Rule based integration of Web Services into semantic data bases

Table of Contents

1. Introduction

1.1 The Task

1.2 Case Studies

1.3 Overview

1.4 Notation

2. Current approaches

2.1 OWL-S

2.2 WSDL-S

2.3 WSDF

2.4. Remarks

2.5 Open questions

3. Semantic model

3.1 General modelling decisions

3.2 The base ontologies

3.3 The instance model

3.4 The example: Service annotations

3.5 The example: Process model document

4. Processing framework

4.1 Implementation rationale

4.2 The Jena framework

4.3 Implementation overview

4.4 Implementation details

4.5 Optimizations

4.6 Runtime behavior

5. Evaluation

5.1 Commerce use case

5.2 T-Info use case

6. Conclusion

6.1 Outlook

Research Objectives and Key Topics

The primary objective of this work is to develop a framework that enables the fully automated, transparent selection, composition, and invocation of Information Providing Services (IPS) within Semantic Web environments. The research addresses the challenge of integrating heterogeneous Web Services into semantic knowledge bases by utilizing rule-based logic and formal semantic annotations to overcome the limitations of purely syntactic service descriptions.

• Automation of Web Service selection and composition for information-centric tasks.
• Development of a semantic annotation approach based on a modified version of OWL-S.
• Integration of Web Services as rule-based extensions within the Jena Semantic Web Framework.
• Evaluation of the approach using commerce and travel-related (T-Info) service case studies.
• Optimization of service invocation runtime behavior within rule-based inference engines.

Excerpt from the Book

Summary of Chapters

1. Introduction: Defines the core challenges of software projects regarding resource definition and outlines the vision for automating service integration within Service Oriented Architectures.

2. Current approaches: Reviews existing frameworks such as OWL-S, WSDL-S, and WSDF, analyzing their strengths and limitations for information-providing services.

3. Semantic model: Details the ontological foundations required for modeling the universe of discourse and introduces the instance model for parameter relation description.

4. Processing framework: Describes the technical realization of the framework as a Jena-based add-on, translating service annotations into executable horn rules.

5. Evaluation: Tests the framework through two practical scenarios, verifying the logic of automated composition and the usability of generated service rules.

6. Conclusion: Summarizes the achievements of the research and provides an outlook on potential future extensions for complex service interactions.

Keywords

Semantic Web Services, Information Providing Services (IPS), OWL-S, WSDL, Jena Framework, Service Oriented Architecture (SOA), Ontologies, Semantic Annotation, Rule-based Integration, Web Service Composition, Knowledge Base, Automated Invocation, Service Discovery, Data Interoperability, Inference Engines.

Frequently Asked Questions

What is the core focus of this research?

The work focuses on Information Providing Services (IPS) and how to make their selection, composition, and invocation fully transparent and automated within Semantic Web applications.

What are the primary themes addressed?

The research explores Semantic Web technologies, ontology modeling, service annotation standards (specifically OWL-S), and the integration of Web Services into knowledge base rule engines.

What is the primary goal of the proposed framework?

The goal is to enable a system to autonomously select and invoke services by matching semantic data requirements with available web resources, without requiring hard-coded integration for every service.

Which scientific method is utilized?

The author proposes a modified OWL-S annotation approach combined with an instance model, implemented as a proof-of-concept add-on for the Jena Semantic Web Framework, using horn rules for logic representation.

What is the main topic of the implementation phase?

The main topic is the processing framework that interprets semantic annotations to generate rules. These rules are integrated into a knowledge base, allowing the service invocation to be triggered by standard inference processes.

Which keywords characterize this work?

Key terms include Semantic Web Services, OWL-S, WSDL, Jena Framework, SOA, ontologies, and automated rule-based service invocation.

Why are standard WSDL descriptions considered insufficient for this task?

Purely syntactic WSDL documents lack the semantic meaning of data parameters, making it impossible for automated systems to logically map local data to service inputs without human intervention.

How does the proposed framework handle data validity?

The framework introduces a 'hasValidity' property in the service model to track how long data returned by a service remains reliable, helping to avoid the use of obsolete triples in the knowledge base.