Details of a semantic annotation are outlined, both for the semantic model consisting of concepts to model the area of discourse as well as the individual model for a single service. The annotation is used to build a concrete implementation of a generic processing framework translating the annotation of a service into rules to be integrated into an OWL knowledge base rule engine.
The realization is done for the Jena Semantic Web Framework, an open source library for Semantic Web application for the Java language. The realization is designed as an add-on to Jena which integrates service calls in such a way that service invocation is transparent to applications building on Jena.
A discussion on optimizations, both implemented ones and realizable but not implemented ones is included. They can serve as starting points for moving the implementation from a proof of concept status to real world usability. The section finishes with some considerations on general run-time behavior.
Finally the presented framework is evaluated in more detail: Firstly, a sophisticated scenario for the running example is described and shown, how automated service selection, composition and invocation is actually realized during run-time. Then the approach is evaluated with regard to services with more complex parameterizations with particular focus on the data supplied to the services and the rules generated from such complex parameterized services and whether such rules are still usable.
The prime design rationale of the presented framework implementation is as a proof of concept for the approach of generically integrating Web Services as rules with Semantic knowledge bases. Therefore there is still a long way to go for a real world application to be build on the framework. At several points notes are added hinting on potential challenges, particularly with regard to specific techniques for optimizing reasoning on knowledge bases. Neither are these remarks to be seen as exhaustive nor are they to be understood as short treatments. Rather they are intended as selected starting points for further research.
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
1.1 The Task
Solutions for task two, that is to automate selection and composition of services, is the vision of Semantic Web Services: Not only should some given service be accessed in a standardized way. But it should be possible for a system, given some specific task, to automatically select an appropriate service. Moreover, if necessary, a system should be able to combine services to fulfill some task which can not be achieved by a single service.
Clearly, for automatic service selection and composition, purely technical descriptions of services as contained in WSDL documents do not suffice: E.g., knowing from a service that it requires two strings and one integer parameter as input and returns an integer as output is not of much help if the system needs to find some person's telephone number – the system should not have to parse free text or names for assigning correctly the first string parameter to the given name, the second to the family name and the integer to the postal code of the person's home town, while the return parameter corresponds to the person's telephone number: although such parsing could be done by current natural language processing systems, this would be a very error prone process depending heavily on the service provider to use unambiguous names – often an impossible task due to ambiguousness of natural language. In general, the system can neither find out that this service is the one it needs to invoke, nor can it associate the right data from its data base with the service parameters.
Thus, to allow automation of Web Service selection and composition, an additional layer of semantic information has to be added on top of the technical information provided by the WSDL document: The WSDL document adds meta-data to the service on the types of connection and operations, of which messages an operation consists, of which parameters a message is build up and the data types of these parameters. This information describes the syntax for communicating with a service. On top of this information we now need meta-data describing the meaning of the messages' contents, both how the service interprets the data to be send and how to interpret the service's answer. Once a framework for processing this semantic information is available, it can use the existing technology for the technical details of service invocation described above.
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.
- Citar trabajo
- Dr. Jochen Gruber (Autor), 2006, Rule based integration of Web Services into semantic data bases, Múnich, GRIN Verlag, https://www.grin.com/document/63296
