A consensus glossary of temporal database concepts

Temporal Databases: Research and Practice, 1998

Abstract. This document 1 contains definitions of a wide range of concepts specific to and widely used within temporal databases. In addition to providing definitions, the document also includes explanations of concepts as well as discussions of the adopted names. The consensus effort that lead to this glossary was initiated in Early 1992. Earlier versions appeared in SIGMOD Record in September 1992 and March 1994. The present glossary subsumes all the previous documents. The glossary meets the need for creating a higher degree of consensus on ...

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., ...

2004

The paper “Proposed Temporal Database Concepts— May 1993” contained a complete set of glossary entries proposed by members of the temporal database community from Spring 1992 until May 1993. The aim of the proposal was to define a consensus glossary of temporal database concepts and names. Several glossary entries (Section 3) were included in the proposal, but were still unresolved at the time of the deadline. This addendum reflects on-going discussions and contains revised versions of several unresolved entries. The entries here thus supersede the corresponding entries in Section 3 of the proposal.

Sigmod Record, 1994

Temporal databases has been an active area of research for the the last fteen years, with a corpus nearing 800 papers. While most applications need to store time-varying data, there are no widely used commercial temporal databases. A primary reason for the absence of technology transfer from research to practice is the lack of a commonly accepted consensus data model or query language upon which to base research and development. Even the terminology is inconsistent.

Business Intelligence and Big Data, 2018

Despite the ubiquity of temporal data and considerable research on the effective and efficient processing of such data, database systems largely remain designed for processing the current state of some modeled reality. More recently, we have seen an increasing interest in the processing of temporal data that captures multiple states of reality. The SQL:2011 standard incorporates some temporal support, and commercial DBMSs have started to offer temporal functionality in a step-by-step manner, such as the representation of temporal intervals, temporal primary and foreign keys, and the support for so-called time-travel queries that enable access to past states. This tutorial gives an overview of state-of-the-art research results and technologies for storing, managing, and processing temporal data in relational database management systems. Following an introduction that offers a historical perspective, we provide an overview of basic temporal database concepts. Then we survey the state-of-the-art in temporal database research, followed by a coverage of the support for temporal data in the current SQL standard and the extent to which the temporal aspects of the standard are supported by existing systems. The tutorial ends by covering a recently proposed framework that provides comprehensive support for processing temporal data and that has been implemented in PostgreSQL.

2016

All the variable recorded information in the form of raw data which further manipulated and defined in such a way which is meaningful and correlated. These information were recorded at some point in time which may or may not acknowledge the importance of the time at which it has been initiated, processed and terminated. There are uncountable number of databases like medical histories, banking transactions, employee’s database, etc., which are being maintained ever since the mankind evolved and started to keep the record of such information. Time is the key factor to any database created irrespective of its attributes and the values that are being stored in it. This article is consist of the details about the temporal database (TD) and the concepts that shows the functionalities and the importance of the TD in the real world. This article also explains that how the time can further be dissected into smaller versions or granules which has its own significance. Therefore, the main focu...

Several attempts to incorporate temporal extensions into the Structured Query Language, SQL, one of the most popular query languages for databases date back to the nineteenth and twentieth century. Although a lot of work and research has been done on temporal databases and SQL, there exist very limited literature clearly outlining the various events which have taken place with regards to temporal extensions of SQL over the years till the present state in a concise document. Consequently, researchers need to gather several pieces of literature before they can obtain a vivid pictorial timeline of the history and the current state of these temporal extensions for research and software development purposes.

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].

1994

Temporal data. bases has been an active a. rea of research for the last fifteen years, with a corpus nearing 700 papers [Kline93]. Most d&abase conferences include at least one paper on temporal databases (TDB). Temporal databases are now discussed in several undergraduate database textbooks. There are perhaps one hundred researchers actively studying temporal databases.

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.