Bipolarity in the querying of temporal databases

A database represents part of reality by containing data representing properties of real objects or concepts. To many real-world concepts or objects, time is an essential aspect and thus it should often be (implicitly) represented by databases, making these temporal databases. However, like other data, the time-related data in such databases may also contain imperfections such as uncertainties. One of the main purposes of a database is to allow the retrieval of information or knowledge deduced from its data, which is often done by querying the database. Because users may have both positive and negative preferences, they may want to query a database in a bipolar way. Moreover, their demands may have some temporal aspects. In this paper, a novel technique is presented, to query a valid-time relation containing uncertain valid-time data in a heterogeneously bipolar way, allowing every elementary query constraint a specific temporal constraint

A general treatment of dynamic constraints

This paper introduces a general, formal treatment of dynamic constraints, i.e., constraints on the state changes that are allowed in a given state space. Such dynamic constraints can be seen as representations of "real world" constraints in a managerial context. The notions of transition, reversible and irreversible transition, and transition relation will be introduced. The link with Kripke models (for modal logics) is also made explicit. Several (subtle) examples of dynamic constraints will be given. Some important classes of dynamic constraints in a database context will be identified, e.g. various forms of cumulativity, non-decreasing values, constraints on initial and final values, life cycles, changing life cycles, and transition and constant dependencies. Several properties of these dependencies will be treated. For instance, it turns out that functional dependencies can be considered as "degenerated" transition dependencies. Also, the distinction between primary keys and alternate keys is reexamined, from a dynamic point of view.

Operadores de bases de datos temporales y su implementación

Actualmente, los Sistemas de Gestión de Bases de Datos (SGBD) comerciales no soportan adecuadamente las bases de datos temporales. Por ejemplo, el planteamiento de consultas temporales es difícil de expresar. En este artículo se discuten los aspectos referentes a la implementación de operadores temporales con el fin de facilitar la gestión de los datos temporales en un SGBD. Además, se presenta un caso de estudio para ejemplificar los operadores temporales implementados

Aspects of dealing with imperfect data in temporal databases

In reality, some objects or concepts have properties with a time-variant or time-related nature. Modelling these kinds of objects or concepts in a (relational) database schema is possible, but time-variant and time-related attributes have an impact on the consistency of the entire database. Therefore, temporal database models have been proposed to deal with this. Time itself can be at the source of imprecision, vagueness and uncertainty, since existing time measuring devices are inherently imperfect. Accordingly, human beings manage time using temporal indications and temporal notions, which may contain imprecision, vagueness and uncertainty. However, the imperfection in human-used temporal indications is supported by human interpretation, whereas information systems need extraordinary support for this. Several proposals for dealing with such imperfections when modelling temporal aspects exist. Some of these proposals consider the basis of the system to be the conversion of the specificity of temporal notions between used temporal expressions. Other proposals consider the temporal indications in the used temporal expressions to be the source of imperfection. In this chapter, an overview is given, concerning the basic concepts and issues related to the modelling of time as such or in (relational) database models and the imperfections that may arise during or as a result of this modelling. Next to this, a novel and currently researched technique for handling some of these imperfections is presented

Marking time in sequence mining

Sequence mining is often conducted over static and temporal datasets as well as over collections of events (episodes). More recently, there has also been a focus on the mining of streaming data. However, while many sequences are associated with absolute time values, most sequence mining routines treat time in a relative sense, only returning patterns that can be described in terms of Allen-style relationships (or simpler). In this work we investigate the accommodation of timing marks within the sequence mining process. The paper discusses the opportunities presented and the problems that may be encountered and presents a novel algorithm, INTEMTM, that provides support for timing marks. This enables sequences to be examined not only in respect of the order and occurrence of tokens but also in terms of pace. Algorithmic considerations are discussed and an example provided for the case of polled sensor data.Sydney, NS

Aplicando restricciones en un datawarehouse temporal utilizando UML/OCL

Un datawarehouse es una colección de datos no volátiles, variables en el tiempo y orientado a un tema específico utilizado para tomar decisiones. La necesidad de registrar valores que permitan evaluar tendencias, variaciones, máximos y mínimos, justifican considerar en el diseño la evolución temporal de atributos o interrelaciones. La determinación de restricciones que permitan mantener la consistencia de los datos almacenados e impidan los solapamientos de rangos temporales, permiten conservar la integridad de la base de datos. En la etapa de modelado la determinación de estas restricciones se realizan de manera informal.\nEstablecer sin ambigüedad las mismas no es posible sin un lenguaje apropiado.\nProponemos determinar restricciones en el modelo de datos transformando el esquema multidimensional temporal a UML y emplear OCL para documentar dichas limitaciones.Eje: Ingeniería de Software y Bases de Datos (ISBD