The problem presented is how to handle encoded data for which the encodings or decodings change with respect to time, and which contains codes indicating that certain data is unknown, invalid, or not applicable with respect to certain entities during certain time periods. It is desirable to build a database management system that is capable of knowing about and being able to handle the changes in encodings and the missing information codes by embedding such knowledge in the data definition structure, in order to remove the necessity of having applications programmers and users constantly worrying about how the data is encoded. The experimental database management language DEFINE is utilized to achieve the desired result, and a database structure is created for a real-life example of data which contains many examples of time-variant encodings and missing information. / Science, Faculty of / Computer Science, Department of / Graduate

A new data base independent query language for relational systems is presented. Queries in this language specify only properties of the data which is to be retrieved. An algorithm for reducing queries to a response relation is described. This reduction algorithm makes use of Micro-Planner to decide which relations in the data base are applicable to the query, and how these relations should be manipulated. A semantic model is used as the basis for this work. This query language is also compared with existing languages. / Science, Faculty of / Computer Science, Department of / Graduate

The object of this study was to survey large Canadian organizations in order to: 1) determine the extent to which these organizations have established a separate Data Administration function, 2) empirically test Nolan's Stage Model of EDP Growth as a predictor of a separate Data Administration function, and 3) survey the characteristics of the Data Administration function in those organizations that have formally established such a speciality. A survey package containing two questionnaires was sent to 555 large Canadian organizations in the private and public sectors. The "EDP Profile Questionnaire" was directed to the Manager of the EDP Activity in the surveyed organizations. This questionnaire is concerned with the EDP growth process and the existence of a Data Administrator. The "Data Administration Questionnaire" was directed to the Data Administrator in the surveyed organizations. This questionnaire is concerned with the characteristics and responsibilities of the Data Administration function. Analysis was performed on 254 EDP functions and 69 Data Administration functions. The results obtained indicate that the Data Administration function is not prevalent in large Canadian organizations; where the function does exist its role is a fairly minor one within the EDP activity. This study found that organizations with very large EDP activities and many years of experience with computers were more likely to have established a Data Administration function than-smaller and less experienced ones. Certain organizational types (those with discretionary funds available) were more likely, to have a Data Administration function than other types. The "maturity" of the organization's EDP activity was not found to be- a good predictor of the existence of a Data Administrator. The sampled Data Administration functions exhibited a wide dispersion in both the activities performed and the amount of time spent on each. Few policy setting activities were performed by the Data Administrators. The Data Administration function appeared to be focused on those "data bases" using a Data Base Management System. Organizational conflicts and a general misunderstanding of the function by EDP Management have likely held back the development of the function beyond one involved primarily with the support of DBMS application systems. Future research should be directed at- understanding these conflicts and misperceptions through an analysis of the decision process involved in establishing the Data Administration function. An attempt- should be made to more fully understand the data resource and how it might differ among organizational types. Before further use is made of Nolan's Stage Growth model, serious thought should be given to determining in more precise terms what the EDP growth process variables are and how they might best be measured. / Business, Sauder School of / Graduate

Any design of an access path level of a database management system must make allowance for physical reorganization requirements. The facilities provided for such requirements at the access path level have so far been primitive in nature (almost always, in fact, requiring complicated human intervention)This thesis begins to explore the notion of increasing the degree of automation of such requirements at the access path level; to consider the practical basis for self-adapting or self-organizing data management systems. Consideration is first given to the motivation (justification) of such a notion. Then, based on a review of the relevant aspects of a number of existing data management systems, we present a complete design specification and outline for a proposed access path level. Regarding this system we consider in detail the automation of two major aspects of physical organization: the clustering of records on mass storage media and the selection of secondary indices. The results of our analysis of these problems provides a basis for the ultimate demonstration of feasibility of such automation. / Science, Faculty of / Computer Science, Department of / Graduate

Master of Science

see document / Master of Science

Obtaining low-latency results from window-aggregate queries can be critical to certain data-stream processing applications. Due to a DSMS's lack of control over incoming data (typically, because of delays and bursts in data arrival), timely results for a window-aggregate query over a data stream cannot be obtained with guarantees about the results' accuracy. In this thesis, I propose a technique, which I term prodding, to obtain early result estimates for window-aggregate queries over data streams. The early estimates are obtained in addition to the regular query results. The proposed technique aims to maximize the contribution to a result-estimate computation from all the stateful operators across a multi-level query plan. I evaluate the benefits of prodding using real-world and generated data streams having different patterns in data arrival and data values. I conclude that, in various DSMS applications, prodding can generate low-latency estimates to window-aggregate query results. The main factors affecting the degree of inaccuracy in such estimates are: the aggregate function used in a query, the patterns in arrivals and values of stream data, and the aggressiveness of demanding the estimates. The utility of the estimates obtained using prodding should be optimized by tuning the aggressiveness in result-estimate demands to the specific latency and accuracy needs of a business, considering any available knowledge about patterns in the incoming data.

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