Dealing with granularity of time in temporal databases

Information Sciences, 1994

In this paper we identify and present three distinct time concepts for precise and lossless information preservation in temporal databases. We provide a formal definition of temporal validity and further extend it to the notion of interpretation-based validity, with which the confusion among various time concepts introduced earlier for temporal databases is resolved. Then, we discuss the problem of preserving multiple past states of a temporal database, which leads to the identification of a maximal set of time concepts. It is shown that the time concept event time is needed to correctly model retroactive and proactive updates, as it is not possible to model them using only the valid and transaction times as thought earlier. We also show the adequacy of three time concepts (event time, along with valid and transaction times) for completely preserving different past states generated by retroactive and proactive updates, error corrections, and delayed updates. In addition, we define the evolution of an object (i.e., object's history) along a single time dimension (valid time) by using temporal and interpretation-based validity. Finally, we sketch the implementation of history for the relational data model. 'Note that the effective time and registration time, similar to the logical time and physical time, respectively, were proposed earlier in [4].

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

Computing Research Repository, 2011

Many works have focused, for over twenty five years, on the integration of the time dimension in databases (DB). However, the standard SQL3 does not yet allow easy definition, manipulation and querying of temporal DBs. In this paper, we study how we can simplify querying and manipulating temporal facts in SQL3, using a model that integrates time in a native manner. To do this, we propose new keywords and syntax to define different temporal versions for many relational operators and functions used in SQL. It then becomes possible to perform various queries and updates appropriate to temporal facts. We illustrate the use of these proposals on many examples from a real application.

1995

ÐGranularity is an integral feature of temporal data. For instance, a person's age is commonly given to the granularity of years and the time of their next airline flight to the granularity of minutes. A granularity creates a discrete image, in terms of granules, of a (possibly continuous) time-line. We present a formal model for granularity in temporal operations that is integrated with temporal indeterminacy, or ªdon't know whenº information. We also minimally extend the syntax and semantics of SQL-92 to support mixed granularities. This support rests on two operations, scale and cast, that move times between granularities, e.g., from days to months. We demonstrate that our solution is practical by showing how granularities can be specified in a modular fashion, and by outlining a time-and space-efficient implementation. The implementation uses several optimization strategies to mitigate the expense of accommodating multiple granularities.

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.

This research try to address several issues related to multiple relations time-stamps temporal databases and the development of temporal databases. A new hash-clustered index structure has been designed to accommodate efficient access for tuples that are indexed on time-stamps. Furthermore, new time intersection equi-join algorithms have been developed. These algorithms have been designed to handle special types of temporal relations, such like continuous and event dependents temporal relations. These algorithms have been implemented and the tests' results prove the correctness of the algorithms.

Eprint Arxiv 1002 1143, 2010

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 incorporates neither the concept of time nor any theory of temporal semantics. Many temporal extensions of the relational model have been proposed and some of them are also implemented. This paper offers a brief introduction to temporal database research. We propose a conceptual model for handling time varying attributes in the relational database model with minimal temporal attributes.

1995

This paper concerns the design of temporal relational database schemas. Normal forms play a central role during the design of conventional relational databases, and we h a ve previously extended all existing relational normal forms to apply to temporal relations. However, these normal forms are all atemporal in nature and do not fully take i n to account the temporal semantics of the attributes of temporal relations. Consequently, additional guidelines for the design of temporal relations are required. This paper presents a systematic study of important aspects of the temporal semantics of attributes. One such aspect is the observation and update patterns of attributes|when an attribute changes value and when the changes are recorded in the database. A related aspect is when the attributes have v alues. A third aspect is the values themselves of attributes|how to derive a v alue for an attribute at any p o i n t in time from stored values. Guidelines for the design of the logical schema of a temporal database are introduced, and implications of the temporal-attribute semantics for the design of views and the physical schema are considered. The Bitemporal Conceptual Data Model, the data model of the consensus temporal query language TSQL2, serves as the context for the study.

ACM Transactions on Database Systems, 1997

The purpose of good database logical design is to eliminate data redundancy and insertion and deletion anomalies. In order to achieve this objective for temporal databases, the notions of temporal types, which formalize time granularities, and temporal functional dependencies (TFDs) are introduced. A temporal type is a monotonic mapping from ticks of time (represented by positive integers) to time sets (represented by subsets of reals) and is used to capture various standard and user-de ned calendars. A TFD is a proper extension of the traditional functional dependency and takes the form X ?! Y , meaning that there is a unique value for Y during one tick of the temporal type for one particular X value. An axiomatization for TFDs is given. Since a nite set of TFDs usually implies an in nite number of TFDs, we introduce the notion of and give an axiomatization for a nite closure to e ectively capture a nite set of implied TFDs that are essential to the logical design. Temporal normalization procedures with respect to TFDs are given. Speci cally, temporal Boyce-Codd normal form (TBCNF) that avoids all data redundancies due to TFDs, and temporal third normal form (T3NF) that allows dependency preservation, are de ned. Both normal forms are proper extensions of their traditional counterparts, BCNF and 3NF. Decomposition algorithms are presented that give lossless TBCNF decompositions and lossless, dependency preserving, T3NF decompositions.

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.