Dataspaces aim to remove upfront cost in the generation of the schema mappings that reconcile schematic heterogeneities, and to incrementally improve the generated mappings based on user feedback. The reconciliation of schematic heterogeneities is a crucial step for translating queries between a mediating schema and data sources. The generation of schema mappings depends on the elicitation of conceptually equivalent schema constructs and information on schematic heterogeneities. Furthermore, many dataspace operations manipulate associations between schemas, for example for generating a global schema to mediate user queries. With a view to minimizing upfront costs associated with understanding the relationships between schemas, many schema matching algorithms and tools have been developed for postulating equivalent schema constructs. However, they derive simple associations between schema constructs, and do not provide rich information on schematic heterogeneities. Without manual refinement, the elicitation of conceptually equivalent schema constructs and schematic heterogeneities may create uncertainties that must be managed.The schematic correspondences captures a wide range of one-to-one and many-to-many schematic heterogeneities. This thesis investigates the use of schematic correspondences as a central component in a dataspace management system. To support query evaluation in a dataspace in which relationships between schemas are represented using schematic correspondences, we propose a mechanism for automatically generating schema mappings from the schematic correspondences. We then characterise model management operators, which can underpin the bootstraping and maintenance of dataspaces, over schematic correspondences. To support the management of uncertainty in dataspaces, we propose techniques for quantifying uncertainty in the equivalence of schema constructs from evidence in the form of similarity scores and user feedback, and provide a flexible framework for incrementally updating the uncertainties in the light of new evidence.

Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-05-21T13:33:00Z No. of bitstreams: 1 JOSÉ AMILTON MOURA ACIOLI FILHO - DISSERTAÇÃO (PPGCC) 2016.pdf: 4531903 bytes, checksum: 0544920547c2d257f657b480a1c5f45f (MD5) / Made available in DSpace on 2018-05-21T13:33:00Z (GMT). No. of bitstreams: 1 JOSÉ AMILTON MOURA ACIOLI FILHO - DISSERTAÇÃO (PPGCC) 2016.pdf: 4531903 bytes, checksum: 0544920547c2d257f657b480a1c5f45f (MD5) Previous issue date: 2016-09-02 / Com a evolução da web e dos sistemas de informação, as organizações têm obtido dados dos mais diversos formatos, estruturas e tipos, podendo-se destacar os espaciais. Devido aos dados apresentarem características distintas, estes acabam sendo mantidos em fontes de dados heterogêneas, sendo assim necessário investir cada vez mais em soluções que possam integrar e analisar estes dados de diferentes fontes. Algumas destas soluções conseguem analisar o componente espacial dos dados, no entanto, essa análise dos dados espaciais é limitada pelo tipo de dados ou funções espaciais suportadas. Neste trabalho, é abordado o problema da integração de dados espaciais de fontes de dados heterogêneas, com ou sem esquema, utilizando linguagem SQL. Este é um problema em aberto na área de integração de dados espaciais, pois as soluções existentes apresentam inúmeras limitações, a exemplo da linguagem de consulta utilizada, os meios para acesso a dados, as tecnologias que podem ser integradas, as funções disponibilizadas e os tipos de dados espaciais suportados. Visando solucionar esse problema, desenvolveu-se a solução GeoDrill, uma extensão do Apache Drill que dá suporte a todas as funções espaciais padronizadas pela OGC (Open Geospatial Consortium), através da linguagem SQL, podendo realizar consultas em dados com ou sem esquema. Para validar a capacidade de integração dos dados no GeoDrill, foi desenvolvido um experimento para analisar as funcionalidades e o desempenho do mesmo. A solução GeoDrill foi capaz de realizar a integração dos dados espaciais de fontes heterogêneas, apresentando-se como uma alternativa para a resolução de parte das limitações existentes na área. / With the evolution of the web and information systems, organizations have obtained data of various formats, structures and types, specially the spatial one. Due to different characteristics presented in data, such data have been stored in heterogeneous data sources. Therefore, it is needed to increasingly invest in solutions that can integrate and analyze these data from different sources. Some of these solutions can analyze the spatial component of data; however, this analysis of spatial data is limited either by the data type or spatial functions supported. In this work, the problem of spatial data integration from heterogeneous data sources is addressed, either with or without using schemas, using SQL language. This is an open issue in the area of spatial data integration, since existing solutions present many limitations, such as the query language used, the ways to access data, the technologies that can be integrated, the available functions set and the spatial data types supported. Aiming at solving this problem, the GeoDrill solution was developed, which is an extension of the Apache Drill that supports all standard spatial functions provided by the OGC (Open Geospatial Consortium) through the SQL language. The GeoDrill can perform queries on data with or without schema. In order to validate the capacity of GeoDrill to integrate data, an experiment was conducted to analyze its functionalities and performance. The obtained results indicate the GeoDrill solution is able to integrate spatial data from heterogeneous data sources. Hence, it appears to be a suitable alternative for solving part of the existing limitations in this research field.

The Generative Communication (GC) paradigm was introduced in the early 1980s in the form of the Linda coordination and communication language (Gelernter & Bernstein, 1982). The goal of the language was to provide an elegant, intuitive alternative to the state-of-the-art in parallel and distributed processing languages at that time, namely remote procedure calls; message passing systems; and shared memory systems (Gelernter, 1985). Despite the longevity of the Linda coordination language and the GC paradigm, in general, the literature is devoid of meaningful research into the construction and manipulation of dynamic, pointer-based data structures within the context of the GC paradigm. This document motivates the need for such data structures in GC. In addition, this document explores the reasons for the lack literature regarding dynamic pointer-based data structures in GC. Finally, we develop solutions to address the lack of support, within the GC paradigm, for such data structures. / Ph. D.