55 research outputs found
Modeling views in the layered view model for XML using UML
In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction
Designing and querying XML views based on the ORA-SS data model
Ph.DDOCTOR OF PHILOSOPH
Content-based video indexing for sports applications using integrated multi-modal approach
This thesis presents a research work based on an integrated multi-modal approach for sports video indexing and retrieval. By combining specific features extractable from multiple (audio-visual) modalities, generic structure and specific events can be detected and classified. During browsing and retrieval, users will benefit from the integration of high-level semantic and some descriptive mid-level features such as whistle and close-up view of player(s). The main objective is to contribute to the three major components of sports video indexing systems. The first component is a set of powerful techniques to extract audio-visual features and semantic contents automatically. The main purposes are to reduce manual annotations and to summarize the lengthy contents into a compact, meaningful and more enjoyable presentation. The second component is an expressive and flexible indexing technique that supports gradual index construction. Indexing scheme is essential to determine the methods by which users can access a video database. The third and last component is a query language that can generate dynamic video summaries for smart browsing and support user-oriented retrievals
Migrating relational databases into object-based and XML databases
Rapid changes in information technology, the emergence of object-based and WWW applications, and the interest of organisations in securing benefits from new technologies have made information systems re-engineering in general and database migration in particular an active research area. In order to improve the functionality and performance of existing systems, the re-engineering process requires identifying and understanding all of the components of such systems. An underlying database is one of the most important component of information systems. A considerable body of data is stored in relational databases (RDBs), yet they have limitations to support complex structures and user-defined data types provided by relatively recent databases such as object-based and XML databases. Instead of throwing away the large amount of data stored in RDBs, it is more appropriate to enrich and convert such data to be used by new systems. Most researchers into the migration of RDBs into object-based/XML databases have concentrated on schema translation, accessing and publishing RDB data using newer technology, while few have paid attention to the conversion of data, and the preservation of data semantics, e.g., inheritance and integrity constraints. In addition, existing work does not appear to provide a solution for more than one target database. Thus, research on the migration of RDBs is not fully developed. We propose a solution that offers automatic migration of an RDB as a source into the recent database technologies as targets based on available standards such as ODMG 3.0, SQL4 and XML Schema. A canonical data model (CDM) is proposed to bridge the semantic gap between an RDB and the target databases. The CDM preserves and enhances the metadata of existing RDBs to fit in with the essential characteristics of the target databases. The adoption of standards is essential for increased portability, flexibility and constraints preservation. This thesis contributes a solution for migrating RDBs into object-based and XML databases. The solution takes an existing RDB as input, enriches its metadata representation with the required explicit semantics, and constructs an enhanced relational schema representation (RSR). Based on the RSR, a CDM is generated which is enriched with the RDB's constraints and data semantics that may not have been explicitly expressed in the RDB metadata. The CDM so obtained facilitates both schema translation and data conversion. We design sets of rules for translating the CDM into each of the three target schemas, and provide algorithms for converting RDB data into the target formats based on the CDM. A prototype of the solution has been implemented, which generates the three target databases. Experimental study has been conducted to evaluate the prototype. The experimental results show that the target schemas resulting from the prototype and those generated by existing manual mapping techniques were comparable. We have also shown that the source and target databases were equivalent, and demonstrated that the solution, conceptually and practically, is feasible, efficient and correct
From Relations to XML: Cleaning, Integrating and Securing Data
While relational databases are still the preferred approach for storing data, XML is emerging
as the primary standard for representing and exchanging data. Consequently, it has
been increasingly important to provide a uniform XML interface to various data sourcesā
integration; and critical to protect sensitive and confidential information in XML data ā
access control. Moreover, it is preferable to first detect and repair the inconsistencies in
the data to avoid the propagation of errors to other data processing steps. In response to
these challenges, this thesis presents an integrated framework for cleaning, integrating and
securing data.
The framework contains three parts. First, the data cleaning sub-framework makes
use of a new class of constraints specially designed for improving data quality, referred
to as conditional functional dependencies (CFDs), to detect and remove inconsistencies in
relational data. Both batch and incremental techniques are developed for detecting CFD
violations by SQL efficiently and repairing them based on a cost model. The cleaned relational
data, together with other non-XML data, is then converted to XML format by using
widely deployed XML publishing facilities. Second, the data integration sub-framework
uses a novel formalism, XML integration grammars (XIGs), to integrate multi-source XML
data which is either native or published from traditional databases. XIGs automatically
support conformance to a target DTD, and allow one to build a large, complex integration
via composition of component XIGs. To efficiently materialize the integrated data, algorithms
are developed for merging XML queries in XIGs and for scheduling them. Third, to
protect sensitive information in the integrated XML data, the data security sub-framework
allows users to access the data only through authorized views. User queries posed on these
views need to be rewritten into equivalent queries on the underlying document to avoid the
prohibitive cost of materializing and maintaining large number of views. Two algorithms
are proposed to support virtual XML views: a rewriting algorithm that characterizes the
rewritten queries as a new form of automata and an evaluation algorithm to execute the
automata-represented queries. They allow the security sub-framework to answer queries
on views in linear time.
Using both relational and XML technologies, this framework provides a uniform approach
to clean, integrate and secure data. The algorithms and techniques in the framework
have been implemented and the experimental study verifies their effectiveness and efficiency
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