Time-oriented data model

1998

Abstract Most database research on modeling time has concentrated on the definition of a particular temporal model and its incorporation into a (relational or object) database management system. This has resulted in quite a large number of different temporal models, each providing a specific set of temporal features. This paper presents an object-oriented framework for temporal models which supports multiple notions of time.

1998

Most of the database research on modeling time has concentrated on the definition of a particular temporal model and its incorporation into a (relational or object) database management system. This has resulted in quite a large number of different temporal models, each providing a specific set of temporal features. Therefore, the first step of this work is a design space for temporal models which accommodates multiple notions of time, thereby classifying design alternatives for temporal models.

Lecture Notes in Computer Science, 1998

Database applications are frequently faced with the necessity of representing time varying information and, particularly in the management of information systems, a few kinds of behavior in time can characterize a wide class of applications. A great amount o f w ork in the area of temporal databases aiming at the de nition of standard representation and manipulation of time, mainly in relational database environment, has been presented in the last years. Nevertheless, conceptual design of databases with temporal aspects has not yet received su cient attention. The purpose of this paper is twofold: to propose a simple temporal treatment of information at the initial conceptual phase of database design; to show h o w the chosen temporal treatment can be exploited in time integrity enforcement b y using standard DBMS tools, such as referential integrity and triggers. Furthermore, we present a design tool implementing our data model and constraint generation technique, obtained by extending a commercial design tool.

2003

ABSTRACT Relaxing the First Normal Form (1NF) assumption of relational databases gives rise to Non-First Normal Form relations or nested relations for short. Nested relations overcome a number of problems that the apparently reasonable restriction of 1NF condition causes. The need to support time in database systems, in order to model temporal events in the real world, has been addressed over the last two decades, reflecting the importance of that for almost every computer system application.

Decision Support Systems, 1995

Although widely advocated as a tool for the conceptual modelling of data, the Entity-Relationship (E-R) model and its extensions are generally lacking in constructs to model the dynamic nature of the real world, making them inadequate for designing temporal databases. This research first extends the E-R model to a Temporal Event-Entity-Relationship Model (TEERM), by introducing events as an additional construct. Second, a method is proposed for mapping this conceptual model into a temporal relational model for the logical design of temporal relational databases with a corresponding set of integrity constraints. The model is illustrated with an example and evaluated using a set of criteria proposed by Batini et al. [2]. The model appears to be expressive, simple and easy to use, and should, therefore, aid the temporal database design process significantly.

Information Systems, 1991

Arguably the most critical of all activities in the development of an information system is that of requirements modelling. The effectiveness of such a specification depends largely on the ability of the chosen conceptual model to represent the problem domain in such a way so as to permit natural and rigorous descriptions within a methodological framework. Recent years have witnessed an increased demand for information systems which cover a wide spectrum of application domains. This, inevitably, has had the effect of demanding conceptual models of enhanced functionality and expressive power than is currently possible in practice. This paper introduces the TEMPORA modelling paradigm for developing information system applications from a unified perspective which deals with definitional, intentional and constrain knowledge. The paper discusses in detail one of the components of the TEMPORA conceptual model, the entity-relationshiptime (ERT) model, which deals with structural aspects including time and complex objects modelling.

1997

Abstract Temporal databases are an active and fast growing research area. Although many temporal extensions of the relational data model have been proposed, there is no comparable amount of work in the context of object-oriented data models. Moreover, few of the proposed models have been implemented. This report discusses how the temporal data model developed for T Chimera 4] has been implemented on top of the Ode OODBMS 1]. In particular, two di erent approaches to handle temporal data are investigated.

Data & Knowledge Engineering, 2006

The algebra (TNA) of a generalised temporal database model supporting temporal relations nested to any finite depth is presented. The temporal nested relations consist of temporal nested attributes which are formed from temporal attributes together with the corresponding time-varying attributes. Therefore, the temporal dimension of the model is nested and is not integral with the corresponding time-dependent value. All the operations of the algebra are defined recursively and are proved to be closed. In particular, considering the natural join operation for temporal nested relations, different cases are presented, distinguished by the types and the nesting levels of the common attributes that participate in the natural join operation.

Open Computer Science, 2014

Temporal database is an extension of the concept of standard databases which process only current valid data. Temporal structure is not based only on managing historical data, but it should also model the data, the validity of which will be in the future in special structures. This paper deals with the temporal structure on object level in comparison with the column level temporal data. It describes the principles, required methods, procedures, functions and triggers to provide the functionality of this system. It also defines the possible implementations and offers the solution to get the snapshot of the database or the object whenever during the existence. The reason for column level solution development is based on the heterogeneity of the attributes time. Some attributes, however, do not change their values over the time or are updated very rarely, and therefore it is not necessary to record the new values for these attributes.

1995

Based on a systematic study of the semantics of temporal attributes of entities, this paper provides new guidelines for the design of temporal relational databases. The notions of observation and update patterns of an attribute capture when the attribute changes value and when the changes are recorded in the database. A lifespan describes when an attribute has a value. And derivation functions describe how the values of an attribute for all times within its lifespan are computed from stored values. The implications for temporal database design of the semantics that may be captured using these concepts are formulated as schema decomposition rules.