniques with the automatic generation of mappings between the extracted ontologies and the underlying data sources. Finally, to demonstrate the usefulness of our solution, we integrate it with an independent data integration system.A framework for building OLAP cubes on graphs
http://hdl.handle.net/2117/82627
A framework for building OLAP cubes on graphs
Ghrab, Amine; Romero Moral, Óscar; Skhiri, Sabri; Vaisman, Alejandro; Zimányi, Esteban
Graphs are widespread structures providing a powerful abstraction for modeling networked data. Large and complex graphs have emerged in various domains such as social networks, bioinformatics, and chemical data. However, current warehousing frameworks are not equipped to handle efficiently the multidimensional modeling and analysis of complex graph data. In this paper, we propose a novel framework for building OLAP cubes from graph data and analyzing the graph topological properties. The framework supports the extraction and design of the candidate multidimensional spaces in property graphs. Besides property graphs, a new database model tailored for multidimensional modeling and enabling the exploration of additional candidate multidimensional spaces is introduced. We present novel techniques for OLAP aggregation of the graph, and discuss the case of dimension hierarchies in graphs. Furthermore, the architecture and the implementation of our graph warehousing framework are presented and show the effectiveness of our approach.
2016-02-05T12:53:49ZGhrab, AmineRomero Moral, ÓscarSkhiri, SabriVaisman, AlejandroZimányi, EstebanGraphs are widespread structures providing a powerful abstraction for modeling networked data. Large and complex graphs have emerged in various domains such as social networks, bioinformatics, and chemical data. However, current warehousing frameworks are not equipped to handle efficiently the multidimensional modeling and analysis of complex graph data. In this paper, we propose a novel framework for building OLAP cubes from graph data and analyzing the graph topological properties. The framework supports the extraction and design of the candidate multidimensional spaces in property graphs. Besides property graphs, a new database model tailored for multidimensional modeling and enabling the exploration of additional candidate multidimensional spaces is introduced. We present novel techniques for OLAP aggregation of the graph, and discuss the case of dimension hierarchies in graphs. Furthermore, the architecture and the implementation of our graph warehousing framework are presented and show the effectiveness of our approach.Addressing HPC skills shortages with parallel computing MOOC
http://hdl.handle.net/2117/82207
Addressing HPC skills shortages with parallel computing MOOC
Sancho Samsó, María Ribera; Alexandrova, Nia; González, Montserrat
The technical inflection points in the route to Exascale and the existing talent gap in Computational Science and HPC are well publicized. In this paper is described the development of a xMOOC format course with the aim at reaching a target audience composed of BSc, MSc and professional training students that have no experience in parallel programming, as one approach to deal with the lack of specialists that can tackle parallelism. This MOOC utilizes UCATx platform based on and linked to edX. Relying on the expertise of BSC Education and Training Team and UPC Computer Science Lecturers, was devised a course syllabus at introductory level. The paper outlines the design of the course and highlights some of the problems to deliver on-line courses on technical subjects while highlighting the developers' approach to tackle them. An evaluation process for the course is described and the current trends of MOOC courses are reviewed.
2016-01-28T09:52:18ZSancho Samsó, María RiberaAlexandrova, NiaGonzález, MontserratThe technical inflection points in the route to Exascale and the existing talent gap in Computational Science and HPC are well publicized. In this paper is described the development of a xMOOC format course with the aim at reaching a target audience composed of BSc, MSc and professional training students that have no experience in parallel programming, as one approach to deal with the lack of specialists that can tackle parallelism. This MOOC utilizes UCATx platform based on and linked to edX. Relying on the expertise of BSC Education and Training Team and UPC Computer Science Lecturers, was devised a course syllabus at introductory level. The paper outlines the design of the course and highlights some of the problems to deliver on-line courses on technical subjects while highlighting the developers' approach to tackle them. An evaluation process for the course is described and the current trends of MOOC courses are reviewed.Contextualizing learning analytics for secondary schools at micro level
http://hdl.handle.net/2117/82199
Contextualizing learning analytics for secondary schools at micro level
Sancho Samsó, María Ribera; Cañabate Carmona, Antonio; Sabaté i Garriga, Ferran
PILARES (Smart Learning Analytics Platform to enhance Performance in Secondary Education ) is a research project aimed at developing a learning analytics platform for Spanish secondary schools' blended learning focused primarily at micro level (students, teachers, tutors and families). In this paper we contextualize the goal of the PILARES project in the wider panorama of learning analytics with references to the situation in the Spanish context.
2016-01-28T09:35:23ZSancho Samsó, María RiberaCañabate Carmona, AntonioSabaté i Garriga, FerranPILARES (Smart Learning Analytics Platform to enhance Performance in Secondary Education ) is a research project aimed at developing a learning analytics platform for Spanish secondary schools' blended learning focused primarily at micro level (students, teachers, tutors and families). In this paper we contextualize the goal of the PILARES project in the wider panorama of learning analytics with references to the situation in the Spanish context.A robust framework for the estimation of dynamic OD trip matrices for reliable traffic management
http://hdl.handle.net/2117/82164
A robust framework for the estimation of dynamic OD trip matrices for reliable traffic management
Barceló Bugeda, Jaime; Montero Mercadé, Lídia
Origin-Destination (OD) trip matrices describe the patterns of traffic behavior across the network and play a key role as primary data input to many traffic models. OD matrices are a critical requirement, either in static or dynamic models for traffic assignment. However, OD matrices are not yet directly observable; thus, the current practice consists of adjusting an initial or a priori matrix from link flow counts, speeds, travel times and other aggregate demand data. This information is provided by an existing layout of traffic counting stations, as the traditional loop detectors. The availability of new traffic measurements provided by ICT applications offers the possibility to formulate and develop more efficient algorithms, especially suited for real-time applications. However, the efficiently strongly depends, among other factor, on the quality of the seed matrix. This paper proposes an integrated computational framework in which an off-line procedure generates the time-sliced OD matrices, which are the input to an on-line estimator. The paper also analyzes the sensitivity of the on-line estimator with respect to the available traffic measurements
2016-01-27T18:22:37ZBarceló Bugeda, JaimeMontero Mercadé, LídiaOrigin-Destination (OD) trip matrices describe the patterns of traffic behavior across the network and play a key role as primary data input to many traffic models. OD matrices are a critical requirement, either in static or dynamic models for traffic assignment. However, OD matrices are not yet directly observable; thus, the current practice consists of adjusting an initial or a priori matrix from link flow counts, speeds, travel times and other aggregate demand data. This information is provided by an existing layout of traffic counting stations, as the traditional loop detectors. The availability of new traffic measurements provided by ICT applications offers the possibility to formulate and develop more efficient algorithms, especially suited for real-time applications. However, the efficiently strongly depends, among other factor, on the quality of the seed matrix. This paper proposes an integrated computational framework in which an off-line procedure generates the time-sliced OD matrices, which are the input to an on-line estimator. The paper also analyzes the sensitivity of the on-line estimator with respect to the available traffic measurementsOntology-based mappings
http://hdl.handle.net/2117/82030
Ontology-based mappings
Mecca, Giansalvatore; Rull, Guillem; Santoro, Donatello; Teniente López, Ernest
Data translation consists of the task of moving data from a source database to a target database. This task is usually performed by developing mappings, i.e. executable transformations from the source to the target schema. However, a richer description of the target database semantics may be available in the form of an ontology. This is typically defined as a set of views over the base tables that provides a unified conceptual view of the underlying data. We investigate how the mapping process changes when such a rich conceptualization of the target database is available. We develop a translation algorithm that automatically rewrites a mapping from the source schema to the target ontology into an equivalent mapping from the source to the target databases. Then, we show how to handle this problem when an ontology is available also for the source. Differently from previous approaches, the language we use in view definitions has the full power of non-recursive Datalog with negation. In the paper, we study the implications of adopting such an expressive language. Experiments are conducted to illustrate the trade-off between expressibility of the view language and efficiency of the chase engine used to perform the data exchange.
2016-01-26T10:47:02ZMecca, GiansalvatoreRull, GuillemSantoro, DonatelloTeniente López, ErnestData translation consists of the task of moving data from a source database to a target database. This task is usually performed by developing mappings, i.e. executable transformations from the source to the target schema. However, a richer description of the target database semantics may be available in the form of an ontology. This is typically defined as a set of views over the base tables that provides a unified conceptual view of the underlying data. We investigate how the mapping process changes when such a rich conceptualization of the target database is available. We develop a translation algorithm that automatically rewrites a mapping from the source schema to the target ontology into an equivalent mapping from the source to the target databases. Then, we show how to handle this problem when an ontology is available also for the source. Differently from previous approaches, the language we use in view definitions has the full power of non-recursive Datalog with negation. In the paper, we study the implications of adopting such an expressive language. Experiments are conducted to illustrate the trade-off between expressibility of the view language and efficiency of the chase engine used to perform the data exchange.Las habilidades sociales del docente universitario: una formación hacia la competencia interpersonal
http://hdl.handle.net/2117/80948
Las habilidades sociales del docente universitario: una formación hacia la competencia interpersonal
Gómez Soberón, José Manuel Vicente; Berbegal Mirabent, Jasmina; Farrerons Vidal, Óscar; Cañabate Carmona, Antonio; Huerta Carrillo, María; Montero Mercadé, Lídia; Mora Giné, Mercè; Santos Boada, Germán; Torre Martínez, María del Rocío de la; Corral Manuel de Villena, Ignacio de
2015-12-21T14:27:34ZGómez Soberón, José Manuel VicenteBerbegal Mirabent, JasminaFarrerons Vidal, ÓscarCañabate Carmona, AntonioHuerta Carrillo, MaríaMontero Mercadé, LídiaMora Giné, MercèSantos Boada, GermánTorre Martínez, María del Rocío de laCorral Manuel de Villena, Ignacio deComputational framework for the estimation of dynamic OD trip matrices
http://hdl.handle.net/2117/80834
Computational framework for the estimation of dynamic OD trip matrices
Barceló Bugeda, Jaime; Montero Mercadé, Lídia
Origin-Destination (OD) trip matrices describe traffic behavior patterns across the network and play a key role as primary data input to many traffic models. OD matrices are a critical requirement, in traffic assignment models, static or dynamic. However, OD matrices are not yet directly observable; thus, the current practice consists of adjusting an initial a priori matrix from link flow counts, speeds, travel times and other aggregate demand data, supplied by a layout of traffic counting stations. The availability of new traffic measurements from ICT applications offers the possibility to formulate and develop more efficient algorithms, especially suited for real-time applications; whose efficiency depends, among other factors, on the quality of the seed matrix. This paper proposes an integrated computational framework in which an off-line procedure generates the time-sliced OD matrices, which are the input to an on-line estimator, whose sensitivity with respect to the available traffic measurements is analyzed.
Origin-Destination (OD) trip matrices describe traffic behavior patterns across the network and play a key role as primary data input to many traffic models. OD matrices are a critical requirement, in traffic assignment models, static or dynamic. However, OD matrices are not yet directly observable; thus, the current practice consists of adjusting an initial a priori matrix from link flow counts, speeds, travel times and other aggregate demand data, supplied by a layout of traffic counting stations. The availability of new traffic measurements from ICT applications offers the possibility to formulate and develop more efficient algorithms, especially suited for real-time applications. This work proposes an integrated computational framework in which an off-line procedure generates the time-sliced OD matrices, which are the input to an on-line estimator, whose sensitivity with respect to the available traffic measurements is analyzed.
2015-12-16T18:15:58ZBarceló Bugeda, JaimeMontero Mercadé, LídiaOrigin-Destination (OD) trip matrices describe traffic behavior patterns across the network and play a key role as primary data input to many traffic models. OD matrices are a critical requirement, in traffic assignment models, static or dynamic. However, OD matrices are not yet directly observable; thus, the current practice consists of adjusting an initial a priori matrix from link flow counts, speeds, travel times and other aggregate demand data, supplied by a layout of traffic counting stations. The availability of new traffic measurements from ICT applications offers the possibility to formulate and develop more efficient algorithms, especially suited for real-time applications; whose efficiency depends, among other factors, on the quality of the seed matrix. This paper proposes an integrated computational framework in which an off-line procedure generates the time-sliced OD matrices, which are the input to an on-line estimator, whose sensitivity with respect to the available traffic measurements is analyzed.Modeling tuberculosis in Barcelona. A solution to speed-up agent-based simulations
http://hdl.handle.net/2117/80620
Modeling tuberculosis in Barcelona. A solution to speed-up agent-based simulations
Montañola Sales, Cristina; Gilabert Navarro, Joan-Francesc; Casanovas Garcia, Josep; Prats Soler, Clara; López Codina, Daniel; Valls Ribas, Joaquim; Cardona Iglesias, Pere Joan; Vilaplana, Cristina
Tuberculosis remains one
of the world’s deadliest infectious diseases. About one
third of the world’s
population is infected with tuberculosis bacteria. Understanding the dynamics of transmission at different
spatial scales is critical to progress in its control.
2015-12-16T08:37:48ZMontañola Sales, CristinaGilabert Navarro, Joan-FrancescCasanovas Garcia, JosepPrats Soler, ClaraLópez Codina, DanielValls Ribas, JoaquimCardona Iglesias, Pere JoanVilaplana, CristinaTuberculosis remains one
of the world’s deadliest infectious diseases. About one
third of the world’s
population is infected with tuberculosis bacteria. Understanding the dynamics of transmission at different
spatial scales is critical to progress in its control.Applying projection-based methods to the asymmetric traffic assignment problem
http://hdl.handle.net/2117/80036
Applying projection-based methods to the asymmetric traffic assignment problem
Codina Sancho, Esteve; Ibáñez Marí, Gemma; Barceló Bugeda, Jaime
This article examines the application of a path-based algorithm to the static and fixed demand asymmetric traffic assignment problem. The algorithm is of the simplicial decomposition type and it solves the equilibration or master problem step by means of five existing projection methods for variational inequality problems to evaluate their performance on real traffic networks. The projection methods evaluated are: (1) a cost approximation-based method for minimizing the Fukushima's gap function, (2) the modified descent method of Zhu and Marcotte (), (3) the double projection method of Khobotov () and three of its recently developed variants (Nadezhkina and Takahashi, ; Wang etal., ; and He etal., 2012); (4) the method of Solodov and Svaiter (); and (5) the method of Solodov and Tseng (). These projection methods do not require evaluation of the Jacobians of the path cost functions. The source for asymmetries are link costs with interactions, as in the case of priority ruled junctions. The path-based algorithm has been computationally tested using the previous projection methods on three medium to large networks under different levels of congestion and the computational results are presented and discussed. Comparisons are also made with the basic projection algorithm for the fixed demand asymmetric traffic assignment problem. Despite the lack of monotonicity properties of the test problems, the only method that failed to converge under heavy congestion levels was the basic projection algorithm. The fastest convergence was obtained in all cases solving the master problem step using the method of He et al. (2012), which is a variant of Khobotov's method.
2015-11-30T12:48:56ZCodina Sancho, EsteveIbáñez Marí, GemmaBarceló Bugeda, JaimeThis article examines the application of a path-based algorithm to the static and fixed demand asymmetric traffic assignment problem. The algorithm is of the simplicial decomposition type and it solves the equilibration or master problem step by means of five existing projection methods for variational inequality problems to evaluate their performance on real traffic networks. The projection methods evaluated are: (1) a cost approximation-based method for minimizing the Fukushima's gap function, (2) the modified descent method of Zhu and Marcotte (), (3) the double projection method of Khobotov () and three of its recently developed variants (Nadezhkina and Takahashi, ; Wang etal., ; and He etal., 2012); (4) the method of Solodov and Svaiter (); and (5) the method of Solodov and Tseng (). These projection methods do not require evaluation of the Jacobians of the path cost functions. The source for asymmetries are link costs with interactions, as in the case of priority ruled junctions. The path-based algorithm has been computationally tested using the previous projection methods on three medium to large networks under different levels of congestion and the computational results are presented and discussed. Comparisons are also made with the basic projection algorithm for the fixed demand asymmetric traffic assignment problem. Despite the lack of monotonicity properties of the test problems, the only method that failed to converge under heavy congestion levels was the basic projection algorithm. The fastest convergence was obtained in all cases solving the master problem step using the method of He et al. (2012), which is a variant of Khobotov's method.