Thesis (M.S.)--University of Florida, 2001. / Title from first page of PDF file. Document formatted into pages; contains viii, 135 p.; also contains graphics. Vita. Includes bibliographical references (p. 132-134).

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: XML algebra; order; view maintenance; propagation rules; XML. Includes bibliographical references (p. 80-83).

The development of high-throughput genome sequencing and protein structure determination techniques have provided researchers with a wealth ofbiological data. However, providing an integrated analysis can be difficult due to the incompatibilities of data formats between providers and applications, the strict schema constraints imposed by data providers, and the lack ofinfrastructure for easily accommodating new semantic information. To address these issues, this thesis first proposes to use Extensible Markup Language (XML) [26] and its supporting query languages as the underlying technology to facilitate a seamless, integrated access to the sum of heterogeneous biological data and services. XML is used due to its semi-structured nature and its ability to easily encapsulate both contextual and semantic information. The tree representation of an XML document enables applications to easily traverse and access data within the document without prior knowledge of its schema. However, in the process ofconstructing the framework, we have identified a number of issues that are related to the performance ofXML technologies. More specifically, on the performance ofthe XML query processor, the data store and the transformation processor. Hence, this thesis also focuses on finding new solutions to address these issues. For the XML query processor, we proposes an efficient structural join algorithm that can be implemented on top of existing relational databases. Experiments show the proposed method outperforms previous work in both queries and updates. For complicated XML query patterns, a new twig join algorithm called CTwigStack is proposed in this thesis. In essence, the new approach only produces and merges partial solution nodes that satisfy the entire twig query pattern tree. Experiments show the proposed algorithm outperforms previous methods in most cases. For more general cases, a propose a mixed mode twig join is proposed, which combines CTwigStack with the existing twig join algorithms and the extensive experimental results have shown the superior effectiveness of both CTwigStack and the mixed mode twig join. By combining with existing system information, the mixed mode twig join can be served as a framework for plan selection during the process of XML query optimization. For the XML transfonnation component, a novel stand-alone, memory conscious XSLT processor is proposed in this thesis, such that the proposed XSLT processor only requires a single pass of the input XML dataset. Consequently, enabling fast transfonnation of streaming XML data and better handling of complicated XPath selection patterns, including aggregate predicate functions such as the XPath count function. Ultimately, based on the nature of the proposed framework, we believe that solving the perfonnance issues related to the underlying XML components can subsequently lead to a more robust framework for integrating heterogeneous biological data sources and services.

Thesis (M.S.C.I.T.)--Regis University, Denver, Colo., 2007. / Title from PDF title page (viewed on Jan 17, 2008). Includes bibliographical references.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: database; xml; view update. Includes bibliographical references (leaves 51-53 ).

Thesis (Ph.D.)--Washington State University. / Includes bibliographical references.

Thesis (Ph. D.)--Washington State University, August 2006. / Includes bibliographical references (p. 156-164).

published_or_final_version / Humanities / Master / Master of Philosophy

Approved for public release; distribution is unlimited / The Department of Defense (DoD) is both challenged by the quest for interoperability and capable of the bottom-up development of a solution. The predominant method for achieving interoperability is the development of an intermediate representation that provides a common integration language or data model. An example is Young's Object-Oriented Method for Interoperability (OOMI), which produces a Federation Interoperability Object Model (FIOM) for the resolution of heterogeneities in representation and view of a real-world entity. An FIOM generates a standard for interoperability by associating the non-standard, component system data models into an extensible lattice, which captures translations that resolve data modeling differences. To support the bottom-up creation of an FIOM we; (1) describe a self-similar approach to data storage that allows generic data structures to be manageable, extensible and asynchronously populated, and (2) introduce a lattice concept for facilitating efficient and scalable object inheritance relationships. We assert that DoD's acquisition environment necessitates a distributed approach to solving the interoperability challenge. We present the description of a distributed software system to facilitate the collaborative construction of an FIOM within the existing DoD structure and provide an architecture to guide the development of such a distributed collaborative environment. / Lieutenant, United States Navy

by Yan, Men-Hin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 114-119). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgments --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Storing XML in Database Systems --- p.2 / Chapter 1.2 --- Outline of the Thesis --- p.4 / Chapter 2 --- Related Work --- p.5 / Chapter 2.1 --- Overview of XML --- p.5 / Chapter 2.1.1 --- Extensible Markup Language (XML) --- p.5 / Chapter 2.1.2 --- Data Type Definition (DTD) --- p.6 / Chapter 2.1.3 --- "ID, IDREF and IDREFS" --- p.9 / Chapter 2.2 --- Using Special-Purpose Database to Store XML Data --- p.10 / Chapter 2.3 --- Using Relational Databases to Store XML Data --- p.11 / Chapter 2.3.1 --- Extracting Schemas with STORED --- p.11 / Chapter 2.3.2 --- Using Simple Schemes Based on Labeled Graph --- p.12 / Chapter 2.3.3 --- Generating Schemas from DTDs --- p.12 / Chapter 2.3.4 --- Commercial Approaches --- p.13 / Chapter 2.4 --- Discovering Functional Dependencies --- p.14 / Chapter 2.4.1 --- Functional Dependency --- p.14 / Chapter 2.4.2 --- Finding Functional Dependencies --- p.14 / Chapter 2.4.3 --- TANE and Partition Refinement --- p.15 / Chapter 2.5 --- Multivalued Dependencies --- p.17 / Chapter 2.5.1 --- Example of Multivalued Dependency --- p.18 / Chapter 3 --- Using RDBMS to Store XML Data --- p.20 / Chapter 3.1 --- Global Schema Extraction Algorithm --- p.22 / Chapter 3.1.1 --- Step 1: Simplify DTD --- p.22 / Chapter 3.1.2 --- Step 2: Construct Schema Prototype Trees --- p.24 / Chapter 3.1.3 --- Step 3: Generate Relational Schema Prototype --- p.29 / Chapter 3.1.4 --- Step 4: Discover Functional Dependencies and Candidate Keys --- p.31 / Chapter 3.1.5 --- Step 5: Normalize the Relational Schema Prototypes --- p.32 / Chapter 3.1.6 --- Discussion --- p.32 / Chapter 3.2 --- DTD-splitting Schema Extraction Algorithm --- p.34 / Chapter 3.2.1 --- Step 1: Simplify DTD --- p.35 / Chapter 3.2.2 --- Step 2: Construct Schema Prototype Trees --- p.36 / Chapter 3.2.3 --- Step 3: Generate Relational Schema Prototype --- p.45 / Chapter 3.2.4 --- Step 4: Discover Functional Dependencies and Candidate Keys --- p.46 / Chapter 3.2.5 --- Step 5: Normalize the Relational Schema Prototypes --- p.47 / Chapter 3.2.6 --- Discussion --- p.49 / Chapter 3.3 --- Experimental Results --- p.50 / Chapter 3.3.1 --- Real Life XML Data: SIGMOD Record XML --- p.50 / Chapter 3.3.2 --- Synthetic XML Data --- p.58 / Chapter 3.3.3 --- Discussion --- p.68 / Chapter 4 --- Finding Multivalued Dependencies --- p.75 / Chapter 4.1 --- Validation of Multivalued Dependencies --- p.77 / Chapter 4.2 --- Search Strategy and Pruning --- p.80 / Chapter 4.2.1 --- Search Strategy for Left-hand Sides Candidates --- p.81 / Chapter 4.2.2 --- Search Strategy for Right-hand Sides Candidates --- p.82 / Chapter 4.2.3 --- Other Pruning --- p.85 / Chapter 4.3 --- Computing with Partitions --- p.87 / Chapter 4.3.1 --- Computing Partitions --- p.88 / Chapter 4.4 --- Algorithm --- p.89 / Chapter 4.4.1 --- Generating Next Level Candidates --- p.92 / Chapter 4.4.2 --- Computing Partitions --- p.93 / Chapter 4.5 --- Experimental Results --- p.94 / Chapter 4.5.1 --- Results of the Algorithm --- p.95 / Chapter 4.5.2 --- Evaluation on the Results --- p.96 / Chapter 4.5.3 --- Scalability of the Algorithm --- p.98 / Chapter 4.5.4 --- Using Multivalued Dependencies in Schema Extraction Al- gorithms --- p.101 / Chapter 5 --- Conclusion --- p.108 / Chapter 5.1 --- Discussion --- p.108 / Chapter 5.2 --- Future Work --- p.110 / Chapter 5.2.1 --- Translate Semistructured Queries to SQL --- p.110 / Chapter 5.2.2 --- Improve the Multivalued Dependency Discovery Algorithm --- p.112 / Chapter 5.2.3 --- Incremental Update of Resulting Schema --- p.113 / Bibliography --- p.113 / Appendix --- p.120 / Chapter A --- Simple Proof for Minimality in Multivalued Dependencies --- p.120 / Chapter B --- Third and Fourth Normal Form Decompositions --- p.122 / Chapter B.1 --- 3NF Decomposition Algorithm --- p.123 / Chapter B.2 --- 4NF Decomposition Algorithm --- p.124