Semantic Mediation between Loosely Coupled Information Models in Service-Oriented Architectures

Doctoral Thesis / Dissertation, 2011

233 Pages, Grade: Sehr gut


Table of Contents

Chapter 1 Introduction
1.1 Background and Motivation
1.2 OverallGoals andScope
1.3 Methodology
1.3.1 Scientific Hypothesis and its Confirmation
1.3.2 Research Questions and Technical Challenges
1.4 Outline of the Thesis

Chapter 2 Understanding the Challenge of Semantic Interoperability in SOA
2.1 Overview
2.2 Interoperability Dimensions
2.2.1 The Context of Semantic Interoperability
2.3 Semantic Interoperability
2.3.1 Terms as Representation of Meaning
2.3.2 Abstraction Levels for Representation ofMeaning
2.3.3 SemanticInteroperability Gap
2.4 Service-OrientedArchitecture
2.5 Framework of Semantic Interoperability in SOA
2.6 Summary and Reflection

Chapter 3 State-of-the-Art in SOA for Bridging the Semantic Interoperability Gap
3.1 Overview
3.2 Web Services
3.2.1 Definition andConcepts
3.2.2 Technologies and Standards
3.2.3 Evaluation
3.3 Semantic Web
3.3.1 Definition and Concepts
3.3.2 Technologies and Standards
3.3.3 Evaluation
3.4 Semantic Web Services
3.4.1 Definition and Concepts
3.4.2 Technologies and Standards
3.4.3 Evaluation
3.5 Semantic Information Integration in Related Areas
3.5.1 Semantic Information Integration in Database Systems
3.5.2 Semantic Information Integration in RM-ODP
3.6 Semantic Information Integration with Ontologies
3.6.1 SingleOntology Approach
3.6.2 Multiple Ontology Approach with Ontology Mapping
3.6.3 Hybrid Ontology Approach
3.7 Summary and Reflection

Chapter 4 Semantic Mediation between Loosely Coupled Information Models in SOA...
4.1 Overview
4.2 Conceptual Goals and Requirements
4.3 General Idea
4.4 Limitations of Standardization for Semantic Interoperability in SOA
4.4.1 Standardizationvs. Mediation
4.4.2 From Technical Standards to Semantic Standards
4.4.3 Semantic Standardization and Monolithic Information Models
4.4.4 Consensus Degree and Adequate Scope of Semantic Standards
4.5 Context Dependency of Information Models
4.5.1 Heterogeneity of Information Models
4.5.2 Model of Conception and Information Models
4.5.3 Constructive Model Relations and Information Models
4.5.4 Conclusions and Implications for Information Models
4.6 Loose Coupling on the Semantic Level
4.6.1 The Principle of Loose Coupling in Computer Science
4.6.2 Transferable Characteristics ofLoose Coupling
4.6.3 Loosely Coupled Information Models
4.6.4 Limitations in the Transfer of Loose Coupling and Open Issues
4.7 Trade-offbetween Effectiveness and Efficiency
4.7.1 Point-to-Point Mediation
4.7.2 Pivot Ontology based Standardization
4.7.3 Semantic Mediation on Domain Level
4.7.4 Alleviation of Trade-Offbetween Effectiveness and Efficiency
4.8 Semantic Bridges for Loose Coupling ofDomain Ontologies
4.8.1 Generalization and Polymorphism
4.8.2 Facet Analysis Classification
4.8.3 Declarative Rule-based Entity Manipulation
4.8.4 Operation of Semantic Bridges
4.8.5 Benefits ofDeveloped Approach for Semantic Bridges
4.9 Summary andReflection

Chapter 5 Methodology and Functional Architecture for Semantic Mediation in SOA..
5.1 Overview
5.2 Methodology Requirements and Domain-specific Considerations
5.3 Semantic Mediation Aligned to SOA Life-Cycle
5.4 Domain Ontology Development
5.4.1 Goals and Tasks
5.4.2 Existing Work
5.5 Mediated Business Process Modeling
5.5.1 Goals and Tasks
5.5.2 Functional Architecture
5.5.3 Related Work
5.6 Semantic Bridge Definition
5.6.1 Goals and Tasks
5.6.2 Existing Work
5.7 Semantic Bridge Testing
5.7.1 Goals and Tasks
5.7.2 FunctionalArchitecture
5.7.3 Related Work
5.8 Semantic Service Enrichment
5.8.1 Goals and Tasks
5.8.2 Existing Work
5.9 MediatedServiceComposition
5.9.1 Goals and Tasks
5.9.2 FunctionalArchitecture
5.9.3 Related Work
5.10 Meditated Process Execution
5.10.1 Goals and Tasks
5.10.2 Functional Architecture
5.10.3 Related Work
5.11 Summary and Reflection

Chapter 6 Realization of Semantic Mediation Toolkit
6.1 Overview
6.2 Mediated Business Process Modeling Tool
6.2.1 System Requirements
6.2.2 DesignandRealization
6.2.3 Scenario, Validation and Verification
6.3 Semantic Bridge Testing Tool
6.3.1 System Requirements
6.3.2 DesignandRealization
6.3.3 Scenario, Validation and Verification
6.4 Mediated Service Composition Tool
6.4.1 System Requirements
6.4.2 DesignandRealization
6.4.3 Scenario, Validation and Verification
6.5 Meditated Process Execution Tool
6.5.1 System Requirements and Challenges
6.5.2 DesignandRealization
6.5.3 Scenario, Validation and Verification
6.6 Usage and Extension of the Semantic Mediation Toolkit
6.7 Summary andReflection

Chapter 7 Evaluation and Case Study of an Exemplary Distributed Organization
7.1 EvaluationMethodology
7.2 The German Chambers of Commerce and its eGovernment Context
7.2.1 The Chambers Service Bus and Service Hub
7.2.2 The Data Conference Working Group
7.2.3 Achievements and Ongoing Challenges
7.2.4 Potential of the Semantic Mediation Approach
7.2.5 Network Effect
7.3 Coverage of Goals and Confirmation ofResearch Hypothesis
7.3.1 Coverage of Conceptual Goals
7.3.2 Confirmation ofResearch Hypothesis
7.4 Summary andReflection

Chapter 8 Conclusion and Outlook
8.1 Summary and Main Contributions
8.2 Evolution andOutlook



Domain Ontology Sample “RosettaNetOntology”

Domain Ontology Sample “MoonOntology”

Semantic Bridge Sample “RosettaNetOntology2MoonOntology”

Semantic Web Service Sample “MoonCRMService”


The last two decades have shown a major shift from stand-alone to networked information technology (IT) systems. Consequently, the effective and efficient achievement of interoperability is a key factor to enable seamless business process chains and networks across intra- and inter-organizational boundaries. Thereby, interoperability can be understood along three dimensions: technical, semantic and organizational interoperability.

While the concept of service-oriented architectures (SOA) and widely accepted Web service standards have benefited technical interoperability in recent years substantially, managing and integrating semantic differences in heterogeneous distributed environments remains critical and cost intensive. In order to preserve the precise meaning as data is moved from one IT system to another, explicit formal information models in terms of ontologies have evolved as the concept of choice from academia to first industry adoption. However, it has been recognized that the dominant approach of developing a common, globally shared ontology as an information model standard has turned out to be limited in real world cross-domain environments. Organizational boundaries with regard to consensus degree and the complexity deriving from inherent domain- specific differences in requirements force a coexistence of independently managed but however semantic interoperable information models.

In order to address this challenge, the guiding idea of this work is to transfer the principle of loose coupling to the semantic level. In particular, the goal of this thesis is to contribute to the reduction of complexity in semantic system integration by developing an effective and efficient approach for semantic interoperability in large-scale SOA landscapes based on semantic mediation between loosely coupled information models. Moreover, this work shows how emerging semantic technologies can contribute to the instantiation of this concept exploiting their capabilities to explicitly express semantics. The main contributions of this work are:

- A conceptual framework for semantic interoperability in SOA, which is mapped to an overview and evaluation of existing academic and industry-driven approaches pointing out shortcomings and fields for further advancements.
- A concept of semantic mediation between loosely coupled information models in SOA, which describes an information architecture design pattern that provides an optimized balance within the identified inherent trade-off between effectiveness and efficiency in achieving semantic interoperability in SOA. It includes a specification of loosely coupled information models in terms of key characteristics derived from the principle of loose coupling such as autonomy, flexible binding and encapsulation.
- An instantiating semantic mediation mechanism by means of description logic rule-based semantic bridges and self-contained domain ontologies exploiting capabilities such as polymorphism, facet analysis classification and declarative entity manipulation.
- A semantic mediation methodology and prototypical toolkit, which maps the developed concept and mechanism to the SOA life-cycle ranging from business process modeling, over service composition to runtime process execution, in order to provide a proof of concept.

The developed approach is evaluated based on a case study of an exemplary distributed organization. It is shown how the approach of semantic mediation between loosely coupled information models can be applied in practice and which benefits can be generated with regard to achieving effective and efficient semantic interoperability in large-scale SOA landscapes.


Die Informationstechnologie (IT) der letzten zwei Jahrzehnte war durch eine zunehmende Entwicklung weg von eigenständigen hin zu vernetzten IT-Systemen geprägt. Vor diesem Hintergrund ergibt sich die Herausforderung, Interoperabilität möglichst effektiv und effizient zu erreichen, um nahtlose Geschäftsprozesse innerhalb und über Organisationsgrenzen hinweg zu ermöglichen. Interoperabilität kann dabei entlang von drei Dimensionen verstanden werden: technische, semantische und organisatorische Interoperabilität.

Während das Konzept der Service-orientierten Architekturen (SOA) und weit etablierte Web Service-Standards in den letzten Jahren wesentlich zum Erreichen von technischer Interoperabilität beigetragen haben, ist die semantische Integration in heterogenen verteilten Umgebungen weiterhin schwierig und kostenintensiv. Für den bedeutungskonsistenten Datenaustausch zwischen IT-Systemen haben sich explizite formale Informationsmodelle in Form von Ontologien als erfolgversprechendes Konzept in akademischen und ersten industriellen Bereichen herausgestellt. Allerdings hat sich gezeigt, dass der dominierende Ansatz basierend auf einer umfassenden gemeinsam zu nutzenden Ontologie als standardisiertes Informationsmodell in organisationsübergreifenden Szenarien nur begrenzt praktikabel ist. Organisatorische Grenzen mit Hinsicht auf Konsensfähigkeit und die Komplexität, die aus unterschiedlichen domänenspezifischen Anforderungen hervorgeht, erfordern eine Koexistenz von unabhängig zu verwaltendenjedoch semantisch interoperablen Informationsmodellen.

Um dieser Herausforderung zu begegnen, ist der Leitgedanke der vorliegenden Arbeit, das Prinzip der losen Kopplung auf die semantische Ebene zu übertragen. Dabei verfolgt die Arbeit das Ziel, einen Beitrag zur Verringerung der Komplexität bei der semantischen System­integration zu leisten. Im Zentrum steht die Entwicklung eines effektiven und effizienten Ansatzes für die semantische Interoperabilität in groß angelegten SOA-Landschaften mittels semantischer Mediation zwischen lose gekoppelten Informationsmodellen. Darüber hinaus zeigt die Arbeit, wie neuartige semantische Technologien verwendet werden können, um das entworfene Konzept zu instanziieren. Die wichtigsten Beiträge dieser Arbeit sind:

- Ein konzeptioneller Rahmen der semantischen Interoperabilität in SOA, der abgebildet wird auf einen Überblick existierender akademischer und industrieller Ansätze, mit dem Ziel Handlungsfelder und Entwicklungsbedarfe aufzuzeigen.
- Ein Konzept der semantischen Mediation zwischen lose gekoppelten Informationsmodellen in SOA als Entwurfsmuster für Informationsarchitekturen. Es beinhaltet eine Spezifikation auf Basis von wesentlichen Merkmalen des Prinzips der losen Kopplung wie Autonomie, flexible Bindung und Kapselung.
- Ein semantischer Mediationsmechanismus basierend auf regelbasierten semantischen Brücken und unabhängiger Ontologien unter Nutzung von Eigenschaften wie Poly­morphismus, Facetten-basierte Klassifizierung und deklarativer Entitätenmanipulation.
- Ein Machbarkeitsnachweis auf Basis einer Methodik und prototypischer Werkzeuge zur semantischen Mediation, welche das entwickelte Konzept auf den SOA-Lebenszyklus abbilden und instanziieren mit dem Fokus auf der Geschäftsprozessmodellierung, der Servicekomposition und der laufzeitorientierten Prozessausführung.

Der entwickelte Ansatz wird anhand einer Fallstudie einer beispielhaften verteilten Organisation evaluiert. Es wird gezeigt, wie der Ansatz in der Praxis angewendet werden kann und welche Vorteile sich daraus für die effektive und effiziente Erreichung der semantischen Interoperabilität in groß angelegten SOA-Landschaften ergeben.


After finishing my studies, I made an internship at the United Nations Headquarters, where I attended a conference called Web for development. A marketing vice president from a large IT company gave a presentation on how service-oriented architectures (SOA) can accelerate development. After the talk a question came from the audience asking to further elaborate on how SOA can foster development in Africa. This misunderstanding has shown me that semantic interoperability - or the absence of it - is not only an abstract concept but can be found all around us even though often not visible and identified as such. Another example was the organization-wide knowledge management system, which could not be adopted in the eGovernance department I was working for, because the general terms and categories did not match the required differentiation and perspective for this practice area.

These practical experiences and the unexploited potentials for organizational synergies through seamless IT integration have motivated me to undertake my research on semantic mediation, when I started to work at the eGovernment competence center of the Fraunhofer Institute for Open Communication Systems (FOKUS).

Doing a PhD is an endeavor with many challenges. Especially in a dynamic environment driven by client-orientation, it is sometimes hard to find the time besides all the daily project work. However, it is just this combination at FOKUS covering theoretical research and real-world client projects, which provides a unique opportunity to understand the multiple dimensions and challenges ofIT integration in cross-organizational contexts, for which I am very grateful.

In particular, I want to thank my two PhD supervisors: Prof. Dr. Radu Popescu-Zeletin for the discussions, his encouragement and practical advice at key points of my PhD project and Prof. Dr. Bernd Mahr for his conceptual advice and motivating feedback. I also express my gratitude to Prof. Dr. Mathias Weske for serving as the external reviewer of my dissertation and for his helpful comments. Furthermore, I want to thank my department head Gerd Schürmann for giving me the freedom of a home office Friday in the second phase of the PhD. A big thanks goes to my colleague and office mate Dr. Matthias Flügge for sharing his experiences and for the discussions and feedbacks especially during paper publication. I also want to thank Prof. Dr. Adrian Paschke for the joint work we have done for the iSemantics and European Semantic Web Conference in 2010. Additionally, I thank my students, especially Ralf Weinand, Elena Antonenko and Johannes Böttcher for supporting the development of the semantic mediation toolkit.

To close the cycle in this personal preface I am referring back to my internship with the United Nations. The second part of it brought me to Dakar in Senegal, West Africa to support the launch of a Web community platform for eGovernance practitioners in the region. During that time I met my wonderful wife Anta. The internship was over and I was working on semantic mediation of IT systems. But the same time I found myself heavily involved in semantic mediation with her, her family and relatives trying to bridge continents, languages and different cultures. Finally, I am happy and proud that I can write about this twofold semantic mediation success story and herewith dedicate this work to my wife Anta and our five month old son Junus.

Berlin, May 2011

List of Figures

Figure 1-1 Thesis Structure

Figure 2-1 Semantic Interoperability Gap

Figure 2-2 Service Interaction Model

Figure 2-3 Enterprise SOA Layers [32]

Figure 2-4 SOA Layer Model

Figure 2-5 Service Model

Figure 2-6 Framework of Semantic Interoperability in SOA

Figure 3-1 Cross-Organizational Communication using HTTP and XML [37]

Figure 3-2 Web Service Interaction Model

Figure 3-3 Flow-based Web Service Composition [43]

Figure 3-4 Web Service Stack

Figure 3-5 Development Environment for Process Design

Figure 3-6 WSDL-based Web Service Model

Figure 3-7 Human Interaction in Web service technology based SOA-Life-Cycle

Figure 3-8 Placement of XML in the Semantic Interoperability Gap

Figure 3-9 Typical Knowledge Representation System based on Description Logics [70]

Figure 3-10 Semantic Web Stack

Figure 3-11 XML Serialization ofRDF

Figure 3-12 Classification of Semantic Web Service Concept [99]

Figure 3-13 Exemplary Web Service Ontology [100]

Figure 3-14 Generic Semantic Web Service Grounding

Figure 3-15 Machine-based Interpretation ofWeb Services

Figure 3-16 Semantic Integration with Semantic Web Services

Figure 3-17 Top Level of OWL-S Service Ontology [107]

Figure 3-18 WSMO Top LevelNotions [103]

Figure 3-19 SAWSDL Overview [118]

Figure 3-20 Shift of Abstraction Level using Semantic Web Services

Figure 3-21 Global-as-View [130]

Figure 3-22 Local-as-View [130]

Figure 3-23 RM-ODP Inter-Domain Communication Architecture [134]

Figure 3-24 Three Ontology-based Semantic Integration Strategies [139]

Figure 3-25 Example Ontologies with Mappings [140]

Figure 3-26 Basic Steps in Ontology Mapping

Figure 3-27 Step 1 of Ontology Mapping: Mapping Discovery

Figure 3-28 Step 2 of Ontology Mapping: Mapping Representation

Figure 3-29 Step 3 of Ontology Mapping: Mapping Deployment

Figure 3-30 Step 4 of Ontology Mapping: Mapping Application

Figure 4-1 From Monolithic to Loosely Coupled Information Models on Domain Level

Figure 4-2 Shift of Semantic Integration with Loosely Coupled Ontologies

Figure 4-3 Semantic Standardization vs. Semantic Mediation

Figure 4-4 Integration of Multiple Interface Technologies vs. Web Service Standards

Figure 4-5 Consensus Degree and Appropriate Scope of Standards [167]

Figure 4-6 Model of Conception [170]

Figure 4-7 Model of Conception Applied to Information Models

Figure 4-8 Constructive Model Relations

Figure 4-9 Constructive Model Relations and Information Models

Figure 4-10 Transfer ofLoose Coupling to the Semantic Level

Figure 4-11 Dimensions of Coupling [175]

Figure 4-12 Degree of Coupling and Functional Distance [176]

Figure 4-13 Definition ofLoosely Coupled Information Models

Figure 4-14 Point-to-Point Mediation

Figure 4-15 Pivot Ontology based Standardization

Figure 4-16 Semantic Mediation on Domain Level

Figure 4-17 Effectiveness and Efficiency Gain

Figure 4-18 Heterogeneous Domain Information Models

Figure 4-19 Semantic Bridge Operation (Step 1)

Figure 4-20 Semantic Bridge Operation (Step 2)

Figure 5-1 Domain Actor Model for Semantic Mediation Methodology

Figure 5-2 Semantic Mediation Methodology

Figure 5-3 Scoping ofDomain Ontologies Aligned to Organizational Structures

Figure 5-4 Protégé Ontology Editor [191]

Figure 5-5 Semantic Mediated Business Process Modeling

Figure 5-6 Functional Architecture Mediated Business Process Modeling

Figure 5-7 Semantic Extension ofBusiness Process Modeling Notation

Figure 5-8 Mediation between Business and IT Perspective [199]

Figure 5-9 Big Picture Semantic Bridge Definition [201]

Figure 5-10 Required Entity Manipulation between Different Semantic Sub-Graphs

Figure 5-11 Graphical representation of a mapping rule in Snoggle [209]

Figure 5-12 Basic Idea ofSemantic Bridge Testing

Figure 5-13 Functional Architecture of Semantic Bridge Testing Tool

Figure 5-14 Basic Idea of Semantic Web Service Enrichment

Figure 5-15 ASSAM WSDL to OWL-S Annotator GUI [222]

Figure 5-16 Basic Idea of Mediated Service Composition

Figure 5-17 Functional Architecture of Mediated Service Composition

Figure 5-18 SATINE Composition Phases and Tools [230]

Figure 5-19 Basic Idea of Mediated Process Execution based on BPEL

Figure 5-20 Functional Architecture of Mediated Process Execution

Figure 6-1 System Architecture of Mediated Business Process Modeling Tool

Figure 6-2 GUI ofMediated Business Process Modeling Tool

Figure 6-4 Polymorph Information Entities embedded in BPMN

Figure 6-3 Realization of Semantic Mediation Mechanism

Figure 6-5 Realization of Semantic Pool

Figure 6-6 Purchase Order Mediation Scenario Overview [246]

Figure 6-7 Scenario Performed with Mediated Business Process Modeling Prototype

Figure 6-8 System Architecture of Semantic Bridge Testing Tool

Figure 6-9 Test Project Ontology

Figure 6-10 GUI of Semantic Bridge Testing Tool

Figure 6-11 Heterogeneous Domain Ontologies "Blue" and "Moon"

Figure 6-12 Example Mapping Rules Created with Snoggle Mapping Tool

Figure 6-13 Semantic Bridge and Polymorph Classification Example

Figure 6-14 System Architecture ofMediated Service Composition Tool

Figure 6-15 GUI ofMediated Service Composition Tool

Figure 6-16 eGovernment Scenario for Mediated Service Composition

Figure 6-17 System Architecture ofMediated Process Execution Engine

Figure 6-18 Typed Container in BPEL Variable

Figure 6-19 Mediated Process Execution in Semantically Enhanced Process Engine

Figure 6-20 Purchase Order Mediation Scenario and Semantic Extensions

Figure 7-1 Task-oriented Isolated IT Applications

Figure 7-2 Overview of Chambers Service-Oriented Architecture

Figure 7-3 General Approach ofData Conference Working Group

Figure 7-4 Data Conference Methodology

Figure 7-5 Planned Mediation Services of Chambers Service Hub

Chapter 1 Introduction

1.1 Background and Motivation

The last two decades have shown a major shift from stand-alone to networked information technology (IT) systems. Today, networked IT systems based on the infrastructure of the World Wide Web provide the technological backbone of enterprise ecosystems enabling various business process chains and networks within and across organizational borders. Consequently, the effectiveness and efficiency of integration of independent and distributed IT systems is of great practical importance, which can already be seen by the estimation that up to 40% of companies" IT budgets are spent on integration issues [1]. Considering historically grown and heterogeneous IT landscapes, the ability of organizations and their IT systems to work together - namely by ensuring interoperability - is the key factor for achieving seamless business processes. Consequently, cross-organizational interoperation of IT systems becomes a critical business success factor [2].

Interoperability can be understood along three dimensions: technical, semantic and organizational interoperability [3]. Although the concept of service-oriented architectures (SOA) [4] and widely accepted Web service standards [19] have benefited technical interoperability in recent years substantially, managing and integrating semantic differences in heterogeneous distributed environments remains critical and cost intensive [5]. In fact, case studies have shown that 60-80% of the resources of integration projects are spent on reconciling semantic heterogeneities [6].

To provide an example, a distributed organization such as the German Chamber of Industry and Commerce with 80 decentralized sites can be considered. The sites are operated by four different IT service providers resulting in a heterogeneous IT landscape. In order to establish organization-wide business processes, in particular existing historically grown information models of different providers need to be integrated. The semantic integration challenge further increases taking into account the various external business partners to be integrated in cross- organizational business processes.

In order to preserve the precise meaning as data is moved from one IT system to another, ontologies have evolved as the concept of choice from academia to first industry adoption. Ontologies provide the means for generating explicit formal information models of a domain that can be shared between applications. The description logic-based expressiveness of ontologies not only enables humans to develop, discuss and agree on shared conceptualizations but also enables machines to interpret these information models in a meaningful manner across different IT systems.

However, the dominant approach of developing one common ontology-based standard for information exchange, which has to be globally shared by all actors in a distributed IT ecosystem, has turned out to be limited in real world cross-organizational contexts. In practice, organizational boundaries and the complexity deriving from different requirements on information models hinder the overall commitment to one common conceptualization. Thus, ontology-based standards could only alleviate the problem of semantic heterogeneity and a mapping between ontologies originating from different contexts is needed [7]. Consequently, diverse SOA landscapes covering multiple independent organizations require a more flexible information architecture to achieve semantic consistency while allowing for and accepting different conceptualizations.

1.2 Overall Goals and Scope

The core concept of SOA is the decomposition of complex business processes into a composition of loosely coupled independently managed services providing distinct business functionalities. The guiding idea of this work is that the same principle of loosely coupled units can be applied to information models, in order to capture the complexity of semantics in distributed IT ecosystems.

According to this principle, the overall goal of this thesis is to contribute to the reduction of complexity in semantic system integration by analyzing, designing, instantiating and evaluating an information architecture pattern for large-scale SOA landscapes based on semantic mediation between loosely coupled information models.

The concept should take into account the realistic perspective of different conceptualizations and resulting information representations that need to evolve independently from each other to serve best for their domain. Therefore, the concept should allow for autonomous management of self-contained information models of independent business domains. Furthermore, the concept should target semantic interoperability on the level of domain models rather than addressing it recursively during process integration on the application level. In order to facilitate semantic consistency in cross-organizational SOA scenarios, these heterogeneous domain-specific information models should be interlinked in a loosely coupled manner by means of an effective and efficient semantic mediation mechanism. The mechanism has to provide a high level of expressiveness that enables to reconcile complex semantic heterogeneities between information representations from different domain models. And at the same time the mechanism should be easy to handle. Thus, declarative approaches should be favored in contrast to procedural ones in order to assure efficient maintainability.

Moreover, a technology instantiating the concept of semantic mediation should be developed. To reap the benefits of explicit semantic formalizations, it should be based on emerging Semantic Web technologies. In particular domain ontologies and description logic rules should be exploited to describe ontology mappings in terms of so called semantic bridges [8]. Semantic bridges provide declarative reasoning-based means which can be integrated in SOA scenarios for aligning heterogeneous information models and thus ensure semantic interoperability by remaining organizational independence. However, taking into account technological path dependency in SOA, already existing traditional XML-based Web service technology should be respected and therefore the approach should be realized as an additional semantic layer on top of existing technology.

Given the horizontal nature of semantic interoperability, implications of the approach of semantic mediation to the SOA life-cycle should be derived with a focus on cross- organizational aspects. Consequently, the approach should be applied to key steps of the SOA life-cycle from conceptual business process modeling, over service composition to runtime process execution. The therefore required technologies should be bundled in a semantic mediation toolkit, which finally should be evaluated in terms of a case study of an exemplarily distributed organization.

To summarize, the objectives of this work are to:

- provide problem awareness in terms of a framework of semantic interoperability in SOA used to analyze the state-of-the-art and outline open challenges;
- develop a concept for semantic mediation between loosely coupled information models in SOA;
- design a semantic mediation methodology that applies the approach to the SOA life­cycle;
- instantiate key steps of the methodology in terms of a semantic mediation toolkit;
- and evaluate the semantic mediation approach in terms of a case study of an exemplary distributed organization.

The identified overall goals and objectives are further refined in the following section covering the methodology of this work and its research hypothesis.

1.3 Methodology

1.3.1 Scientific Hypothesis and its Confirmation

Based on the above presented overall goals and objectives the scientific hypothesis of this work can be formulated as follows:

In order to effectively and efficiently achieve semantic interoperability in large- scale cross-organizational service-oriented architectures, the principle of loose coupling can be applied to information models based on a flexible semantic mediation mechanism using Semantic Web technology for autonomous management and integration of domain-specific information models in terms of self-contained ontologies.

To confirm the hypothesis a systematic approach is followed. The research methodology is aligned to the approach of design research in information systems. Design research has its origin in engineering and sciences of the artificial [9]. The approach is motivated by improving the state-of-the-art in terms of solving practical problems, whereby the utility of the solutions is focused. In the context of the design paradigm, understanding and knowledge of the problem domain and its solution are achieved by construction and application of designed artifacts. Information systems artifacts are defined as constructs (vocabularies and symbols), models (abstractions and representations), methods (sequence of activities) and instantiations (implemented and prototype systems) [10]. The results of design research in information systems are useful artifacts built to address an organizational problem.

Corresponding to the basic steps in design research [11], the confirmation of the hypothesis is structured in five consecutive parts. For each general step in design research the concrete artifact produced in this work is further specified:

1. Awareness of a problem - Framework of Semantic Interoperability in SOA and State- of-the-Art

This work addresses the problem of achieving semantic interoperability in large-scale cross- organizational service-oriented architectures. Therefore, based on literature review, definitions and models of semantic interoperability are analyzed including their context to other dimensions of interoperability such as technical and organizational interoperability. An aggregation of conceptual models for semantic interoperability is further specified to the focused domain of SOA. Consequently, a conceptual framework of semantic interoperability in SOA has to be derived to deepen the understanding and providing a consistent conceptualization of the problem area. The framework then is utilized as a reference point for comparison in the following chapters of this work. Furthermore, an analysis is given discussing advantages and limitations of state-of-the-art approaches and technologies for achieving semantic interoperability in SOA, whereas it is referred to the previously developed framework.

2. Suggestion - Concept of Semantic Mediation between Loosely Coupled Information Models

The guiding idea of this work is to transfer the concept of loose coupling to the semantic level. In contrast to limitations of state-of-the-art approaches based on one common information model to be globally-shared as a lingua franca, this work develops a concept based on multiple coexisting information models. It aims to provide a flexible information architecture pattern that allows for autonomous management of distinct information models, whereas a semantic mediation mechanism provides loose coupling between them to ensure semantic interoperability. In particular, the claimed effectiveness and efficiency of the developed approach is addressed by a comparative analysis. The concept is further concretized by relating it to formal ontologies representing information models of specific domains. Furthermore, the concept introduces a description logic rules-based ontology mapping approach, in order to realize the semantic mediation between the heterogeneous domain ontologies.

3. Development - Semantic Mediation Methodology for SOA Life-Cycle and Semantic Mediation Toolkit

By means of a connecting step between theory and experiment, the theoretical concept is mapped to the concrete application domain of SOA. A specific semantic mediation methodology is developed that determines the basic steps relevant for the application of the concept of semantic mediation to the SOA life-cycle. In order to instantiate key steps of the methodology and to provide an experimental confirmation, a prototypical toolkit based on Semantic Web technologies is designed and developed. The toolkit integrates existing components and services and is extended with key tools required for semantic mediation in the SOA life-cycle. In particular, the semantic mediation toolkit addresses the design of semantic bridges in terms of ontology mapping rules, their systematic testing, their integration into business process modeling, as well as into service composition and finally into runtime execution infrastructures.

4. Evaluation - Case Study of an Exemplary Distributed Organization

The evaluation of the developed approach of semantic mediation is addressed from a practical perspective investigating its effectiveness and efficiency in comparison to state-of- the-art approaches. For this purpose the developed methodology and the toolkit is mapped to an exemplary distributed organization in terms of a case study. Thus, the potential of the semantic mediation concept is demonstrated. Finally, the originally set goals and the derived research hypothesis are recalled and discussed, in order to access how and to which extent they could be covered and whether the claims of the research hypothesis could be confirmed.

5. Conclusion

The conclusion summarizes the before described steps and points out the main conceptual conclusions and scientific contributions in a condensed manner. Furthermore, remaining open issues are discussed and potential extensions and future work is outlined.

1.3.2 Research Questions and Technical Challenges

In the above outlined multi-step process for the confirmation of the hypothesis various challenges have to be overcome. In the following, the central research questions and technical challenges are outlined.

Challenges in Step 1: Framework of Semantic Interoperability in SOA and State-of-the- Art - Semantic interoperability is an abstract concept, which frameworks about interoperability often do not clearly distinguish from related aspects such a syntactical or structural interoperability originating from a more technical perspective or with pragmatic interoperability leading to a more organizational perspective. The framework to be developed should differentiate between these aspects and define the scope of semantic interoperability as it is addressed in this work.

- The framework of semantic interoperability should be expressive enough to compare various approaches possibly following opposing concepts. The range should cover industry- based state-of-the-art approaches to academic-driven ontology-based ones on the one hand and as well approaches based on shared homogeneous information models following a semantic standardization approach to approaches accepting and focusing on heterogeneous conceptualizations on the other hand.

Challenges in Step 2: Concept of Semantic Mediation between Loosely Coupled Information Models

- It should be investigated why on the one hand, the success of widely accepted Web service standards for SOA has benefited technical interoperability substantially in recent years, but on the other hand, standardization on the semantic level has turned out to be limited in the cross-organizational context. Therefore, analogies from other fields of standardization should be derived, in order to examine the relation between consensus degree and adequate scope of standards and its implication for the semantic level.

- Furthermore, it should be investigated how context dependency of information models influences heterogeneous conceptualizations and how this relates to limiting factors for their monolithic alignment. Therefore, a model theoretic approach should be mapped to information models.

- The transfer of the concept of loose coupling to information models implies that the central principles of loose coupling are addressed. Therefore, the question should be addressed how principles such as autonomy, encapsulation and flexible binding can be applied to the semantic level and how these characteristics can be interpreted to provide a specification of loosely coupled information models and a corresponding semantic mediation mechanism.

- Having identified the practical limitations of semantic standardization across organizational boundaries, a trade-off between effectiveness and efficiency for achieving semantic interoperability becomes apparent. On the one hand, N actors have to develop an agreement in terms of a community process about one common standardized information model. However, with regard to cross-organizational and heterogeneous IT landscapes with a large number of actors N with possibly divergent business requirements, a high coordination complexity appears hindering an effective solution. On the other hand, aiming at an approach which is based on direct mediation between each two independent information models just requires coordination efforts for two actors, which results in lower complexity. However, this effort could be potentially become necessary N x N times to map between each two information models. Thus, both general approaches do not provide a sufficient solution regarding effectiveness on the one side and efficiency on the other side. Therefore, an adequate solution within this trade-off needs to be addressed by the developed concept of semantic mediation.

- As the developed concept for semantic mediation is designed to be based on Semantic Web concepts and technologies, it needs to be pointed out which specific features of Semantic Web languages and meta-models are the beneficial and enabling factors for the semantic mediation approach compared to other technologies.

Challenges in Step 3: Semantic Mediation Methodology for the SOA Life-Cycle and Semantic Mediation Toolkit

In order to develop the methodology and toolkit, the relevant phases of the SOA life-cycle where mediation between heterogeneous information models is required need to be identified and the afore-developed conceptual solution needs to be applied.

- The SOA life-cycle starts from the business perspective on how processes can be supported by IT systems. Therefore, with regard to semantic mediation the modeling of cross- organizational business processes should be covered, whereas the modeling of information flow across heterogeneous conceptualizations is of particular concern. In order to ease the modeling of business processes and reduce technical complexity, the heterogeneity between different information models should be transparent for the user and its resolution should be handled automatically based on underlying semantic bridges. This implies that required information models and semantic bridges are already in place. Furthermore, coming from the perspective of agile development and continuous maintenance, information models need to evolve over time and correspondingly semantic bridges between them. According to process-orientation, the requirements for the evolution should be derived from business processes. Consequently, specific features for requirement engineering of information models and semantic bridges should be supported during cross-organizational business process modeling.

- The identified requirements provide a foundation for the development and testing of semantic bridges. As first prototypical tools for the development of semantic mappings are already available, they can be exploited in an adequate manner, in order to define semantic bridges according to the requirements of the developed semantic mediation mechanism. Furthermore, taking into account that semantic bridge developers and users such as process experts or Web service composers are divided into different roles and may originate from different organizational contexts, the consideration of trust in the quality of the underlying semantic mappings is essential. Therefore, an approach and tool for testing of semantic bridges should be provided. The focus should be put on how to apply concepts from software testing to testing of ontology mappings.

- Having all required assets such as business process models, information models and quality assessed semantic bridges at hand; the consequent next step of the SOA life-cycle is the composition of services to instantiate the business process. Therein, the explicit semantic description of information models and formalized semantic bridges between the involved heterogeneous information models should be exploited for seamless information flow design between the services to be composed. One particular challenge lies in the consideration of technological path dependency. On the one hand, the dominant instantiation of SOA is based on Web service technology, which relies on the XML and XML schema meta-data model. On the other hand, the meta-data model applied for the semantic mediation approach is based on ontology concepts and description logic based rules. Thus, a challenge is to integrate as well an appropriate mapping mechanism between these two meta-data models and realize the solution as an additional layer on top of existing technology.

- After design time, the runtime execution of Web service compositions takes the focus in the SOA life-cycle. Again, well established industry standards should be considered. On this regard especially the industry standard BPEL [12] should be addressed, which relies on the XML meta-data model, too. Therefore, components providing Semantic Web technology have to be incorporated into BPEL-based process integration middleware and the different meta-data models need to be reflected on the runtime level. Another challenge thereby lies in ensuring a reasonable performance during the rule-based inferencing process, which still often remains a bottleneck of Semantic Web technology.

Challenges in Step 4: Case Study of an Exemplary Distributed Organization

- The evaluation needs to address how the potential of the developed methodology and toolkit for loosely coupled domain-specific ontologies can be qualitatively analyzed and demonstrated. Therefore, a case study is carried out in context of a research transfer project with the German Chambers of Industry and Commerce. The Fraunhofer Institute for Open Communication Systems (FOKUS) supports the introduction of an SOA-based IT integration infrastructure to the German Chambers of Industry and Commerce consisting of 80 decentralized sites, which are operated by four different IT service providers. In particular, the activities of the data conference working group targeting the development and alignment of organization-wide information models and semantic integration with external business process partners in the larger eGovernment context are subject to the evaluation. In this process, shortcomings of applied state-of-the-art practices and technologies need to be pointed out and compared to the potential provided by the developed semantic mediation approach.

1.4 Outline of the Thesis

After having discussed the objectives and the methodology of the work, this section outlines the structure of the thesis. The thesis is organized in 8 chapters, which are derived straightforward from the applied methodology of design research as illustrated in the following figure:

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Figure 1-1 Thesis Structure

Chapter 1 gives the motivation and background of this work, its goals and scope and the research hypothesis and methodology structuring this thesis.

Chapter 2 provides an understanding of the challenge to achieve semantic interoperability in cross-organizational service-oriented architectures. Finally, a conceptual framework of semantic interoperability in SOA is elaborated, in order to provide a foundation for comparison in the following chapters.

Chapter 3 then performs a systematic state-of-the-art analysis of existing approaches. Conceptual ideas, technologies and standards for achieving semantic interoperability in SOA originating from different backgrounds ranging from industry to academia are presented and are evaluated against the before developed framework.

Chapter 4 presents the core part of this work namely the concept of semantic mediation between loosely coupled information models in SOA. The transfer of the principle of loose coupling to the semantic level is discussed based on a conceptual argumentation ranging from the limitations of semantic standardization to context dependency of information models and its consequences for semantic interoperability in cross-organizational SOA. Finally, a specification of loosely coupled information models in SOA is provided including a developed conceptual approach for a corresponding semantic mediation mechanism.

Chapter 5 provides an intermediate step between the developed theory and its application and presents a derived semantic mediation methodology. It maps the concept to the SOA life-cycle ranging from business process modeling, over service composition to runtime process execution. It describes how the semantic mediation approach can be integrated within these phases, in order to improve effectiveness and efficiency in achieving semantic interoperability.

Chapter 6 presents the developed semantic mediation toolkit, which instantiates key steps of the before developed methodology. It includes prototypical tools for mediated business process modeling, semantic bridge testing, mediated service composition and mediated process execution. Its realization by means of a combination of state-of-the-art Web service technologies and emerging description logic based Semantic Web technologies is described with regard to design and development aspects.

Chapter 7 evaluates the developed approach for semantic mediation. Based on a case study of an exemplarily distributed organization, namely the German Chambers of Industry and Commerce, the semantic mediation methodology and the potential of the developed toolkit are assessed. On the basis of this analysis, the coverage of the originally set conceptual goals and the confirmation of the research hypothesis are discussed.

The final Chapter 8 provides a conclusion of the thesis and recalls the fundamental concepts and ideas of the proposed approach for semantic mediation between loosely coupled information models in SOA. Moreover, remaining open issues and potential advancements are discussed. Finally, an outlook on future developments and priorities in this area is outlined.

Chapter 2 Understanding the Challenge of Semantic Interoperability in SOA

2.1 Overview

The introduction has already outlined that interoperability is the enabling factor to achieve IT - supported business processes across intra- and inter-organizational boundaries. The mentioned estimation that enterprises and organizations today spend up to 40% of their IT budget on integration projects [1] further points out the relevance and shows that interoperability has become a crucial competitive factor. Taking into account this background, it becomes comprehensible that the promise to advance interoperability has been a central success factor for the adoption of SOA. However, focusing on a particular dimension of interoperability, namely semantic interoperability, still substantive limitations have to be overcome as managing and integrating semantic differences in heterogeneous distributed environments remains critical and cost intensive [5]. As this work aims at advancing the way semantic interoperability in cross- organizational SOA is achieved, firstly the problem area of this particular interoperability dimension is analyzed.

This chapter begins by setting the scope of the addressed problem and putting semantic interoperability into the context of related dimensions of interoperability. Then, existing conceptual models dedicated to semantic interoperability are reviewed and interpreted from the perspective of SOA. Furthermore, in order to develop a framework for comparison of existing and emerging approaches, an aggregation of the analyzed conceptual models is derived. The derived framework should deepen the understanding and provide a consistent conceptualization of the problem area to be utilized as a reference point in the following chapters. Thereby, the framework is limited to a descriptive scope with a clear distinction to the description of a solution as targeted in the conceptual part of this work.

2.2 Interoperability Dimensions

In the context of the European Union's Information Society activities, interoperability is defined as the ability of information and communication technology systems and of the business processes they support to exchange data and to enable the sharing of information and knowledge [3]. In order to understand the nature of interoperability, it is important to note that interoperability is not a static property, which is provided or not, but rather a continuous degree which can be achieved to a lower or higher extent. According to this conception, a further definition states that interoperability is the ongoing process of ensuring that the systems, procedures and cultures of an organization are managed in such a way as to maximize opportunities for exchange and re-use of information, whether internally or externally [13].

Given such a wide scope within the suggested definitions, it becomes useful to further subdivide the notion of interoperability. The European interoperability framework distinguishes between three main interoperability dimensions [3]:

- technical interoperability, which is concerned with the technical issues of linking up computer systems, the definition of open interfaces and telecommunication protocols
- semantic interoperability, which is concerned with ensuring that the precise meaning of exchanged information is understandable by any other application not initially developed for this purpose
- organizational interoperability, which is concerned with modeling business processes, aligning information architectures with organizational goals and helping business processes to co-operate

Other frameworks about interoperability introduce further dimensions to be considered, such as the political context including cultural aspects or legal interoperability dealing with the alignment ofheterogeneous legal environments that my hinder integration [14].

However, as this work addresses the dimension of semantic interoperability, deeper analysis should be given with a finer granularity on its context within the three interoperability dimensions presented above.

2.2.1 The Context of Semantic Interoperability

In [15] a changing focus on interoperability of information systems is discussed: from system, over syntax and structure to semantics. Thereby, several types of heterogeneity are identified with according types of interoperability:

- System - differences between hardware, operating systems, protocols etc. ;
- Syntactic - incompatibilities in encodings and formats;
- Structural - differences in representation and schemata;
- Semantic - inconsistencies in terminology and meanings.

In this sense, system interoperability corresponds to the common understanding of technical interoperability as outlined above in context of the European interoperability framework. However, the above presented perspective identifies further aspects between technical and semantic interoperability. On the one hand, syntactic interoperability can be referred to the ability of different systems to interpret the syntax of data the same way, i.e. to share common rules how parts of data can be arranged together. In particular, this deals with technical aspects such as the alignment of common APIs, interchange formats and messaging standards. And on the other hand, structural interoperability can be identified, which refers to the ability to align different data representations based on differently structured schemata. Taking into account that schemata relate to specific domains or applications, it points out that the structure of data in terms of schemata captures partly - in terms of a limited view - the aspect of meaning. Thus, it can be stated that structural interoperability is closer related to semantic interoperability than syntactical interoperability, as syntax is generally more independent and generic from the specific domain or application context of IT systems.

However, semantic interoperability covers further aspects than discussed in context of structural interoperability. Data representation in terms of schemata cannot capture the entire meaning as they lack the description of context of data and explicit description of relations between data, which constitute fundamental aspects of meaning [16]. From the research area of linguistics a further aspect comes into the play and the before discussed field is broken down into the three branches [17]:

- Syntactics - relation of signs to each other in formal structures;
- Semantics - relation between signs and the things they refer to;
- Pragmatics - relation of signs to their impacts on those who use them.

With regard to interoperability, the aspect of pragmatics is reflected and referred to the pragmatic interoperability problem, which arises when the sender's intended effect of a message differs from the actual effect of the message performed by the receiver [18]. In SOA, this is the case when there is insufficient insight in the interworking of services and their interdependent behavior [283]. This problem can be overcome by means of languages that define so called service choreographies [284]. In [285] choreographies are defined as complex interactions with behavioral dependencies between the contained interactions. Consequently, this aspect on how information is processed depending on its dynamic or behavioral context, points out the relation to the dimension of organizational interoperability with its particular focus on business process alignment between different actors as identified in the European interoperability framework.

This section has analyzed the different dimensions of interoperability and positioned semantic interoperability within these dimensions. With regard to technical interoperability, the aspect of structural interoperability in terms of mismatching schemata has been identified as partly overlapping with semantic interoperability. On the other hand, the aspect of pragmatic interoperability has been identified as bridging the gap between semantic and organizational interoperability.

While the requirement for interoperability in all three dimensions seems obvious, it is a fact that IT systems today are not interoperable in the way that seamless process integration can be realized to its full potential. Only with the ubiquity of internet technologies based on open standards and specifications namely TCP/IP, HTTP and SMTP etc., it has been possible to achieve a high degree of technical interoperability. In this context, the recent developments of Web service standards [19] along with the advent of the SOA paradigm, which are discussed in more detail in the next chapter, have to be highlighted as well. However, in order to enable IT systems to exchange and combine information and accordingly process it in a meaningful manner, it requires agreement on more complex issues, such as the relation to the context within information is created and used and consensus on how to represent meaning of data in principle.

As this work focuses on semantic interoperability in SOA, the following section focuses particularly on the semantic dimension of interoperability. The scope for semantic interoperability as targeted in this work is pointed out taking into account the overlapping aspects identified above. Furthermore, the dimension of semantic interoperability is broken down to the targeted domain of SOA.

2.3 Semantic Interoperability

The quest for meaning in language has a history that is almost as old as language itself [20]. Accordingly, the challenge to achieve semantic interoperability of IT systems is an ongoing effort since the advent of distributed IT environments. In this process, is has turned out that semantic interoperability requires much more than a simple agreement concerning the isolated meaning of a term but rather depends on the individual context [20].

2.3.1 Terms as Representation of Meaning

To further understand semantic interoperability, an analysis of the words meaning and term is required. In linguistics, meaning is considered as a human artifact [21]. In this sense, terms as well as things to which terms refer have no meaning per se. The meaning is assigned to them by human beings. In order to exchange the meaning, which is subject of semantic interoperability, it has to be encoded by utilizing terms[1], whereas inherently never all facets of meaning can be represented but restrictions have to be made according to an individual context. Thus, a first distinction can be made between the meaning as a human artifact or conceptual idea on the one hand and the term which represents the meaning on the other hand.

To further analyze the semantic interoperability problem, which occurs if the exchanged terms do not refer to the intended meaning, the characteristics of terms as a representation of meaning in context of IT systems should be elaborated. According to system design in informatics, terms that represent meaning refer to information models which can be distinguished along different abstraction levels. This distinction between different abstraction levels for representation of meaning provides the starting point and foundation of the envisaged conceptual framework for semantic interoperability in SOA, which is presented in the following section.

2.3.2 Abstraction Levels for Representation of Meaning

Following the paradigm of separation of concerns, each different abstraction level for the representation of meaning is used for a specific purpose. The starting point in IT system design are highly abstract modeling languages, which should be closely related to the actual meaning or conceptual idea in the mind of human beings. Such highly abstract modeling languages are e.g. the Unified Modeling Language (UML) [22] or the Entity-Relationship Model (ER) [23]. In order to be used in a concrete application context, these information models need to be broken down to a lower application specific level. Considering the common database design methodology of different abstraction levels, it can be distinguished between:

(1) the Conceptual (2) the Logical and (3) 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 a more concrete 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.

In order to get a consistent picture and integrate the above described analysis regarding terms as representation of meaning, a further abstraction level can be added on top of the presented levels. Accordingly, in the following the conceptual idea or the meaning in the human mind is considered as the initial model of a thing or information. Consequently, it can be distinguished between the following abstraction levels:

(0) the Conceptual Idea (1) the Conceptual Data Model (2) the Logical Data Model and (3) the Physical Data Model

A further reference to these basic abstraction levels for information models can be found in the context of model driven architecture (MDA) [24] for modeling software systems from the Object Management Group (OMG) [25]. MDA focuses on functionality and dynamic behavior, however the static data-oriented part can be related to the identified abstraction levels. The MDA viewpoints distinguish between:

(1) Computation Independent Model (CIM) - The computation independent model focuses on the environment of the system and the requirements for the system. A CIM does not show details of the structure of systems. It is sometimes called a domain model, whereas a vocabulary that is familiar to the practitioners of the domain in question is used in its specification. Accordingly, the information model in CIM corresponds to (1) the conceptual data model described above.

(2) Platform Independent Model (PIM) - The platform independent model focuses on the operation of a system while hiding the details necessary for a particular platform. A platform independent view shows that part of the complete specification that does not change from one platform to another. Accordingly, the information model in PIM corresponds to (2) the logical data model described above.

(3) Platform Specific Model (PSM) - The platform specific model combines the platform independent viewpoint with an additional focus on the detail of the use of a specific platform by a system and the underlying implementation. Accordingly, the information model in PSM corresponds to (3) the physical data model described above.

The identified abstraction levels have further differentiated the characteristics of terms as a representation of meaning in context of IT systems and can be taken as a reference framework to further analyze semantic interoperability problems. In the following, the terminology is aligned to the identified abstraction levels in context of database system design including the initial level of the conceptual idea. However, instead of data model or information model just the term model is used. The conception of a message as data or as information depends on the user"s or receiver's ability to interpret the data according to a certain context. In a first step, this differentiation should be out of scope while the focus is put on the identification of the different abstraction levels for representing meaning by utilizing terms. In a following second step (cf. Section 2.3.3), the usage of these abstraction levels for the exchange of meaning is analyzed and then the differentiation between data and information becomes relevant.

To summarize, it can be distinguished between the following abstraction levels for representation of meaning, which provide the starting point to the framework to further analyze semantic interoperability:

(0) Conceptual Idea (1) Conceptual Model (2) Logical Model (3) Physical Model

2.3.3 Semantic Interoperability Gap

The goal of semantic interoperability is to ensure that the meaning of exchanged information is preserved in different application context in a distributed IT system. However, as the conceptual idea cannot be directly and fully formalized in an IT system and therefore not exchanged directly, the conceptual idea has to be represented by means of terms. As described above, this representation can be distinguished into the four different abstraction levels. Thereby, it is important to note that the meaning of a term is inherently dependent on the context. The expressiveness of context description thereby differs between the different abstraction levels.

The conceptual idea of a thing captures the full domain context, as it represents the initial model and constitutes a kind of master model or reference model for capturing the meaning per definition. Following the path down to the lesser abstract levels, certain context information gets reduced while the same time application specific information gets concretized. The conceptual model reduces the potentially holistic conceptual graph from the conceptual idea to the focused application domain and refines the conceptual structure such as generalization and composition of classes and its attributes. In a further step, the logical model reduces explicit context description between concepts, in order to map the representation to an application specific level. Thus, logical operations can be well defined on a sufficiently concrete level to enable machine interpretation and processing. On the physical level, context is only encoded implicitly on a technical level specific to the IT system performing the application.

Regarding information exchange, this explicit context description or lack of it becomes important for semantic interoperability. The following Figure 2-1 illustrates a typical information exchange scenario between two IT systems based on service-oriented exchange of messages. The fundamentals for their interoperation are overlapping conceptual ideas about a domain model which describes a certain information space. The domain context may be different between the two IT systems. However, the designers share or refer to the same understanding of specific concepts, which can be located in the overlapping part of the two conceptual ideas.

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Due to the different domain context the corresponding conceptual models are different. They may also exhibit overlapping parts which are modeled consistently but they may also differ completely and thus only with the reference to the conceptual idea the corresponding parts can be identified. On the abstraction level of the logical model, additional differences in information representation can be identified as the logical model maps the representation to an application specific level, which further differs between IT System A and B. Thus, it can be stated that the semantic interoperability gap grows with each lower abstraction level as the differences between the representations and the conceptual idea increase. Consequently, the largest semantic interoperability gap is given if information is exchanged on the physical level as the concepts including their context relation are only encoded implicitly, which may differ completely between the two IT systems.

In order to overcome the semantic interoperability gap, the information representation needs to be interpreted - in an automated, machine-supported or manual manner - according to the next higher abstraction level. Thus, the representation gets linked to the shared understanding in the two shared conceptual ideas and semantic interoperability is ensured. Finally, in order finish the round-trip across the semantic interoperability gap and to ensure that the information gets processed by the receiving system, the information needs to be represented according to the system"s technical representation on the logical or physical level.

Moreover, it is important to note that even if in a concrete scenario a direct transformation between two different physical models or logical models is applied, the above described steps have to be performed logically and are included within the transformation as virtual steps. However, this logical analysis points out the complexity which these transformations contain.

Another, conclusion can be drawn from the above developed model for semantic interoperability: If two systems are equally designed with regard to their utilized information models on the different abstraction levels, the logical steps to bridge the semantic interoperability gap have to be performed as well. However, the actual round-trip can be shortened, if two models are equal on the same abstraction level. The above described round- trip just has to be performed up to the respective abstraction level where the models are equal. Accordingly, the semantic interoperability gap on this level is not present and therefore no reference to the upper abstraction level is required. This explains why semantic interoperability can be achieved by standardizing the representation models of information - whenever this is possible. This topic is detailed later on in Chapter 4.

Referring again to the aspects identified in the context of semantic interoperability as described in Section 2.2.1, they can be mapped to the above introduced conceptual framework: Pragmatic heterogeneity can be located at the highest level, as this level deals with the idea of a concept in the human mind including the context about the intension of sending or receiving such information. The identified aspect referred to as structural heterogeneity can be located at the logical level, as it deals with heterogeneous schemata. Syntactic heterogeneity, which addresses incompatibilities in encodings and formats, can be mapped to the physical level. Finally, what is referred to semantic heterogeneity in general in Section 2.1.1 as addressing the inconsistencies in terminology and meanings can be mapped to the level of conceptual ideas with regard to meaning and to the conceptual, logical and physical model with regard to terminology each representing the meaning on a different abstraction level. Thus, it can be stated that the developed model describing the problem of semantic interoperability captures consistently the different semantic interoperability aspects identified in current state of research (cf. Section 2.2.1).

As the aim of this chapter is to develop a framework for semantic interoperability in SOA to provide a systematic understanding of the problem addressed in this work, the above developed model describing the semantic interoperability gap needs to be mapped to the domain of SOA. Therefore, as an intermediate step, the concepts and approaches of SOA are introduced in the following section.

2.4 Service-Oriented Architecture

In [26] several definitions of SOA are introduced and compared, whereas the following unified definition is provided:

,A service-oriented architecture is a framework for integrating business processes and supporting IT infrastructure as secure, standardized services that can be reused and combined to address changing businesspriorities.“

This definition outlines two major goals of SOA, namely flexibility and reusability of IT systems. These two characteristics become particularly relevant as more and more business processes are spanning multiple organizational and administrative domains. Changing external business partners need to be flexibly integrated into IT -supported processes while reuse of IT infrastructure needs to ensure that this flexibility can be realized with regard to optimized resource spending within economic constraints.

To address these challenges, the core concept of SOA is the decomposition of complex business processes into a composition of loosely coupled independently managed services providing distinct business functionalities. IT systems supporting business processes are split of into a set of loosely coupled reusable services, whereas each service realizes one modular unit of business logic.

The architectural model of SOA is based on fundamental principles such as modularization, encapsulation and platform-independence. These principles are incorporated from prior approaches, mainly from component-based middleware platforms. Thus, SOA is no revolutionary new development but rather it is based on various known concepts and methods. However, the component-based approach implemented in platforms such as CORBA [27] or EJB [28] require the business partners to adopt a specific object model that might not be suitable for all collaborating parties [29]. Considering that the lifecycle of a component has to be managed by its consumer, the coupling between provision and usage of functionality must be still regarded as tight.

Addressing this shortcoming and extending the ability of loose coupling, the central novelty of the architectural model of SOA relies on the strict focus on the service concept. The service concept represents a further step up in abstraction for distributed IT system design [30]. Consequently, not the component capturing the business functionality takes the center stage but just the service which the component provides replaces the focal point. Thereby, the conceptual model of a service can be defined as follows [31]:

i. A service establishes an agreed relationship between partners in two distinguished roles: a service provider and a service user.
ii. A service is meant to produce benefit of a definite type to the service user and to meet the user"s needs.
iii. A service is the result generated by processes at the interface between the provider and the user and by processes internal to the provider and internal to the user.

The service model can be further refined focusing on the interaction patterns between the above identified roles of the service provider and service user. Accordingly, the service interaction model often is equated with the “find-bind-execute” paradigm. As illustrated in Figure 2-2, firstly a service provider registers a service at a registry which includes a description of the service and the business context relevant for the usage. Then, a service user interacts with the registry for finding service descriptions which fulfill certain criteria, e.g. regarding service class or non-functional properties. This refers to the user"s needs and the aimed produced benefit of a definite type (cf. ii. above). Then, the service user utilizes the service description to bind to a service provider and to invoke the provided service. Thus, the relation between service user and service provider gets established.

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Figure 2-2 Service Interaction Model

In order to enable this so called find-bind-execute paradigm, the SOA concept needs to be instantiated with an appropriate technology. In recent years, fostered by broad standardization initiatives and wide industry adoption, Web services have taken the lead role as the dominant realization approach to implement SOA. The main technologies behind Web services such as XML, WSDL, SOAP, UDDI and BPEL are analyzed in Chapter 3 with specific focus on how they address the problem of semantic interoperability in SOA.

In order to outline how the principles of the SOA model are reflected within a typical enterprise IT architecture, the following Figure 2-3 illustrates the decomposition of complex business processes into a composition ofloosely coupled Web services along the so called SOA layers:

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- The bottom layer (layer 1) contains existing business applications, which may originate from different organizational domains including e.g. customer relationship management (CRM) and enterprise resource planning (ERP) systems, legacy applications or specifically designed object-oriented systems as well as business-intelligence applications.

- The component layer (layer 2) uses typical container-based technologies and component implementation models. It enables distribution of functional components within the enterprise.

- Layer 3 provides the mechanism to make enterprise-scale components, business unit- specific components and in some cases project-specific components available as services. The interfaces are exported by means of standard service descriptions. Moreover, this layer comprises the service infrastructure (e.g. service registries).

- Layer 4 combines services and other composite services to orchestrations or choreographies which implement enterprise-wide or even cross-enterprise business processes. Visual process modeling and process execution engines are used for this purpose.

- The presentation layer (layer 5) is usually out of the scope of the actual SOA. It is important to note that generally in SOA the user interfaces are decoupled from the services. However, it is part of the figure because recent standards such as Web Services for remote portlets (WSRP) may indeed carry service functionalities directly to the application interface or presentation level.

- Layer 6 (orthogonal) enables the integration of services through the introduction of reliable and intelligent routing, protocol mediation and other transformation mechanisms, often described as the enterprise service bus.

- Layer 7 (orthogonal) ensures quality of service through sense- and respond mechanisms and tools that monitor the state of SOA applications.

Besides the runtime perspective focused in the above SOA layers, as well the design time of SOA needs to be taken into account. Such a holistic perspective is provided in terms of a so called service life-cycle or SOA life-cycle focusing less on any particular service but rather on the entire set of service from design over implementation to usage and monitoring. Even there exists no well-established definition of the term service life-cycle or SOA life-cycle, there is a common understanding about the main phases to be covered in it. Nevertheless, the phases are clustered on different granularity levels and different aspects are more or less highlighted in the various available definitions. In [33] an overview of popular definitions of the service life-cycle model is provided. In order to stick to a consistent perspective within this work, the following refers to a definition provided by IBM [34]. Accordingly, the service or SOA life-cycle can be distinguished into the following phases:

- Model - This phase is about capturing the business requirements and translating them into business process models refined by service identification and service specification.

- Assemble - This phase is about developing reusable services and composing them into service orchestration plans which instantiate the modeled business process.

- Deploy - In this phase the developed services and service compositions are tested and deployed to a runtime infrastructure.

- Manage - The last phase is about maintenance, measurement and optimization of service operations from a technical and as well from a business perspective.

In order to reflect the discussed SOA concepts within the framework of semantic interoperability in SOA described in the next section, the following Figure 2-4 presents a condensed SOA layer model focusing on the conceptually most relevant parts. Furthermore, to stress that the business processes may consist of services and underlying components from different organizational domains the corresponding layers are split as well into different domains.

illustration not visible in this excerpt

- The business process layer describes the cross-organizational business process as a composition of services (from an abstract perspective in terms of business process models and from a concrete perspective in terms of a service orchestration plan).

- The service layer describes the (heterogeneous) services which provide the distinct business functionalities.

- The business components or objects layer describes the underlying components which realize the services implementations for the middle layer.

In the following this condensed SOA layer model is incorporated as an integral part into the framework of semantic interoperability in SOA, which is presented in the next section.

2.5 Framework of Semantic Interoperability in SOA

Before relating the concept of the semantic interoperability gap introduced in Section 2.3.3 to the above described SOA layer model, a connecting step in terms of further analysis of the service artifact presented in the middle layer is elaborated. As the concept of the semantic interoperability gap has focused on information models represented on different abstraction levels, these representations need to be related to the service descriptions.

According to the Web Ontology Language for Services [35] which aims at providing a specification of a service in terms of a formal ontology, the following conceptual characteristics of a service can be distinguished:

- Inputs
- Outputs
- Preconditions
- Postconditions or Effects

In this sense, the specification of a service can be related to the mathematical concept of a function as an abstract entity that associates an input to a corresponding output according to some specific rule [36].

In the service context the input describes information which needs to be provided by the service user necessary to invoke the service and perform the provider's internal processes in order to deliver the service. The output describes information which is generated as a result of the provider's internal processes and delivered to the service user. The preconditions specify the state of the information space of the service before its execution. Moreover, preconditions can be represented as expressions that are required to be true before an operation can be successfully invoked. Vice versa postconditions describe the state of the information space of the service after the execution of the service. Postconditions can be represented as expressions that must be true after the service has been invoked and its operation completes its execution. In the following Figure 2-5 the service model as described above is illustrated:

illustration not visible in this excerpt

Figure 2-5 Service Model

Considering instantiations of this service model in concrete IT systems, these four service characteristics have an information representation in terms of the different abstraction levels for information models as introduced in Section 2.3.2:

Firstly, a conceptual idea about inputs, outputs, preconditions and postconditions is existent in the mind of an IT system designer. Later in the design process, domain specific representations of these service characteristics can be derived and captured in a conceptual model. With regard to preconditions and postconditions most state-of-the-art approaches limit the representation to textual description addressing the human reader. This is due to the fact that a fully-formal specified conceptual model that represents the preconditions and postconditions is difficult to define on a sufficient level that enables machine interpretation. Thus, further specification and concretization of the information model on lower abstraction levels such as the logical or physical model is limited, too. However, some approaches in the research field of Semantic Web services also target this aspect as further analyzed in Chapter 3.

With regard to input and output parameters, which are subject to information flow in a service composition scenario instantiating the business process model, they can be represented in a conceptual model addressing the domain context by relating the input and output parameters to other domain concepts relevant in the business process. The corresponding information model can be further specified on the logical level representing the abstraction level that is utilized when information flow is specified in a concrete application context. In order to realize the business functionality which is provided by the services, the business components or objects get involved. These components process the input and output parameters and thus need to represent the information according to their specific technical environment. Accordingly, the physical level of the information model can be located on the business components or objects layer.

Taking into account the analysis above, the service model including inputs, outputs, preconditions and postconditions provide a further detailed description of services in the SOA layer model. Moreover, the service characteristics can be represented on the different abstraction levels for describing their information models. As the SOA layer model has distinguished between heterogeneous services originating from different organizational domains, these heterogeneous services can be directly related to the semantic interoperability gap describing the heterogeneous information model representations on the different abstraction levels. Consequently, a unified model illustrated in Figure 2-6 can be derived combining the introduced SOA layer model together with the refined service model and the model describing the semantic interoperability gap.

illustration not visible in this excerpt

Hence, the derived perspective on the three models constitutes the framework of semantic interoperability in SOA as a reference point and problem description. In the following, it provides a common ground for comparison. Consequently, approaches and technologies presented in the state-of-the-art analysis in Chapter 3 as well as the concept for semantic mediation between loosely coupled information models in SOA developed in Chapter 4 refer back to this framework.

2.6 Summary and Reflection

This work addresses the problem of achieving semantic interoperability in cross-organizational service-oriented architectures. Therefore, definitions and conceptual models covering the different aspects of semantic interoperability have been analyzed in a first step. In order to define the problem scope, semantic interoperability has been put into context with related interoperability dimensions, namely technical interoperability and organizational interoperability and overlapping issues have been identified.

An aggregation of conceptual models for semantic interoperability has been developed based on the finding that different abstraction levels for representing information models are fundamental for the understanding of semantic interoperability. Consequently, a model describing the semantic interoperability gap has been derived, that demonstrates how heterogeneous IT systems differ in their information models along different abstraction levels. Starting from the conceptual idea of information in the human mind, to the conceptual model formalizing the domain context, over the logical model to the physical model representing the concrete information model on the technical level, the semantic interoperability gap between heterogeneous IT systems continuously increases. Furthermore, different fundamental approaches for achieving semantic interoperability such as alignment of terminology or transformation between heterogeneous representations could be mapped to the derived model of the semantic interoperability gap.

In order to address the targeted domain of semantic interoperability in SOA, the architectural model and basic concepts of SOA have been presented. A layer model has been elaborated capturing the central approach of SOA that lies in the decomposition of complex business processes into a composition of loosely coupled independently managed services providing distinct business functionalities. The service concept has been further analyzed to link the information model used in a service interface description to the different abstraction levels analyzed in the model of the semantic interoperability gap.

Finally, a unified model has been derived from the analysis above describing the semantic interoperability problem in the context of SOA. Consequently, the unified model forms the reference framework that provides a common ground for comparison between approaches and technologies for achieving semantic interoperability in SOA. In the following, it is referred to this framework including Chapter 3 analyzing the state-of-the-art and Chapter 4 presenting the concept for semantic mediation between loosely coupled information models in SOA.

Chapter 3 State-of-the-Art in SOA for Bridging the Semantic Interoperability Gap

3.1 Overview

Having set the scope for the addressed problem of achieving semantic interoperability in heterogeneous IT systems with particular focus on SOA in the previous chapter, the next step is to examine state-of-the-art approaches and technologies that aim at tackling the identified challenges. Even the selected approaches and technologies are often embedded into a broader context; the analysis tries to focus on the aspects particularly relevant for the topic of semantic interoperability in SOA and to limit the general aspects to the basic essentials.

In a first step, Section 3.2 reviews the idea and concepts of traditional Web services along with its existing technology stack. Furthermore, an evaluation is performed describing the capabilities and limitations of traditional Web services in context of the previously developed framework of semantic interoperability in SOA (cf. Section 2.5).

After outlining the need for formally defined semantics of Web service descriptions, an intermediate step introducing the core concepts and technologies of the Semantic Web initiative are described in Section 3.3. The following Section 3.4 then describes how these concepts can be applied to Web services in terms of so called Semantic Web services. Again, the previously developed reference framework describing the semantic interoperability gap is utilized, in order to provide an evaluation outlining the advantages, limitations and open issues of this technology.

Additionally, a survey is carried out on relevant related areas such as semantic information integration in distributed database systems and distributed object-oriented systems.

Finally, these traditional approaches are related to a detailed analysis of ontology-based strategies for semantic integration including approaches where multiple ontologies are involved. In this context, as well a number of ontology mapping approaches and exemplary tools are investigated.

3.2 Web Services

Whenever the realization of an SOA with state-of-the-art technology is discussed, the term Web service takes an important role as Web services represent the dominant technology for the instantiation of an SOA. In the last decade, Web services have gained considerable popularity. Many software vendors have adopted Web service initiatives and correspondingly provide extensive product portfolios. A large consulting market for advisory services regarding Web service technology has emerged. Furthermore, there are many organizations which are involved in the refinement of Web service standards. However, driven by marketing campaigns and the related ongoing SOA and Web service hype, often the problem remains that few people seem to actually agree on what a Web Service is [37]. The introduction in Chapter 1 has already briefly outlined the idea behind Web services and their capabilities for ensuring semantic interoperability. This section aims to provide a further detailed analysis and starts with clarifying what Web services are and how they are used to build an SOA. Furthermore, this section explains the core Web service concepts and related technologies. Finally, an analysis about the shortcomings with regard to semantic interoperability is provided.

3.2.1 Definition and Concepts

The World Wide Web consortium defines Web services as programmatic interfaces for application to application communication over the World Wide Web [38]. This definition states one major aspect that Web service interaction is usually machine to machine. In the same sense another definition states that the easiest way to describe aWeb service is to say that it is done on the Internet, using Web protocols, and it does not involve a live user operating a Web browser [39].

The World Wide Web consortium furthermore highlights the importance of XML by defining a Web service as a software application identified by a URI [40], whose interfaces and bindings are capable of being defined, described, and discovered as XML artifacts. Moreover, a Web service supports direct interactions with other software agents using XML based messages exchanged via Internet protocols [41].

Even though there exists no uniform, consistent, standardized and official terminology for Web services, it can be stated that a common understanding about fundamental Web service characteristics is shared among the various actors. In the following the fundamental characteristics that are featured by Web services are listed and briefly described [42]:

- Programmable - Web services are accessible by programmable interfaces. Web services are used for application communication and not for human information processing. Web services do not have a user interface.
- Self-descriptive - Web services include meta-data which can be processed during runtime, e.g. name, description, version, quality of service etc.
- Encapsulated - Web services encapsulate independent and discrete functionalities that perform a particular task.
- Loosely coupled - Web services communicate over messages, implementation details are hidden to Web service providers and Web service consumers.
- Location transparent - Web services are location independent and can be accessed from anywhere at any time only dependent on access rights of applications that consume the Web services.
- Protocol transparent - Web services are based on the Internet protocol stack. Operations and messages can support multiple, such as Hypertext Transfer Protocol (HTTP) or Simple Mail Transfer Protocol (SMTP)
- Reusable and composable - Web services can be divided into further finer grained Web services or multiple reusable basic Web services can be composed to a new Web service.

The here presented characteristics are not unique to Web services but rather reflect principles that have been adopted from previous middleware approaches. Therefore, in the following the factors and conditions that have shaped the development of Web services as well as fundamental Web service concepts are presented and discussed.

Evolution of Integration Middleware

In a dynamically changing and more and more global economy companies and organizations are continuously seeking for new means to cope with competitive pressure. The need to shorten production and development cycles, to reduce costs and time-to-market, to increase customer satisfaction, and to rapidly adapt to market changes has historically led companies to collaborate and to distribute their business processes.

In order to automate business processes spanning multiple administrative and organizational domains the existing stand-alone applications had to be opened and interoperability mechanisms had to be established. Distributed object-oriented technologies and middleware platforms, such as the Distributed Component Object Model (DCOM), Java 2 Platform Enterprise Edition (J2EE) or the Common Object Request Broker Architecture (CORBA), are powerful means for the integration of applications within companies or organizations.

However, as argued already briefly in section 2.4 about SOA, for integrating systems across organizational domains these technologies are only suitable up to a limited extent. This is due to the highly heterogeneous environments in which prescription or shared agreement of common object models and corresponding programming languages is not appropriate and feasible. Even the communication between organizations that are using compatible middleware technologies is not necessarily practicable since the underlying data transport may be blocked by security facilities such as firewalls. Moreover, not just the transport of data but also its shared interpretation has to be taken into account.

Taking into account the conceptual similarity to component-based approaches, which become obvious by comparing the main characteristics of Web services, it can be stated that the basic idea behind Web Services is not new. However, reflecting the analysis above it becomes comprehensible that with the emergence of XML as the dominant standard exchange format as well Web services based on XML message exchange formats and XML based interface descriptions have taken the lead role in building applications from reusable building blocks.

Web Service Scenario

The following figure illustrates the idea and a communication scenario of Web services across organizational domains:

illustration not visible in this excerpt

Figure 3-1 Cross-Organizational Communication using HTTP and XML [37]

The success of the World Wide Web (WWW) as the ubiquitous infrastructure for information exchange has brought the idea of using the WWW also as a medium for communication between applications based on standard Web protocols, such as the Hypertext Transfer Protocol (HTTP) or the Simple Mail Transfer Protocol (SMTP). As most organizations are using a Web or mail server the data transport can be handled on existing infrastructure. Moreover, in many cases this is the only communication channel which is permitted by security policies such as firewall configurations. On top of these transport protocols messages are defined in terms of the Extensible Mark-up Language (XML). In order to be able to process the message content, application A and application В share common message schemas that are e.g. based on the XML Schema Definition Language (XSD). Based on XSD the definition of customized mark­up language for a specific business context is possible providing a representation of structured data in a human- and as well machine-readable manner. The transformation of XML messages to specific programming languages and object instantiations and vice versa has to be performed by the processing applications corresponding to their underlying platform.

Web Service Interaction Model

However, Web services are not monolithic and have to be regarded in context of a distributed architecture. Based on the general service interaction model presented in Section 2.4 further refinements with regard to the concrete Web service technology can be made. The following roles for the interaction of Web services can be identified [42], whereas the concrete XML standards used in the role descriptions are further described in the following Section 3.2.2:

- User: The user consumes the Web services based on service descriptions defined in the Web Service Description Language (WSDL).
- Provider: The provider provides services and ensures that the services are accessible over programmatic interfaces described in declarative Web service descriptions (WSDL).
- Registry: The registry contains declarative Web service descriptions of various Web service providers and their access points. It provides registry services based on standards such as UDDI or ebXML.

It is important to note, that the roles user and provider are exchangeable. A user can act as a retailer combining several Web services according to a business process using the Business process Execution Language (BPEL), which then is provided as an upper level Web service in the provider role. The following figure illustrates the Web service interaction model:


[1] derived from terminus, lat.: terminus = border, border stone, identifier, denotation

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Semantic Mediation between Loosely Coupled Information Models in Service-Oriented Architectures
Technical University of Berlin  (Fakultät IV – Elektrotechnik und Informatik)
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Interoperability, Semantic Mediation, Semantic Interoperability, Service-Oriented Architecture
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Nils Barnickel (Author), 2011, Semantic Mediation between Loosely Coupled Information Models in Service-Oriented Architectures, Munich, GRIN Verlag,


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