A temporal database (see Temporal Database) contains time-varying data. Time is an important aspect of all real-world phenomena. Events occur at specific points in time; objects and the relationships among objects exist over time. The ability to model this temporal dimension of the real world is essential to many computer applications, such as accounting, banking, econometrics, geographical information systems, inventory control, law, medical records, multi-media, process control, reservation systems, and scientific data analysis. Conventional databases represent the state of an enterprise at a single moment of time. Although the contents of the database continue to change as new information is added, these changes are viewed as modifications to the state, with the old, out-of-date data being deleted from the database. The current contents of the database may be viewed as a snapshot of the enterprise. When a conventional database is used, the attributes involving time are manipulated solely by the application programs, with little help

A temporal database contains time-varying data. In a real-time database transactions have deadlines or timing constraints. In this paper we review the substantial research in these two heretofore separate research areas. We first characterize the time domain, then investigate temporal and real-time data models. We evaluate temporal and real-time query languages along several dimensions. Temporal and real-time DBMS implementation is examined. We conclude with a summary of the major accomplishments of the research to date, and list several research questions that should be addressed next. Keywords: object-oriented database, relational databases, query language, temporal data model, time-constrained database, transaction time, user-defined time, valid time 1 Introduction Time is an important aspect of all real-world phenomena. Events occur at specific points in time; objects and the relationships among objects exist over time. The ability to model this temporal dimension of the real worl...

attention has been focused on spatial databases which combine conventional and spatially related data such as Geographic Information Systems, CAD/CAM, or VLSI. A language has been developed to query such spatial databases. It recognizes the significantly different requirements of spatial data handling and overcomes the inherent problems of the application of conventional database query languages. The spatial query language has been designed as a minimal extension to the interrogative part of SQL and distinguishes from previously designed SQL extensions by (1) the preservation of SQL concepts, (2) the highlevel treatment of spatial objects, and (3) the incorporation of spatial operations and relationships. It consists of two components, a query language to describe what information to retrieve and a presentation language to specify how to display query results. Users can ask standard SQL queries to retrieve non-spatial data based on non-spatial constraints, use Spatial SQL commands to inquire about situations involving spatial data, and give instructions in the Graphical Presentation Language GPL to manipulate or examine the graphical presentation. 1 Index Terms—Geographic Information Systems, graphical presentation, query

In valid-time indeterminacy it is known that an event stored in a database did in fact occur, but it is not known exactly when. In this paper we extend the SQL data model and query language to support valid-time indeterminacy. We represent the occurrence time of an event with a set of possible instants, delimiting when the event might have occurred, and a probability distribution over that set. We also describe query language constructs to retrieve information in the presence of indeterminacy. These constructs enable users to specify their credibility in the underlying data and their plausibility in the relationships among that data. A denotational semantics for SQL’s select statement with optional credibility and plausibility constructs is given. We show that this semantics is reliable, in that it never produces incorrect information, is maximal, in that if it were extended to be more informative, the results may not be reliable, and reduces to the previous semantics when there is no indeterminacy. Although the extended data model and query language provide needed modeling capabilities, these extensions appear initially to carry a significant execution cost. A contribution of this paper is to demonstrate that our approach is useful and practical. An efficient representation of valid-time indeterminacy and efficient query processing algorithms are provided. The cost of

Abstract-The size of temporal databases and the semantics cases are subsequently investigated: 1) Dynamic structures for of temporal queries pose challenges for the design of efhcient indexing methods. The primary issues that affect the design of indexing methods are examined, and propose several structures and algorithms for specific cases. Indexing methods for timebased queries are developed, queries on the surrogate or timesurrogate and time indexing (ST); 2) Static and dynamic partitioning algorithms for the time-line in the context of temporal attribute and time indexing; and 3) Time-indexing for append-only database. In all the designs, the focus is on invariant key and time, and temporal attribute and time. In the the role of the time attribute. latter case, several methods are presented that partition the timeline, in order to balance the distribution of tuple-pointers within the index. The methods are analyzed against alternatives, and present appropriate empirical results. Index Terms-Indexing, physical organization, query processing, searching, temporal databases. The paper is organized as follows. In Section II, we discuss the relational representation of data in the temporal context, followed by a framework for analyzing the physical design of a temporal database. In Section III, we introduce the APtree, which is designed for time-based query operations on an append-only database, and is subsequently incorporated into our surrogate-time index of Section IV. In Section V, we I.

In this paper we discuss extensions to the conventional relational algebra to support both aspects of transaction time, evolution of a database’s contents and evolution of a database’s schema. We define a relation’s schema to be the relation’s temporal signature, a function mapping the relation’s attribute names onto their value domains, and class, indicating the extent of support for time. We also introduce commands to change a relation, now defined as a triple consisting of a sequence of classes, a sequence of signatures, and a sequence of states. A semantic type system is required to identify semantically incorrect expressions and to enforce consistency constraints among a relation’s class, signature, and state following update. We show that these extensions are applicable, without change, to historical algebras that support valid time, yielding an algebraic language for the query and update of temporal databases. The additions preserve the useful properties of the conventional algebra. A database’s schema describes the structure of the database; the contents of the database must adhere to that structure [Date 1976, Ullman 1982]. Schema evolution refers to changes to the database’s schema over time. Conventional databases allow only one schema to be in force at a time, requiring restructuring (also termed logical reorganization [Sockut & Goldberg 1979]) when the schema is modified. With the advent of databases storing past states [McKenzie 1986], it becomes desirable to accommodate multiple schemas, each in effect for an interval in the past. Schema versioning refers to retention of past schemas resulting from schema evolution. In an earlier paper [McKenzie & Snodgrass 1987A] we proposed extensions to the conventional relational algebra [Codd 1970] that model the evolution of a database’s contents. We did not, however, consider the evolution of a database’s schema. In this paper, we provide further extensions to the conventional relational algebra that model the evolution of a database’s schema. The extensions that support evolution of a database’s contents are repeated here for completeness and because the extensions supporting schema evolution are best explained in concert with those earlier extensions

This paper provides a systematic and comprehensive study of the underlying semantics of temporal databases, summarizing the results of an intensive collaboration between the two authors over the last five years. We first examine how facts may be associated with time, most prominently with one or more dimensions of valid time and transaction time. One common case is that of a bitemporal relation, in which facts are associated with exactly one valid time and one transaction time. These two times may be related in various ways, yielding temporal specialization. Multiple transaction times arise when a fact is stored in one database, then later replicated or transferred to another database. By retaining the transaction times, termed temporal generalization, the original relation can be effectively queried by referencing only the final relation. We attempt to capture the essence of time-varying information via a very simple data model, the bitemporal conceptual data model. Emphasis is placed...

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The goal of this paper is to present a data model to manage highly variable spatio-temporal data of the real world. The management of such data raises new database problems. These problems are the data volume, the great number of states that database operators have to manipulate, as well as the deficiency of versions that leads to non-determinist temporal queries. To this end, a new approach to represent and to manipulate these data is proposed. The representation model consists in describing how a value evolves in the course of time. We associate semantics to this description. Concerning the manipulation, this descriptive representation is converted into an internal geometric representation. Queries on highly variable data are solved by using geometric algorithm techniques on the geometric representation. The paper reports on this ongoing experiment.

Migrating applications from conventional to temporal database management technology has received scant mention in the research literature. This paper formally defines three increasingly restrictive notions of upward compatibility which capture properties of a temporal SQL with respect to conventional SQL that, when satisfied, provide for a smooth migration of legacy applications to a temporal system. The notions of upward compatibility dictate the semantics of conventional SQL statements and constrain the semantics of extensions to these statements. The paper evaluates the seven extant temporal extensions to SQL, all of which are shown to complicate migration through design decisions that violate one or more of these notions. We then outline how SQL--92 can be systematically extended to become a temporal query language that satisfies all three notions.