Thesis (Ph. D.)--Ohio University, June, 1999. / Title from PDF t.p.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, March 2005. / Thesis Advisor(s): Thomas W. Otani. Includes bibliographical references (p. 173). Also available online.

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2005. / Includes bibliographical references (leaves 127-136). Also available in electronic version.

Thesis (M.S.) -- Worcester Polytechnic Institute. / Keywords: continuous queries; moving objects. Includes bibliographical references (p.102-110).

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: XML, Query Re-Writing, View Maintenance, Query Containment. Includes bibliographical references. (p.108-111)

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 137-144).

In contrast to a traditional setting where users express queries against the database schema, we assert that the semantics of data can often be understood by viewing the data in the context of the user interface (UI) of the software tool used to enter the data. That is, we believe that users will understand the data in a database by seeing the labels, dropdown menus, tool tips, help text, control contents, and juxtaposition or arrangement of controls that are built in to the user interface. Our goal is to allow domain experts with little technical skill to understand and query data. In this dissertation, we present our GUi As View (Guava) framework and describe how we use forms-based UIs to generate a conceptual model that represents the information in the user interface. We then describe how we generate a query interface from the conceptual model. We characterize the resulting query language using a subset of relational algebra. Since most application developers want to craft a physical database to meet desired performance needs independent of the schema used by the user interface, we subsequently present a general-purpose schema mapping tool called a channel that can be configured by instantiating a sequence of discrete transformations. Each transformation is an encapsulation of a physical design decision or business logic process. The channel, once configured, automatically transforms queries from our query interface into queries that address the underlying physical database, similar to a view. The channel also transforms data updates, schema updates, and constraint definitions posed against the channel’s input schema into equivalent forms against the physical schema. We present formal definitions of each transformation and properties that must be true of transformations, and prove that our definitions respect the properties.

Indexing video data is essential for providing content based access. In this paper, we consider how database technology can offer an integrated framework for modeling and querying video data. As many concerns in video (e.g., modeling and querying) are also found in databases, databases provide an interesting angle to attack many of the problems. From a video applications perspective, database systems provide a nice basis for future video systems. More generally, database research will provide solutions to many video issues even if these are partial or fragmented. From a database perspective, video applications provide beautiful challenges. Next generation database systems will need to provide support for multimedia data (e.g., image, video, audio). These data types require new techniques for their management (i.e., storing, modeling, querying, etc.). Hence new solutions are significant. This paper develops a data model and a rule-based query language for video content based indexing and retrieval. The data model is designed around the object and constraint paradigms. A video sequence is split into a set of fragments. Each fragment can be analyzed to extract the information (symbolic descriptions) of interest that can be put into a database. This database can then be searched to find information of interest. Two types of information are considered: (1) the entities (objects) of interest in the domain of a video sequence, (2) video frames which contain these entities. To represent these information, our data model allows facts as well as objects and constraints. We present a declarative, rule-based, constraint query language that can be used to infer relationships about information represented in the model. The language has a clear declarative and operational semantics. This work is a major revision and a consolidation of [12, 13]. / This is an extended version of the article in: 15th International Conference on Data Engineering, Sydney, Australia, 1999.

As databases accumulate growing amounts of data at an increasing rate, adaptive indexing becomes more and more important. At the same time, applications and their use get more agile and flexible, resulting in less steady and less predictable workload characteristics. Being inert and coarse-grained, state-of-the-art index tuning techniques become less useful in such environments. Especially the full-column indexing paradigm results in many indexed but never queried records and prohibitively high storage and maintenance costs. In this paper, we present Self-Managing Indexes, a novel, adaptive, fine-grained, autonomous indexing infrastructure. In its core, our approach builds on a novel access path that automatically collects useful index information, discards useless index information, and competes with its kind for resources to host its index information. Compared to existing technologies for adaptive indexing, we are able to dynamically grow and shrink our indexes, instead of incrementally enhancing the index granularity.

With the advent of XML, great challenges arise from the demand for efficiently retrieving information from remote XML sources across the Internet. The semantic caching technology can help to improve the efficiency of XML query processing in the Web environment. Different from the traditional tuple or page-based caching systems, semantic caching systems exploit the idea of reusing cached query results to answer new queries based on the query containment and rewriting techniques. Fundamental results on the containment of relational queries have been established. In the XML setting, the containment problem remains unexplored for comprehensive XML query languages such as XQuery, and little has been studied with respect to the cache management issue such as replacement. Hence, this dissertation addresses two issues fundamental to building an XQuery-based semantic caching system: XQuery containment and rewriting, and an effective replacement strategy. We first define a restricted XQuery fragment for which the containment problem is tackled. For two given queries $Q1$ and $Q2$, a preprocessing step including variable minimization and query normalization is taken to transform them into a normal form. Then two tree structures are constructed for respectively representing the pattern matching and result construction components of the query semantics. Based on the tree structures, query containment is reduced to tree homomorphism, with some specific mapping conditions. Important notations and theorems are also presented to support our XQuery containment and rewriting approaches. For the cache replacement, we propose a fine-grained replacement strategy based on the detailed user access statistics recorded on the internal XML view structure. As a result, less frequently used XML view fragments are replaced to achieve a better utilization of the cache space. Finally, we has implemented a semantic caching system called ACE-XQ to realize the proposed techniques. Case studies are conducted to confirm the correctness of our XQuery containment and rewriting approaches by comparing the query results produced by utilizing ACE-XQ against those by the remote XQuery engine. Experimental studies show that the query performance is significantly improved by adopting ACE-XQ, and that our partial replacement helps to enhance the cache hits and utilization comparing to the traditional total replacement.