Shashi K. Gadia

A homogeneous relational model and query languages for temporal databases

In a temporal database, time values are associated with data item to indicate their periods of validity. We propose a model for temporal databases within the framework of the classical database theory. Our model is realized as a temporal parameterization of static relations. We do not impose any restrictions upon the schemes of temporal relations. The classical concepts of normal forms and dependencies are easily extended to our model, allowing a suitable design for a database scheme. We present a relational algebra and a tuple calculus for our model and prove their equivalence. Our data model is homogeneous in the sense that the periods of validity of all the attributes in a given tuple of a temporal relation are identical. We discuss how to relax the homogeneity requirement to extend the application domain of our approach.

A glossary of temporal database concepts

This glossary contains concepts specific to temporal databases that are well-defined, well understood, and widely used. In addition to defining and naming the concepts, the glossary also explains the decisions made. It lists competing alternatives and discusses the pros and cons of these. It also includes evaluation criteria for the naming of concepts. This paper is a structured presentation of the results of e-mail discussions initiated during the preparation of the first book on temporal databases, Temporal Databases: Theory, Design, and Implementation, published by Benjamin Cummings, to appear January 1993. Independently of the book, an initiative aimed at designing a consensus Temporal SQL is under way. The paper is a contribution towards establishing common terminology, an initial subtask of this initiative.

A generalized model for a relational temporal database

We propose a generalized relational model for a temporal database which allows time stamping with respect to a Boolean algebra of multidimensional time stamps. The interplay between the various temporal dimensions is symmetric. As an application, a two dimensional model which allows objects with real world and transaction oriented time stamps is discussed. The two dimensional model can be used to query the past states of the database. It can also be used to give a precise classification of the errors and updates in a database, and is a promising approach for querying these errors and updates.

A Brief Review on Leading Big Data Models

Today, science is passing through an era of transformation, where the inundation of data, dubbed data deluge is influencing the decision making process. The science is driven by the data and is being termed as data science. In this internet age, the volume of the data has grown up to petabytes, and this large, complex, structured or unstructured, and heterogeneous data in the form of “Big Data” has gained significant attention. The rapid pace of data growth through various disparate sources, especially social media such as Facebook, has seriously challenged the data analytic capabilities of traditional relational databases. The velocity of the expansion of the amount of data gives rise to a complete paradigm shift in how new age data is processed. Confidence in the data engineering of the existing data processing systems is gradually fading whereas the capabilities of the new techniques for capturing, storing, visualizing, and analyzing data are evolving. In this review paper, we discuss some of the modern Big Data models that are leading contributors in the NoSQL era and claim to address Big Data challenges in reliable and efficient ways. Also, we take the potential of Big Data into consideration and try to reshape the original operationaloriented definition of “Big Science” (Furner, 2003) into a new data-driven definition and rephrase it as “The science that deals with Big Data is Big Science.”

A pattern matching language for spatio-temporal databases

We propose a pattern matching language for spatio-temporal databases. The matching process in time dimension is based upon the evolutionary nature of time, but in spatial dimension it is based on placement, shape and sizes of regions. The concept of pattern matching introduced in this paper is independent of the choice of the underlying model for spatio-temporal databases. In particular, the pattern matching language seamlessly extends our SQL-like query language ParaSQL for spatio-temporal databases. The pattern matching language would also have application in active databases, because patterns can be used as triggers.

Toward a multihomogeheous model for a temporal database

In a conventional database, out of date information is deleted from time to time to keep the database up-to-date. In some applications it is not appropriate to discard old information. In a temporal database, time values are associated with each data item to indicate its period of validity. We propose a model for temporal databases within the framework of classical relational database theory. Our basic model is homogeneous in the sense that the periods of validity of all the attributes in a given tuple of a temporal relation are identical. The model is realized as a temporal parameterization of static relations. The concepts of normal forms, dependencies, etc., can be extended to our model, allowing the proper initial structuring of the database. We develop relational algebra and tuple calculus for our model and prove their equivalence. We generalize the homogeneous model to a multihomogeneous model which allows us to model a significant part of the real world.

Relational database systems with zero information loss

Transaction time is used for time stamping object values to record their database history and formulate a zero information loss model for database transactions. The model consists of three components, a data history store, an update store, and a query store. In such a model, the effect of a past transaction (a query or an update) can be determined at any time. Additionally, the update and query stores make it possible to reconstruct the circumstances of updates and the information divulged in queries. Such a model is suitable for the design of secure, easy-to-audit database systems. >

Weak temporal relations

In modeling temporal databases, one essentially time stamps all the atomic data elements. As long as this time stamping is not altered, the information content, in some sense, remains unchanged. This observation gives rise to an interesting concept of a weak temporal rala-tion and weak equality. We discuss several semantics for algebraic operatora on certain homogeneous temporal relations, and prove their equivalence in the sense of weak equality. It follows that a user may be allowed the freedom of viewing the relations in any one of the three ways, and the machine can possibly store them differently.

Inadequacy of interval timestamps in temporal databases

Abstract In a temporal database, the value of an attribute is timestamped to indicate its period of validity in the real world. Two data types for timestamps have evolved: an interval, and a finite union of intervals called a temporal element. The use of intervals as timestamps splits the history of an object across several first normal form (1nf) tuples, but the use of temporal elements allows the entire history of an object to be captured into a single non-1nf tuple. According to the form of the tuple thus obtained, the two approaches may be called the 1nf approach and the non-1nf approach. We believe that the latter approach is superior. The query language TQUEL , based upon the 1nf approach, is perhaps the most well known of all temporal query languages. To make a comparison between the two approaches, we introduce a non-1nf tuple calculus, called TCAL , and compare it with TQUEL . We show that the retrieve statement of TQUEL is weaker than its counterpart in TCAL . We also argue that TQUEL is not as user friendly as TCAL . Our remarks also apply to other temporal query languages, such as TSQL , where the timestamps are intervals.

A Relational Model and SQL-like Query Language for Spatial Databases

Spatial databases have experienced enormous growth in application environments, such as agriculture, environmental studies, geography, geology, city-planning, aerospace industry etc. More recently spatial databases have attracted attention in the database community. A considerable research has been done in physical implementation of spatial databases. This is particularly true of access methods for spatial data [238, 483, 512, 230, 231, 39, 506]. On the other hand, abstract modeling and querying of spatial data have received relatively less attention. The need for such a study becomes even more important because of diverse techniques proposed for representing spatial regions. Like [440] we favor that the logical view and the physical implementation of spatial data should be considered orthogonal issues. The users should be given a simple view of data and freed of the worry of how it is physically represented. This is even more important because physical implementation will continue to be a topic of study for quite some time to come. Conventional database techniques are inadequate in spatial databases because of the spatial structure implicit in spatial querying. We present a model and an SQL-like query language called SpaSQL (read space-Q-L) for spatial data. Without tying ourselves down to a choice of representation of spatial regions, we propose certain desirable closure properties for them to make SpaSQL seamless.