A query processing system for very large spatial databases using a new map algebra

Dans cette thèse nous introduisons une approche de traitement de requêtes pour des bases de donnée spatiales. Nous expliquons aussi les concepts principaux que nous avons défini et développé: une algèbre spatiale et une approche à base de graphe utilisée dans l'optimisateur. L'algèbre spatiale est défini pour exprimer les requêtes et les règles de transformation pendant les différentes étapes de l'optimisation de requêtes. Nous avons essayé de définir l'algèbre la plus complète que possible pour couvrir une grande variété d'application. L'opérateur algébrique reçoit et produit seulement des carte. Les fonctions reçoivent des cartes et produisent des scalaires ou des objets. L'optimisateur reçoit la requête en expression algébrique et produit un QEP (Query Evaluation Plan) efficace dans deux étapes: génération de QEG (Query Evaluation Graph) et génération de QEP. Dans première étape un graphe (QEG) équivalent de l'expression algébrique est produit. Les règles de transformation sont utilisées pour transformer le graphe a un équivalent plus efficace. Dans deuxième étape un QEP est produit de QEG passé de l'étape précédente. Le QEP est un ensemble des opérations primitives consécutives qui produit les résultats finals (la réponse finale de la requête soumise au base de donnée). Nous avons implémenté l'optimisateur, un générateur de requête spatiale aléatoire, et une base de donnée simulée. La base de donnée spatiale simulée est un ensemble de fonctions pour simuler des opérations spatiales primitives. Les requêtes aléatoires sont soumis à l'optimisateur. Les QEPs générées sont soumis au simulateur de base de données spatiale. Les résultats expérimentaux sont utilisés pour discuter les performances et les caractéristiques de l'optimisateur.Abstract: In this thesis we introduce a query processing approach for spatial databases and explain the main concepts we defined and developed: a spatial algebra and a graph based approach used in the optimizer. The spatial algebra was defined to express queries and transformation rules during different steps of the query optimization. To cover a vast variety of potential applications, we tried to define the algebra as complete as possible. The algebra looks at the spatial data as maps of spatial objects. The algebraic operators act on the maps and result in new maps. Aggregate functions can act on maps and objects and produce objects or basic values (characters, numbers, etc.). The optimizer receives the query in algebraic expression and produces one efficient QEP (Query Evaluation Plan) through two main consecutive blocks: QEG (Query Evaluation Graph) generation and QEP generation. In QEG generation we construct a graph equivalent of the algebraic expression and then apply graph transformation rules to produce one efficient QEG. In QEP generation we receive the efficient QEG and do predicate ordering and approximation and then generate the efficient QEP. The QEP is a set of consecutive phases that must be executed in the specified order. Each phase consist of one or more primitive operations. All primitive operations that are in the same phase can be executed in parallel. We implemented the optimizer, a randomly spatial query generator and a simulated spatial database. The query generator produces random queries for the purpose of testing the optimizer. The simulated spatial database is a set of functions to simulate primitive spatial operations. They return the cost of the corresponding primitive operation according to input parameters. We put randomly generated queries to the optimizer, got the generated QEPs and put them to the spatial database simulator. We used the experimental results to discuss on the optimizer characteristics and performance. The optimizer was designed for databases with a very large number of spatial objects nevertheless most of the concepts we used can be applied to all spatial information systems."--Résumé abrégé par UMI

Data interoperability across borders : a case study of the Abbotsford-Sumas aquifer (British Columbia-Washington State)

The ability to integrate data from multiple sources is central to geographic information science (GIS).  Although data integration is an active field of research in the GIS community, a number of challenges remain unresolved. Interoperability research addressing data integration challenges experienced by institutions in an international setting also remains sparse. Groundwater is an example of an environmental phenomenon which does not respect political borders, and its management requires data from multiple jurisdictions. The Abbotsford-Sumas aquifer, straddling the Canada US border, is used as a case study to explore integration challenges in an international setting. Development of groundwater management practices to ensure a sustained source of good quality groundwater is dependent, on an understanding of the conceptual model of the aquifer. Due to a lack of geophysical studies, geological information contained in the water well reports, is the chief source of depth-specific lithological information. The use of this information in constructing the conceptual model is constrained by poor data quality and a lack of an integrated and standardized lithological database. To achieve the research goals of exploring integration challenges in an international setting, lithological datasets from BC and Washington State are integrated. The resultant lithological database is used to test the usability of water well reports for constructing the conceptual model. Numerous interoperability challenges such as data availability, lack of metadata, data quality and formats, database structure, semantics, policies and cooperation are identified as inhibitors of data integration. Despite the numerous challenges the lithological database is useful in constructing a generalized conceptual model. This research is important as it presents challenges to data integration that should be considered as a starting point for environmental management projects

Categorical database generalization in GIS

Key words: Categorical database, categorical database generalization, Formal data structure, constraints, transformation unit, classification hierarchy, aggregation hierarchy, semantic similarity, data model, Delaunay triangulation network. semantic similarity evaluation model.Categorical databases are widely used in GIS for different kinds of application, analysis, planning, evaluation and management. Database generalization that derives different resolution databases from a single database with more detail is one of the key research problems and a hot research point in the GIS and Cartography field. This dissertation presents a framework for categorical database generalization in GIS. It includes defining conceptual aspects of current categorical database generalization transformation and constraints for generalization transformation, elaboration on supporting data structure and transformation units, development of auxiliary analysis methods, and demonstration of some application examples.Database generalization is considered as a transformation process. Three kinds of transformation are defined based on the characteristics of categorical database and categorical database generalization. They are geo-spatial model transformation, object transformation and relation transformation. Each transformation has a certain function and deals with some aspects of database. Geo-spatial transformation is mainly used to define the content framework of a new database and decide the theme of a new database. Object transformation and relation transformation deal with transformations of thematic and geometric aspects of objects and relationship between objects from an existing database to a new database.Database generalization (transformation) requires a data structure that strongly supports data organization, spatial analysis and decision-making in a database. The design of a data structure should take two functions into account. One provides the basis for describing and organizing spatial objects and the relationships between them. and the other is for analyzing and supporting operations on spatial objects. This thesis introduces the IEFDS, an integrated and extended version of FDS, as a data model to support automated database generalization transformation. The addition to FDS is triangles. The triangles and their classification are proposed based on constituent properties of triangles in IEFDS which plays an important role in the extended adjacent and inclusion relations and extracting the skeleton line. Some examples of spatial query operations that make use of the extended adjacent relation and semantic triangles are also provided in this thesis.In a categorical database, similarity between object types can be described by a similarity measure. The similarity is application-dependent. In a sense, the similarity will control and guide database transformation operations. The similarity evaluation model and similarity matrix are proposed for analyzing and representing similarity between objects and object types in this study which is based on Set-theory, classification and aggregation hierarchy. The constraints such as transformation conditions play a key role in the process of databasegeneralization. Constraints can be used to identify conflicting areas, guide choices of operationsand trigger operations as well as govern the database generalization. The processes of generalization should be performed by a series of operations under the control of constraints. Three types of constraints, data model. object and relationships based on an object-oriented database are proposed in landuse database generalization. These constraints can be specified interactively by users and varied to reflect different objectives or purposes. These types of constraints are applicationdependent. This will make the database generalization process very flexible/adaptive, and the decisionmaking can be based on geographic meaning and not simply on the geometry of an object.An important element proposed in this study is the transformation unit. It is an important process unit as many generalization problems need to be solved by considering a subset of related objects as a whole, rather than treating them individually. In a sense, the transformation unit is a basic analysis. processing, decision-making unit and a trigger to aggregation operation processes and it plays an important role in database transformation. The conflicted objects and its (their) related objects are organized into a transformation unit. A transformation unit that "brings together- a subset of objects can he created by conflict,; in thematic and /or geometric aspects of objects or spatial relation among objects or integrating them. The main purpose of creating a transformation unit is for the preparationofan aggregation operation. It limits the area and numberofa setofrelated objects in an aggregation operation. The different conflict types will create different types of transformation units. For this study, four types of transformation units are considered based on the constraints discussed. Each of which has a corresponding aggregation operation.The auxiliary analysis methods (algorithms) are needed to actually perform spatial analysis and transformations. The most fundamental tasks are to identify where to generalize, how to generalize, and when to generalize. The thesis introduces a number of auxiliary analysis methods that have been developed to solve a number of important geometric and thematic problems in database trans, form ati on. These auxiliary analysis methods include semantic similarity rnatrix, computing a model of similarity, detection and creation of transformation units, area object aggregation analysis and the process based on transformation units, multineighborhood, object cluster and creation of catchments hierarchy etc.Such examples of the application are included in the thesis as object cluster, land use aggregation and automated organization of hierarchical catchments. The application examples demonstrate the applicability and benefits of the IEFDS and similarity evaluation model. These supporting models play a key role in organizing thematic and geometric data, spatial analysis and spatial query in database generalization. It also proved that a lot of critical geometric and thematic problems in database generalization can be solved, or can be solved in a more efficient way, with the support of an adequate data model.</font

Grey Literature in Library and Information Studies

The further rise of electronic publishing has come to change the scale and diversity of grey literature facing librarians and other information practitioners. This compiled work brings together research and authorship over the past decade dealing with both the supply and demand sides of grey literature. While this book is written with students and instructors of Colleges and Schools of Library and Information Science in mind, it likewise serves as a reader for information professionals working in any and all like knowledge-based communities

Formal extension of the relational model for the management of spatial and spatio-temporal data

[Resumen] En los últioms años, se ha realizado un gran esfuerzo investigador en la manipulación de datos especiales y Sistemas de Información Geográfica (SIG). Una clara limitación de las primeras aproximaciones es la falta de integración entre datos geográficos y alfanuméricos. Para resolver esto surge el área de Bases de Datos Espaciales. Los problemas que aparecen en este campo son muchos y complejos. Un primer ejemplo son las peculiaridades de las operaciones espaciales, como el calculo de la intersección espacial de dos superficies. Otro ejemplo es el elegir las estructuras de datos apropiadas (relaciones, capas, etc.) y el conjunto de operaciones adeucado. La combinación con las Bases de Datos Temporales da lugar a las Bases de Datos Espacio-temporales, en las que la inclusión de la dimensión temporal complica más los problemas anteriores. A pesar de la gran cantidad de aproximaciones propuestas, no se ha llegado todavía a una solución satisfactoria. La presente tesis propone una nueva solución que resuelve todos los problemas de modelado de datos espaciales y espacio-temporales resaltados arriba. Parte del trabajo se completó durante el proyecto ""CHOROCRONOS"": A Research Network for Saptiotemporal Database Systems"", financiado por la Unión Europea. El modelo propuesto en la tesis define tres tipos de dato punto, línea y superficie, que encajan perfectamente en la percepción humana. La definición de estos tipos de dato se basa en la definición previa de Quanta Espacial. Las estructuras de datos usadas son las relaciones no anidadas de modelo relacional puro. El conjunto de operaciones relacionales permite alcanzar casi por completo la funcionalidad propuesta en otros modelos. Todas las operaciones han sido definidas en base a un núcleo reducido de operaciones primitvas. Todos los tipos de datos, espaciales, espacio-temporales y convencionales se manipulan de forma uniforme con este conjunto de operaciones

Contexts and Contributions: Building the Distributed Library

This report updates and expands on A Survey of Digital Library Aggregation Services, originally commissioned by the DLF as an internal report in summer 2003, and released to the public later that year. It highlights major developments affecting the ecosystem of scholarly communications and digital libraries since the last survey and provides an analysis of OAI implementation demographics, based on a comparative review of repository registries and cross-archive search services. Secondly, it reviews the state-of-practice for a cohort of digital library aggregation services, grouping them in the context of the problem space to which they most closely adhere. Based in part on responses collected in fall 2005 from an online survey distributed to the original core services, the report investigates the purpose, function and challenges of next-generation aggregation services. On a case-by-case basis, the advances in each service are of interest in isolation from each other, but the report also attempts to situate these services in a larger context and to understand how they fit into a multi-dimensional and interdependent ecosystem supporting the worldwide community of scholars. Finally, the report summarizes the contributions of these services thus far and identifies obstacles requiring further attention to realize the goal of an open, distributed digital library system

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.Fundação para a Ciência e a Tecnologia (FCT) - (Referencia da bolsa: SFRH SFRH / BD / 33965 / 2009) and EC 7th Framework Programme under grant agreement n° FITMAN 604674 (http://www.fitman-fi.eu

Development of linguistic linked open data resources for collaborative data-intensive research in the language sciences

Making diverse data in linguistics and the language sciences open, distributed, and accessible: perspectives from language/language acquistiion researchers and technical LOD (linked open data) researchers. This volume examines the challenges inherent in making diverse data in linguistics and the language sciences open, distributed, integrated, and accessible, thus fostering wide data sharing and collaboration. It is unique in integrating the perspectives of language researchers and technical LOD (linked open data) researchers. Reporting on both active research needs in the field of language acquisition and technical advances in the development of data interoperability, the book demonstrates the advantages of an international infrastructure for scholarship in the field of language sciences. With contributions by researchers who produce complex data content and scholars involved in both the technology and the conceptual foundations of LLOD (linguistics linked open data), the book focuses on the area of language acquisition because it involves complex and diverse data sets, cross-linguistic analyses, and urgent collaborative research. The contributors discuss a variety of research methods, resources, and infrastructures. Contributors Isabelle Barrière, Nan Bernstein Ratner, Steven Bird, Maria Blume, Ted Caldwell, Christian Chiarcos, Cristina Dye, Suzanne Flynn, Claire Foley, Nancy Ide, Carissa Kang, D. Terence Langendoen, Barbara Lust, Brian MacWhinney, Jonathan Masci, Steven Moran, Antonio Pareja-Lora, Jim Reidy, Oya Y. Rieger, Gary F. Simons, Thorsten Trippel, Kara Warburton, Sue Ellen Wright, Claus Zin