Academia.edu no longer supports Internet Explorer.
To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser.
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...
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.
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 ...
2018
Despite the ubiquity of temporal data and considerable research on processing 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 processing historical or temporal data. The SQL:2011 standard introduced some temporal features, and commercial database management systems have started to offer temporal functionalities in a step-by-step manner. There has also been a proposal for a more fundamental and comprehensive solution for sequenced temporal queries, which allows a tight integration into relational database systems, thereby taking advantage of existing query optimization and evaluation technologies. New challenges for processing temporal data arise with multiple dimensions of time and the increasing amounts of data, including time series data that represent a special kind of temporal data.
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.
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].
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.
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.
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.
10th International Symposium on Temporal Representation and Reasoning, 2003 and Fourth International Conference on Temporal Logic. Proceedings., 2003
Abstract In bitemporal databases, current facts and transaction states are modeled 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 (ie the current time) ...
2007
Researches concerning Temporal Databases are being developed for more than 20 years. However, very few implemented systems are available. Several temporal data models were proposed, extending traditional data models in a way to capture also the temporal features. A feasible way of implementing a Temporal Database is using a conventional commercial database mapping the temporal data model to it. This mapping shall provide the explicit representation of the temporal information related to the intended temporal data model. A Temporal Management System is presented in this paper. Data and rules related to a temporal data model are managed by this system, implemented on a conventional DBMS.
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.
2010
Temporal data management is a concept that has been around for many years. A temporal data management system (TDMS) manages data that is tracked over time. In this paper, the authors present an Oracle-based implementation of a TDMS that provides access to temporal data. The design and implementation presented in this paper are presented at a high level, with the significant features such as reference intervals and temporal relationships. The most notable TDMS benefits are a semi-portable solution and an implementation that maximizes on native database features. The paper finally presents an evaluation of the TDMS implementation with a feature comparison and benchmarking.
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.
Time based data is efficiently managed by temporal database models whereas the conventional database models are only capable of storing the present value, temporal database models not only stores historic values but also provide a roadmap to process future valid data. This paper briefly introduces some vital temporal database concepts. After that, various attribute time stamping models are examined in this domain. Finally, a comparative analysis of the various attribute timestamp models is prepared to discuss their strengths and weaknesses of their Implementations and provide useful and optimised results for solving the problems in the field of the temporal database model.
1994
Abstract In this paper we describe an implementation of a temporal relational database management system based on attribute timestamping. For this purpose we modify an existing software 6] which supports set-valued attributes. The algebraic language of the system includes relational algebra operators, restructuring operators and temporal operators.
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.
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.