This thesis researches the problems concerning the specification and implementation of the temporal requirements in data warehouses. The thesis focuses on two areas, firstly, the methods for identifying and capturing the business information needs and associated temporal requirements at the conceptual level and; secondly, methods for classifying and implementing the requirements at the logical level using the relational model. At the conceptual level, eight candidate methodologies were investigated to examine their suitability for the creation of data models that are appropriate for a data warehouse. The methods were evaluated to assess their representation of time, their ability to reflect the dimensional nature of data warehouse models and their simplicity of use. The research found that none of the methods under review fully satisfied the criteria. At the logical level, the research concluded that the methods widely used in current practice result in data structures that are either incapable of answering some very basic questions involving history or that return inaccurate results. Specific proposals are made in three areas. Firstly, a new conceptual model is described that is designed to capture the information requirements for dimensional models and has full support for time. Secondly, a new approach at the logical level is proposed. It provides the data structures that enable the requirements captured in the conceptual model to be implemented, thus enabling the historical questions to be answered simply and accurately. Thirdly, a set of rules is developed to help minimise the inaccuracy caused by time. A guide has been produced that provides practitioners with the tools and instructions on how to implement data warehouses using the methods developed in the thesis.

The aim of this work is to create an application for interconnect diferrences among temporal databases. The main idea of this project is allow user work with languages TSQL2 and ATSQL without user intervention into relation database system. This work also contain implementation of interface JDBC and demonstration application for testing temporal queries.

A Temporal database is one that supports some aspect of time distinct from user defined time. Over the last two decades interest in the field of temporal databases has increased significantly, with contributions from many researchers. However, the lack of efficient access methods is perhaps one of the reasons why commercial RDBMS vendors have been reluctant to adopt the advances in temporal database research. Therefore, an obvious research question is: can we develop more robust and more efficient access methods for temporal databases than the existing ones? This thesis attempts to address this question, and the main contributions of this study are summarised as follows: We investigated different representations of 'now' and how the modelling of current time influences the efficiency of accessing 'now relative' temporal data. A new method, called the 'Point' approach, is proposed. Our approach not only elegantly models the current time but also significantly outperforms the existing methods. We proposed a new index structure, called a Virtual Binary tree (VB-tree), based on spatial representation of interval data and a regular triangular decomposition of this space. Further, we described a sound and complete query algorithm. The performance of the algorithm is then evaluated both asymptotically and experimentally with respect to the state-of-the-art in the field. We claim that the VB-tree requires less space and uses fewer disk accesses than the currently best known structure - the RI-tree.

With the development of wireless communications and mobile computing technologies, the applications of moving objects have been developed in many topics, for example, traffic monitoring, mobile E-Commerce, Navigation System, and Geographic Information System. The feature of the moving objects is that objects change their locations continuously. Conventional spatial databases can not support to store the moving objects efficiently, because the databases must be updated frequently. Therefore, it is important to index moving objects for efficiently answering queries about moving objects. Among the spatial indexing methods for predicting current and future data, the approach of parametric spatial access methods has been applied largely, since it needs little memory space to preserve parametric rectangles, and it still provides good performance, so it is adopted generally. The methods of this approach include the TPR-tree, the TPR*-tree, the Bx-tree, and the Bxr-tree. Among those methods, the Bxr-tree improves CPU performance of TPR-tree by expanding query region first, and improves I/O performance of the Bxr-tree by expanding the data blocks additionally. However, the query process of the B$^x_r$-tree is too rough such that it costs too much CPU and I/O time to check the useless data. Therefore, in this thesis, we propose a new data structure and a new query processing method named Adjustable Expanded Index (AEI), to improve the disadvantages of the Bxr-tree. In our method, we let each block records the maximum and minimum speeds of each of eight directions, instead of only the maximum speed of each of four directions in the Bxr-tree method. Based on the data structure, the query region can be expanded in each of eight directions individually, instead of being expanded in each of four directions once in the Bxr-tree method. Moreover, in our AEI method, the data blocks can be expanded according to the direction toward the query region, instead of being expanded in four directions in the Bxr-tree method. In this way, the query process of AEI checks less number of data blocks because it considers the minimum speed of each of eight directions. Furthermore, the objects are divided into four groups in AEI according to their directions, while the Bxr-tree method does not. Only the objects moving to query region will be checked in the query process of AEI. Therefore, we can reduce more number of retrieved data blocks and the number of I/O operations in our method than the Bxr-tree. From our simulation, we show that the query process of the AEI method is more efficient than that of the Bxr-tree in term of the average numbers of retrieved data blocks and I/O operations.

Há alguns anos, a necessidade de armazenar a história das informações e o período no qual as mesmas são válidas ou não no mundo real, está crescendo. As próprias leis vigentes no país fazem com que isto seja uma necessidade quando, por exemplo, criam uma tabela de tempo de validade para o armazenamento de documentos fiscais ou de recursos humanos. Neste âmbito destaca-se a importância do estudo de modelos de dados temporais que gerenciem este tipo de informação. Tais modelos definem a forma como as informações são organizadas, mantidas e recuperadas. A implementação destes modelos, entretanto, é realizada sobre bancos de dados (BD) convencionais, uma vez que ainda não existe um BD totalmente temporal. O mapeamento de um modelo temporal sobre um convencional não impede que sejam satisfeitas todas as necessidades de representação temporal, desde que seja realizado de forma coerente. As diferentes informações temporais que podem ser utilizadas para a representação de tempo são o tempo de transação e o tempo de validade. Quando se deseja uma representação completa da realidade, utilizam-se bancos de dados bitemporais, através dos quais é possível recuperar todas as informações passadas, presentes e futuras. Este trabalho apresenta o mapeamento de um modelo de dados bitemporal (modelo TF-ORM) para um SGBD convencional (Oracle). Este mapeamento compreende, além das informações temporais, todas as características do modelo, dentre as quais: classes e papéis, mensagens, regras, propriedades dinâmicas e estáticas. É apresentada, ainda, a definição de um gerenciador temporal, o qual busca automatizar o que é implementado. Complementando o estudo realizado, são apresentadas sugestões de operações a serem realizadas pelos desenvolvedores de aplicações temporais quando da manutenção das informações. As operações de inserção, atualização e remoção em uma base temporal são analisadas, independente do tipo de BD temporal implementado. Um estudo de caso é apresentado para validar todas as definições realizadas. / The need for storing the information’s history and the period in which they are still valid in the real world has been growing in the last few years. The very existing laws in the country make it necessary when, for instance, a validity temporal table is created for storing business or human resources documents. Therefore, the study of temporal data models which manage this kind of information has become very important. Such models define the way in which the information is organized, kept and recovered. The implementation of these models, though, is carried out over conventional data bases (DB), once there is no a totally temporal DB. The mapping of a temporal model over a conventional one allows all of its requirements to be met, as long as it is made coherently. The different temporal information that can be used for time representation are the transaction time and the validity time. Whenever a complete representation of the reality is wanted, bitemporal databases are used. These bases make it possible to recover all the past information as well as present and future information. This work presents the mapping of a temporal data model (TF-ORM model) for a conventional DBMS (Oracle). Besides the temporal information, this mapping comprehends all the model’s characteristics, such as: classes and roles, messages, rules, dynamic and static properties. It is also presented a definition of a temporal manager which aims at automating what is implemented. In addition to this study, suggestions of operations to be carried out by the developers of temporal applications for the maintenance of the information are presented. The operations of inserting, updating and removing on temporal base are analyzed, apart from the kind of DB implemented. A case study is presented in order to validate all the definitions made.

Há alguns anos, a necessidade de armazenar a história das informações e o período no qual as mesmas são válidas ou não no mundo real, está crescendo. As próprias leis vigentes no país fazem com que isto seja uma necessidade quando, por exemplo, criam uma tabela de tempo de validade para o armazenamento de documentos fiscais ou de recursos humanos. Neste âmbito destaca-se a importância do estudo de modelos de dados temporais que gerenciem este tipo de informação. Tais modelos definem a forma como as informações são organizadas, mantidas e recuperadas. A implementação destes modelos, entretanto, é realizada sobre bancos de dados (BD) convencionais, uma vez que ainda não existe um BD totalmente temporal. O mapeamento de um modelo temporal sobre um convencional não impede que sejam satisfeitas todas as necessidades de representação temporal, desde que seja realizado de forma coerente. As diferentes informações temporais que podem ser utilizadas para a representação de tempo são o tempo de transação e o tempo de validade. Quando se deseja uma representação completa da realidade, utilizam-se bancos de dados bitemporais, através dos quais é possível recuperar todas as informações passadas, presentes e futuras. Este trabalho apresenta o mapeamento de um modelo de dados bitemporal (modelo TF-ORM) para um SGBD convencional (Oracle). Este mapeamento compreende, além das informações temporais, todas as características do modelo, dentre as quais: classes e papéis, mensagens, regras, propriedades dinâmicas e estáticas. É apresentada, ainda, a definição de um gerenciador temporal, o qual busca automatizar o que é implementado. Complementando o estudo realizado, são apresentadas sugestões de operações a serem realizadas pelos desenvolvedores de aplicações temporais quando da manutenção das informações. As operações de inserção, atualização e remoção em uma base temporal são analisadas, independente do tipo de BD temporal implementado. Um estudo de caso é apresentado para validar todas as definições realizadas. / The need for storing the information’s history and the period in which they are still valid in the real world has been growing in the last few years. The very existing laws in the country make it necessary when, for instance, a validity temporal table is created for storing business or human resources documents. Therefore, the study of temporal data models which manage this kind of information has become very important. Such models define the way in which the information is organized, kept and recovered. The implementation of these models, though, is carried out over conventional data bases (DB), once there is no a totally temporal DB. The mapping of a temporal model over a conventional one allows all of its requirements to be met, as long as it is made coherently. The different temporal information that can be used for time representation are the transaction time and the validity time. Whenever a complete representation of the reality is wanted, bitemporal databases are used. These bases make it possible to recover all the past information as well as present and future information. This work presents the mapping of a temporal data model (TF-ORM model) for a conventional DBMS (Oracle). Besides the temporal information, this mapping comprehends all the model’s characteristics, such as: classes and roles, messages, rules, dynamic and static properties. It is also presented a definition of a temporal manager which aims at automating what is implemented. In addition to this study, suggestions of operations to be carried out by the developers of temporal applications for the maintenance of the information are presented. The operations of inserting, updating and removing on temporal base are analyzed, apart from the kind of DB implemented. A case study is presented in order to validate all the definitions made.

Há alguns anos, a necessidade de armazenar a história das informações e o período no qual as mesmas são válidas ou não no mundo real, está crescendo. As próprias leis vigentes no país fazem com que isto seja uma necessidade quando, por exemplo, criam uma tabela de tempo de validade para o armazenamento de documentos fiscais ou de recursos humanos. Neste âmbito destaca-se a importância do estudo de modelos de dados temporais que gerenciem este tipo de informação. Tais modelos definem a forma como as informações são organizadas, mantidas e recuperadas. A implementação destes modelos, entretanto, é realizada sobre bancos de dados (BD) convencionais, uma vez que ainda não existe um BD totalmente temporal. O mapeamento de um modelo temporal sobre um convencional não impede que sejam satisfeitas todas as necessidades de representação temporal, desde que seja realizado de forma coerente. As diferentes informações temporais que podem ser utilizadas para a representação de tempo são o tempo de transação e o tempo de validade. Quando se deseja uma representação completa da realidade, utilizam-se bancos de dados bitemporais, através dos quais é possível recuperar todas as informações passadas, presentes e futuras. Este trabalho apresenta o mapeamento de um modelo de dados bitemporal (modelo TF-ORM) para um SGBD convencional (Oracle). Este mapeamento compreende, além das informações temporais, todas as características do modelo, dentre as quais: classes e papéis, mensagens, regras, propriedades dinâmicas e estáticas. É apresentada, ainda, a definição de um gerenciador temporal, o qual busca automatizar o que é implementado. Complementando o estudo realizado, são apresentadas sugestões de operações a serem realizadas pelos desenvolvedores de aplicações temporais quando da manutenção das informações. As operações de inserção, atualização e remoção em uma base temporal são analisadas, independente do tipo de BD temporal implementado. Um estudo de caso é apresentado para validar todas as definições realizadas. / The need for storing the information’s history and the period in which they are still valid in the real world has been growing in the last few years. The very existing laws in the country make it necessary when, for instance, a validity temporal table is created for storing business or human resources documents. Therefore, the study of temporal data models which manage this kind of information has become very important. Such models define the way in which the information is organized, kept and recovered. The implementation of these models, though, is carried out over conventional data bases (DB), once there is no a totally temporal DB. The mapping of a temporal model over a conventional one allows all of its requirements to be met, as long as it is made coherently. The different temporal information that can be used for time representation are the transaction time and the validity time. Whenever a complete representation of the reality is wanted, bitemporal databases are used. These bases make it possible to recover all the past information as well as present and future information. This work presents the mapping of a temporal data model (TF-ORM model) for a conventional DBMS (Oracle). Besides the temporal information, this mapping comprehends all the model’s characteristics, such as: classes and roles, messages, rules, dynamic and static properties. It is also presented a definition of a temporal manager which aims at automating what is implemented. In addition to this study, suggestions of operations to be carried out by the developers of temporal applications for the maintenance of the information are presented. The operations of inserting, updating and removing on temporal base are analyzed, apart from the kind of DB implemented. A case study is presented in order to validate all the definitions made.

La croissance rapide et la complexité de nombreuses villes contemporaines offrent de nombreux défis de recherche pour les scientifiques à la recherche d'une meilleure compréhension des mobilités qui se produisent dans l'espace et dans le temps. A l’heure où de très grandes séries de données de trajectoires en milieu urbain sont disponibles grâce à profusion de nombreux capteurs de positionnement et de services de nombreuses et nouvelles opportunités de recherche et d’application nous sont offertes. Cependant, une bonne intégration de ces données de mobilité nécessite encore l'élaboration de cadres méthodologiques et conceptuels tout comme la mise en oeuvre de bases de données spatio-temporelles qui offriront les capacités appropriées de représentation et de manipulation des données. La recherche développée dans cette thèse introduit une modélisation conceptuelle et une approche de gestion de base de données spatio-temporelles pour représenter et analyser des trajectoires humaines dans des espaces urbains. Le modèle considère les dimensions spatiales, temporelles et sémantiques afin de tenir compte de l’ensemble des propriétés issues des informations de mobilité. Plusieurs abstractions de données de mobilité et des outils de manipulation de données sont développés et expérimentés à partir d’une large base de données de trajectoires disponibles dans la ville de Pékin. L'intérêt de l'approche est double: il montre d’une part que de larges ensembles de données de mobilité peuvent être intégrés au sein de SGBD spatiotemporels extensibles; d’autre part des outils de manipulation et d’interrogation spécifiques peuvent être dérivés à partir de fonctions intégrées au sein d’un langage d’interrogation. Le potentiel de l’approche est illustré par une série d’interrogations qui montrent comment à partir d’une large base de données de trajectoires quelques patrons de déplacements peuvent être obtenus. / Massive trajectory datasets generated in modern cities generate not only novel research opportunities but also important methodological challenges for academics and decision-makers searching for a better understanding of travel patterns in space and time. This PhD research is oriented towards the conceptual and GIS-based modeling of human displacements derived from large sets of urban trajectories. The motivation behind this study originates from the necessity to search for and explore travel patterns that emerge from citizens acting in the city. Our research introduces a conceptual modelling framework whose objective is to integrate and analyze human displacements within a GIS-based practical solution. The framework combines conceptual and logical models that represent travel trajectories of citizens moving in a given city. The whole approach has been implemented in a geographical database system, experimented in the context of transportation data, and enriched by a series of query interface manipulations and specific functions that illustrate the potential of our whole framework for urban studies. The whole framework has been experimented on top of the Geolife project and large trajectories datasets available in the city of Beijing. Overall, the findings are twofold: first, it appears that our modelling framework can appropriately act as an extensible geographical database support for the integration of large trajectory datasets; second the approach shows that several emerging human displacements can be explored from the manipulation of large urban trajectories.

This thesis is focused on PostgreSQL database system. You can find here introducing to temporal databases, database system PostgreSQL, proposal of temporal extension for PostgreSQL and implementation chapter with examples of using this extension. In this thesis is also using temporal database systems and use temporal databases in practise.

The content of this thesis is devided into five parts. Firstly basic principles, data models and some languages of temporal databases are introduced. Next chapter describes ways and techniques for persistent storing of data objects in the programming language Java. Following chapters contain main ideas and key concepts of the Java Data Objects standard, draft for temporal extension of this standard and in the final chapter there are details of the actual implementation.