A System Architecture for Temporally Oriented Data Management

Attentiontothetemporalaspectsof datamanagementhasintensifiedinrecentyears,focusing on data models and related systems that are sensitive to the ubiquitous temporal aspects of data. Both the growing need for easier access to historical data, as well as the imminent availability of mass storage devices, are makingthis apromisingbranchof database research, both practically and theoretically. In this paper we summarize the main results of recent research on temporally sensitive data models, discuss the lessons learned in their development, and assess the prospects and dimculties involved in incorporating a temporal dimension into database management systems (TODBs). Inparticular, three system levels are identified: the external userview of the database; an intermediate view closer to the structure of an existing data model; and an internal or implementation view defined interms of low level data structures. This general architecture coherently incorporates a variety of related research results and development experiences, and serves as the framework for theoretical and implementation research into such systems Introduction The underlying pmmise ofthis expandingbodyof research is the recognition that time is not merely another dimension, or another data item tagged along with each tuple, Itseemsnotonlynaturalbutevensomewhattardythatin but rather a more fundamental organizing aspect that our never-ending quest to capture more semantics in humanuserstreatinvery special ways Theresultsofthis formalinformationsystems,we arebeginningtoaugment researchreinforcetheperceptionthatdesigningtemporal our conceptual models with a temporal dimension. Infeatures into information systems requires new and difdeed, there is growing research interest in the nature of ferent conceptual tools time in computer-based information systems and the handling of temporal aspects of data Roughly 50 referA recent panel broughttogether many researchers in the ences to the subject were identified and annotated by field to discuss their work and identify promising research Bolour (1982), addressing four major topical areas: areas (Ariav, 1983 (a)). At the panel, four areas of research were indentified, and in this paper we focus on two of 1. Conceptual data modeling-an extension to these issues namely the implementation of temporal the relational model to incorporate a built-in DBMS and the data models underlying them. semantics for time (Clifford, 1983 (a)). 2. Design and implementation of historical dataInmost existing information systems, aspects of the data bases-the organization of write-once, histhat refer to time are usually either neglected treated torical databases (Aliav, 1981), and implemenonly implicitly, or explicitly factored out ('Ihichritzis, tation of temporally oriented medical databases 1982). None of thethree majordatamodels incorporates (Wiederhold, 1975). a temporal dimension; users of systems based on these models who need temporal information must resort to 3. 'Dynamic databases'-the modeling of patchworksolutionstocircumventthelimitationsoftheir transition rules and temporal inferences from systems. Furthermore, most information systems these rules (May, 1981). typically differentiate between presentand past-related questions in terms of data accessibility (e.g., online and 4. AI related research-the temporal underoffline storage, current database and log tapes.) It is standing of time-oriented data (Kahn, 1975). important to note that this situation prevails not because