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

Building XML Data Warehouse Based on Frequent Patterns in User Queries

[Abstract]: With the proliferation of XML-based data sources available across the Internet, it is increasingly important to provide users with a data warehouse of XML data sources to facilitate decision-making processes. Due to the extremely large amount of XML data available on web, unguided warehousing of XML data turns out to be highly costly and usually cannot well accommodate the users’ needs in XML data acquirement. In this paper, we propose an approach to materialize XML data warehouses based on frequent query patterns discovered from historical queries issued by users. The schemas of integrated XML documents in the warehouse are built using these frequent query patterns represented as Frequent Query Pattern Trees (FreqQPTs). Using hierarchical clustering technique, the integration approach in the data warehouse is flexible with respect to obtaining and maintaining XML documents. Experiments show that the overall processing of the same queries issued against the global schema become much efficient by using the XML data warehouse built than by directly searching the multiple data sources

Active XML, Security and Access Control ∗

XML and Web services are revolutioning the automatic management of distributed information, somewhat in the same way that HTML, Web browsers and search engines modified human access to world wide information. We argue in this paper that the combination of XML and Web services allows for a novel distributed data management paradigm, where the exchanged information mixes materialized and intensional, active, information. We illustrate the flexibility of this approach by presenting Active XML, a language that is based on embedding Web service calls in XML data. We focus on two particular issues, namely security and access control. 1

MULTIDIMENSIONAL INTEGRATED ONTOLOGIES: A FRAMEWORK FOR DESIGNING SEMANTIC DATA WAREHOUSES

Abstract. The Semantic Web enables companies and organizations to gather huge amounts of valuable semantically annotated data concerning their subjects of interest. Nowadays, many applications attach metadata and semantic annotations taken from domain and application ontologies to the information they generate. From our point of view, the concepts in these ontologies could describe the facts, dimensions, categories and values implied in the analysis subjects of a data warehouse. In this paper we propose the Semantic Data Warehouse to be a repository of ontologies and semantically annotated data resources. We also propose an ontology-driven framework to design multidimensional analysis models for Semantic Data Warehouses. This framework provides means for building an integrated ontology, called the Multidimensional Integrated Ontology (MIO), including the classes, relationships and instances that represent interesting analysis dimensions and measures. The reasoning capabilities of a MIO can be used to check the properties required by current multidimensional databases (e.g., dimension orthogonality, category satisfiability, etc.). In this paper we also sketch how the instance data of a MIO can be translated into OLAP cubes for analysis purposes. Finally, some implementation issues of the overall framework are discussed. Keywords: Data warehouses, Semantic Web, Multi-ontology integration 1