XML technology has emerged during recent years as a popular choice for representing and exchanging semi-structured data on the Web. It integrates seamlessly with web-based applications. If data is stored and represented as XML documents, then it should be possible to query the contents of these documents in order to extract, synthesize and analyze their contents. This thesis for experimental study of Web architecture for data processing is based on semantic mapping of XML Schema. The thesis involves complex methods and tools for specification, algorithmic transformation and online processing of semi-structured data over the Web in XML format with persistent storage into relational databases. The main focus of the research is preserving the structure of original data for data reconciliation during database updates and also to combine different technologies for XML data processing such as storing (SQL), transformation (XSL Processors), presenting (HTML), querying (XQUERY) and transporting (Web services) using a common framework, which is both theoretically and technologically well grounded. The experimental implementation of the discussed architecture requires a Web server (Apache), Java container (Tomcat) and object-relational DBMS (Oracle 9) equipped with Java engine and corresponding libraries for parsing and transformation of XML data (Xerces and Xalan). Furthermore the central idea behind the research is to use a single theoretical model of the data to be processed by the system (XML algebra) controlled by one standard metalanguage specification (XML Schema) for solving a class of problems (generic architecture). The proposed work combines theoretical novelty and technological advancement in the field of Internet computing. This thesis will introduce a generic approach since both our model (XML algebra) and our problem solver (the architecture of the integrated system) are XML Schema- driven. Starting with the XML Schema of the data, we first develop domain-specific XML algebra suitable for data processing of the specific data and then use it for implementing the main offline components of the system for data processing.