In 2005 Mr. Dung Tien Vu completed a master's project for the California State University, San Bernardino Computer Science Department in which he designed a web-based database of department graduate student information. This project was designed to alter the system so that it conforms with current campus regulations, to make some improvements to the system, and to deploy it.

published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

As more and more of information systems develop into large scale web applications, the complexity of multiple possible stakeholders and users multiplies. Web engineering methodologies although developing, are still primarily addressing the technical and functional issues in these large systems. The thesis addresses the web information system development from a social-psychological viewpoint to find ways to better match the user with system development. This thesis proposes a methodology to apply adoption theory into web application development. The hypothesis being that this is another way to enhance the utilisation of the system by the users. A thorough review of both adoption theory and adoption models showed that existing models are more descriptive of the process than applicational. From a wide range of adoption models, the thesis synthesised a composite adoption model, based on an accepted descriptive framework by Rogers. This was done by mapping to this foundation framework relevant criteria and procedures from significant adoption models. Along with this composite adoption model was also developed a development procedure that mapped the adoption model to common activities found in all the web and software engineering processes, giving a formal mechanism to apply the adoption theory to a wide range of web development methodologies. In doing so the composite model introduces a new dimension into the domain analysis by identifying a new class of stakeholders, namely “adoption change agents”, and also broadens the requirements process. The adoption model and development process was then applied to the development of a substantive web information system called Platform Web. Platform Web over a three year period evolved to provide many integrated online functions, including a fully developed teaching package only available on one member, to a university wide online tutorial system that integrated to the student administrative systems, the timetabling and teaching module. As the university at that time consisted of three basically independent network members, each promoting the use of web based teaching, it was possible to run a series of statistical tests across the three members on the uptake of their respective web application teaching modules. The significant statistical results endorsing the thesis hypothesis that “Adoption modelling will enhance the effective use of web applications and the resulting web information systems if applied at the web application design level and also in the formulation of system implementation strategies, management models and system evolution methodologies.” / Doctor of Philosophy (PhD)

Skyline has been proposed as an important operator for many applications, such as multi-criteria decision making, data mining and visualization, and user-preference queries. Due to its importance, skyline and its computation have received considerable attention from database research community recently. All the existing techniques, however, focus on the conventional databases. They are not applicable to online computation environment, such as data stream. In addition, the existing studies consider efficiency of skyline computation only, while the fundamental problem on the semantics of skylines still remains open. In this thesis, we study three problems of skyline computation: (1) online computing skyline over data stream; (2) skyline cube computation and its analysis; and (3) top-k most representative skyline. To tackle the problem of online skyline computation, we develop a novel framework which converts more expensive multiple dimensional skyline computation to stabbing queries in 1-dimensional space. Based on this framework, a rigorous theoretical analysis of the time complexity of online skyline computation is provided. Then, efficient algorithms are proposed to support ad hoc and continuous skyline queries over data stream. Inspired by the idea of data cube, we propose a novel concept of skyline cube which consists of skylines of all possible non-empty subsets of a given full space. We identify the unique sharing strategies for skyline cube computation and develop two efficient algorithms which compute skyline cube in a bottom-up and top-down manner, respectively. Finally, a theoretical framework to answer the question about semantics of skyline and analysis of multidimensional subspace skyline are presented. Motived by the fact that the full skyline may be less informative because it generally consists of a large number of skyline points, we proposed a novel skyline operator -- top-k most representative skyline. The top-k most representative skyline operator selects the k skyline points so that the number of data points, which are dominated by at least one of these k skyline points, is maximized. To compute top-k most representative skyline, two efficient algorithms and their theoretical analysis are presented.

[No Abstract]

Skyline has been proposed as an important operator for many applications, such as multi-criteria decision making, data mining and visualization, and user-preference queries. Due to its importance, skyline and its computation have received considerable attention from database research community recently. All the existing techniques, however, focus on the conventional databases. They are not applicable to online computation environment, such as data stream. In addition, the existing studies consider efficiency of skyline computation only, while the fundamental problem on the semantics of skylines still remains open. In this thesis, we study three problems of skyline computation: (1) online computing skyline over data stream; (2) skyline cube computation and its analysis; and (3) top-k most representative skyline. To tackle the problem of online skyline computation, we develop a novel framework which converts more expensive multiple dimensional skyline computation to stabbing queries in 1-dimensional space. Based on this framework, a rigorous theoretical analysis of the time complexity of online skyline computation is provided. Then, efficient algorithms are proposed to support ad hoc and continuous skyline queries over data stream. Inspired by the idea of data cube, we propose a novel concept of skyline cube which consists of skylines of all possible non-empty subsets of a given full space. We identify the unique sharing strategies for skyline cube computation and develop two efficient algorithms which compute skyline cube in a bottom-up and top-down manner, respectively. Finally, a theoretical framework to answer the question about semantics of skyline and analysis of multidimensional subspace skyline are presented. Motived by the fact that the full skyline may be less informative because it generally consists of a large number of skyline points, we proposed a novel skyline operator -- top-k most representative skyline. The top-k most representative skyline operator selects the k skyline points so that the number of data points, which are dominated by at least one of these k skyline points, is maximized. To compute top-k most representative skyline, two efficient algorithms and their theoretical analysis are presented.

<p>DUE TO COPYRIGHT-RESTRICTIONS THIS PAPER IS NOT AVAILABLE FOR DOWNLOAD!</p><p>The thesis describes a system which communicates in real time with data loggers. The system has been streamlined and integrated with existing application so that each user can get a graphical presentation in real time on what has been sent to and from the units. The user interface and communication has been designed to be robust, user friendly, secure and offer functionality that yields the users of the system added value. The system is flexible from the design perspective and is low maintenance.</p>

Thesis (M.Sc.)--Memorial University of Newfoundland, 2005. / The CD-ROM includes "all source code of the impleemntation" -- leaf 207. Bibliography: leaves 199-202.

Database systems employ physical structures such as indexes and materialized views to improve query performance, potentially by orders of magnitude. It is therefore important for a database administrator to choose the appropriate configuration of these physical structures (i.e., the appropriate physical design) for a given database. Deciding on the physical design of a database is not an easy task, and a considerable amount of research exists on automatic physical design tools for relational databases. Recently, XML database systems are increasingly being used for managing highly structured XML data, and support for XML data is being added to commercial relational database systems. This raises the important question of how to choose the appropriate physical design (i.e., the appropriate set of physical structures) for an XML database. Relational automatic physical design tools are not adequate, so new research is needed in this area. In this thesis, we address the problem of automatic physical design for XML databases, which is the process of automatically selecting the best set of physical structures for a given database and a given query workload representing the client application's usage patterns of this data. We focus on recommending two types of physical structures: XML indexes and relational materialized views of XML data. For each of these structures, we study the recommendation process and present a design advisor that automatically recommends a configuration of physical structures given an XML database and a workload of XML queries. The recommendation process is divided into four main phases: (1) enumerating candidate physical structures, (2) generalizing candidate structures in order to generate more candidates that are useful to queries that are not seen in the given workload but similar to the workload queries, (3) estimating the benefit of various candidate structures, and (4) selecting the best set of candidate structures for the given database and workload. We present a design advisor for recommending XML indexes, one for recommending materialized views, and an integrated design advisor that recommends both indexes and materialized views. A key characteristic of our advisors is that they are tightly coupled with the query optimizer of the database system, and rely on the optimizer for enumerating and evaluating physical designs whenever possible. This characteristic makes our techniques suitable for any database system that complies with a set of minimum requirements listed within the thesis. We have implemented the index, materialized view, and integrated advisors in a prototype version of IBM DB2 V9, which supports both relational and XML data, and we experimentally demonstrate the effectiveness of their recommendations using this implementation.

Thesis (Ph. D.)--University of Hong Kong, 2010. / Includes bibliographical references (p. 115-119). Also available in print.