Aspects of Dealing with Imperfect Data in Temporal Databases

Statistical and Scientific Database Management, 1988

In previous work, we introduced a data model and a query language for temporal data. The model was designed independently of any existing data model rather than an extension of one. This approach provided an insight into the special requirements for handling temporal data. In this paper, we discuss the implications of supporting such a model in the relational database

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.

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.

A minimal extension of relational data model for logical modeling of the category of time in databases is offered. The time is considered as a totally ordered set. In the frame of suggested datamodel the homogeneous model of representation of time in relations is adopted. Allowing the homogeneity, the modeling of the temporal aspect of databases is achieved by means of two temporal attributes. The temporal attribute is considered as abstract data type. A formal definition of temporal relation which is based on abstraction of generalization is given. The semantics of operators update and delete is changed. A temporal algebra and calculus are developed. Also new aggregate functions are suggested considering the time aspect of the object behavior in the given enterprise. In order to give temporal integrity constrains closed formulas are used. The problems of partial support of evolution of the database schemes are considered.

IEEE Transactions on Knowledge and Data Engineering, 2004

The analysis of the semantics of temporal data and queries plays a central role in the area of temporal databases. Although many different algebrae and models have been proposed, almost all of them are based on a point-based (snapshot) semantics for data. On the other hand, in the areas of linguistics, philosophy, and, recently, artificial intelligence, an oft-debated issue concerns the use of an interval-based versus a point-based semantics. In this paper, we first show some problems inherent in the adoption of a point-based semantics for data, then argue that these problems arise because there is no distinction drawn in the data between telic and atelic facts. We then introduce a three-sorted temporal model and algebra including coercion functions for transforming relations of one sort into relations of the other at query time which properly copes with these issues.

A minimal extension of relational data model for logical modeling of the category of time in databases is offered. The time is considered as a totally ordered set. In the frame of suggested data model the homogeneous model of representation of time in relations is adopted. Allowing the homogeneity, the modeling of the temporal aspect of databases is achieved by means of two temporal attributes. The temporal attribute is considered as abstract data type. A formal definition of temporal relation which is based on abstraction of generalization is given. The semantics of operators update and delete is changed. A temporal algebra and calculus are developed. Also new aggregate functions are suggested considering the time aspect of the object behavior in the given enterprise. In order to give temporal integrity constrains closed formulas are used. The problems of partial support of evolution of the database schemes are considered.

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.

10th International Symposium on Temporal Representation and Reasoning, 2003 and Fourth International Conference on Temporal Logic. Proceedings., 2003

In bitemporal databases, current facts and transaction states are modelled using a special value to represent the current time (such as a minimum or maximum timestamp or NULL). Previous studies indicate that the choice of value for now (i.e. the current time) significantly influences the efficiency of accessing bitemporal data. This paper introduces a new approach to represent now, in which current tuples and facts are represented as points on the transaction time and valid time line respectively. This allows us to exploit the computational advantages of point-based query languages. Via an empirical study, we demonstrate that our new approach to representing now offers considerable performance benefits over existing techniques for accessing bitemporal data.

1998

Abstract Data explicitly stored in a temporal database are often associated with certain semantic assumptions. Each assumption can be viewed as a way of deriving implicit information from explicitly stored data. Rather than leaving the task of deriving (possibly infinite) implicit data to application programs, as is the case currently, it is desirable that this be handled by the database management system. To achieve this, the paper formalizes and studies two types of semantic assumptions: point based and interval based.

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.

2008

Abstract Temporal knowledge representation and reasoning is a major research field in Artificial Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to model and process time and calendar data is essential for many applications like appointment scheduling, planning, Web services, temporal and active database systems, adaptive Web applications, and mobile computing applications. This article aims at three complementary goals.

Arxiv preprint arXiv:1002.1143, 2010

Abstract: Time is one of the most difficult aspects to handle in real world applications such as database systems. Relational database management systems proposed by Codd offer very little built-in query language support for temporal data management. The model itself ...

Lecture Notes in Computer Science, 2019

Temporal data given by users are often imprecise. In this paper, we propose an approach to represent and reason about temporal relations between imprecise time intervals which are classical time intervals characterized by gradual beginnings and/or endings. It is mainly based on extending the Allen's interval algebra. It is not only suitable to express precise temporal interval relations (e.g., "Before") but also imprecise personalized ones (e.g., "Just Before"). Compared to related work, our imprecise relations are personalized, in the sense that they are not limited to a given number and their meanings are determined by a domain expert. For instance, the classic Allen's relation "Before" may be generalized in 5 imprecise relations, where "Before (1) " means "just before" and gradually the time gap between the two intervals increases until "Before (5) " which means "too long before". Our imprecise personalized relations are based on our extension of the Vilain and Kautz's point algebra. We showed that, unlike most related work, our temporal interval relations preserve many of the properties of the Allen's interval algebra. Furthermore, we show how they can be used for temporal reasoning by means of a transitivity table. Finally, our approach is applied to the Semantic Web. We propose a fuzzy ontology-based prototype. Inferences are done via a set of SWRL and fuzzy IF-THEN rules. We illustrate the usefulness of our approach in the context of an ontology-based memory prosthesis for Alzheimer's patients. Keywords: Imprecise time interval Á Temporal interval relation Á Temporal reasoning Á Allen's interval algebra Á Semantic Web Á Fuzzy ontology

1993

This document contains the complete set of glossary entries proposed by members of the temporal database community from Spring 1992 until May 1993. It is part of an initiative aimed at establishing an infrastructure for temporal databases. As such, the proposed concepts will be discussed during “International Workshop on an Infrastructure for Temporal Databases,” in Arlington, TX, June 1993, with the specific purpose of defining a consensus glossary of temporal database concepts and names. Earlier status documents appeared in March 1993 and December 1992 and included terms proposed after an initial glossary appeared in SIGMOD Record in September 1992. This document subsumes all the ∗Correspondence may be directed to the TSQL electronic mail distribution, [email protected], or to the editor at Aalborg University, Datalogi, Fr. Bajers Vej 7E, DK–9220 Aalborg Ø, Denmark, [email protected]. Affiliations and e-mail addresses of the authors follow. J. Clifford, Information Systems Dept., ...