Diplomarbeit, 2006
92 Seiten, Note: 1,0
1 Introduction
1.1 Motivation
1.2 Goals and Scope
1.3 Overview
2 eGovernment
2.1 Fields of eGovernment
2.2 eAdministration
2.3 Process Integration
2.4 Semantic Web meets eGovernment
2.5 eGovernment Scenario
2.6 From eGovernment to eGovernance
3 State-of-the-art
3.1 Overview
3.2 Interoperability
3.3 Web Services
3.4 Web Service Composition
3.5 Semantic Web Services
3.6 Semantic Information Integration
3.7 Related Work
4 Concept
4.1 Overview
4.2 Requirements
4.3 General Idea
4.4 Overall View
4.5 Domain Ontologies and Semantic Web Services
4.6 Semantic Bridges
4.7 Matching and Data Flow
4.8 Process Execution
4.9 Logical Architecture
5 Realization
5.1 Overview
5.2 System Architecture for Composition Design
5.3 Semantic Web Services
5.4 Semantic Bridges
5.5 Semantic Web Service Composer
5.6 System Architecture for Composition Execution
5.7 Execution Engine
5.8 Scenario
5.9 Validation and Verification
5.10 Usage
6 Evaluation
6.1 Coverage of Goals
6.2 Network Effect
7 Conclusion and Outlook
7.1 Summary
7.2 Open Problems
7.3 Future Work
This thesis addresses the challenge of achieving interoperability in eGovernment process integration. It proposes a semi-automated approach for designing and executing data flows within the composition of semantically described Web services, utilizing different ontologies and information representations.
4.3 General Idea
Basis of all information systems are domain models which describe a certain information space. They are expressed in highly abstract modeling languages such as the Unified Modeling Language [74] or the Entity-Relationship Model (ER) [75]. In order to be used in a concrete application context, these domain models need to be break down to a lower system specific level. Considering the common database design methodology of different abstraction levels it can be distinguished between the conceptual data model, the logical data model, and the physical data model. The conceptual data model is used for the abstract modeling of an information space as already mentioned. The logical data model provides the view on the information space to be used in application development. In the context of database systems this means to map an ER-model to tables, columns and rows, the relational model. The physical model is private to the actual system processing and storing the data.
Considering these different abstraction levels in the context of data models within Web service composition is the starting point for the general idea of this work, that is shifting the composition process on a higher abstraction level. Currently, traditional Web service composition is based on various XML standards that follow a tree structure data model. Web services described by WSDL integrate XML Schema to specify message parts of their input and output parameters by structuring tags and attributes hierarchically. Process descriptions formulated in XML-based workflow languages as BPEL use XPath expressions for defining the data flow between the involved services of a composition. The same holds for XSLT, where transformation rules match according to appropriate XPath expressions. Therefore, regarding XML from the perspective of different abstraction levels above, it can be said, that its tree structure of tags provides the view used for application development and thus XML can be regarded as a logical data model. However, at the same time it can also be regarded as a physical data model as mostly the encoding of data in tree structured tags is directly used as the storage format.
1 Introduction: This chapter introduces the motivation for the thesis, outlining the interoperability challenges in eGovernment and defining the research goals.
2 eGovernment: The chapter explores the eGovernment domain, its fields, interaction models, and the specific need for process integration.
3 State-of-the-art: It provides a background on existing technologies for interoperability, Web services, composition, and semantic information integration.
4 Concept: This section details the developed approach for cross-ontology semantic Web service composition, including the use of semantic bridges.
5 Realization: The chapter describes the technical implementation of the prototype, including the composer, the execution engine, and the validation scenario.
6 Evaluation: It analyzes to what extent the objectives set in the beginning have been met and discusses the network effect.
7 Conclusion and Outlook: The thesis summarizes the proposed approach, highlights open problems, and suggests directions for future work.
eGovernment, Interoperability, Web Services, Semantic Web, Ontology, Web Service Composition, Data Flow, Mediation, Semantic Bridges, Process Integration, OWL-S, WSDL, XML Schema, Automated Reasoning, Prototype
The thesis focuses on achieving interoperability in the eGovernment sector by addressing the complexity of process integration through semantic Web service composition.
It addresses the issue of integrating processes across different public agencies that use different, heterogeneous data representations and ontologies.
The goal is to provide a semi-automatic approach to design and execute data flows, allowing domain experts to compose Web services without needing extensive technical knowledge of all involved schemas.
The work utilizes Semantic Web technologies, including ontologies (OWL), semantic bridges (rules), and faceted classification, to mediate between different information representations.
The main part covers the conceptualization of cross-ontology composition, the development of a semantic Web service composer, and the realization of an execution engine for eGovernment scenarios.
Key terms include eGovernment, Semantic Web, Web Service Composition, Interoperability, Ontology, and Data Flow mediation.
Semantic bridges act as rules that infer parameter mappings between different ontologies, allowing disparate systems to understand and exchange data.
The prototype serves as a validation mechanism to demonstrate the feasibility of the concept in a cross-domain birth certificate application scenario.
Instead of manual, hard-coded transformations, this approach lifts data models to an ontological level, making integration more flexible and reusable.
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