454 W. Tan et al. The emphasis of the module implementation is the UDDI Specification [18]. The service discovery module queries the UDDI access points (also called UDDI SRC, provided by such as Microsoft, IBM, etc.) to get the documents based on ontology, through which DEA requests the relevant services. The module enquiries the UDDI SRC through the communication by SOAP, and receives also the SOAP message XML-Based. The principle of UDDI is shown in Fig. 6. Fig. 7 shows the effective classes of the Learning Activation by Rational Rose from the design of timing plan diagram. Meanwhile the relationship of those classes is shown clearly in the figure. The EISP will access this Web service ontology docu- ment by the analysis of the URL, and then sent a require message based on the SOAP format to the server to get the resource. 5.2 Communications Module Based on SOAP and ONTOLOGY This module automatically analyses the ontology document that comes from the ser- vice discovery module, gets the service provider information, and then automatically generates client agent. Users communicate with the service provider using the client agent. The advantages of the model are: expansibility and flexibility [18, 19]. Those various services located in different servers can be integrated in a unified client agent. Especially, for those which need to use several different systems in the services work together to complete the task, the module can be very conformable to resolve the problem. Meanwhile, an information encryption and decryption module is embedded into the communications module to enhance communications security. In the Fig. 8, the server initiates the encryption expansion to encrypt the SOAP message sent by. And the circumstances of activating client decryption expansion, SOAP messages received are effective. Effective Information Fig. 8. Client receiving SOAP response message 6 Conclusions and Ongoing Work The paper based on E-learning information technology standards as a solution to the interoperability information model, built an interactive communications architecture for the sharing of enterprises data resources, and designed the data interactive mecha- nism of the communications model. The model adopts a flexible approach to better meet the requirements of the loosely coupling between information model and the An E-Learning System Engineering Ontology Model on the Semantic Web 455 communications model. Based on UDDI, ontology, and SOAP protocols, we design and achieve the modules, and built an interoperable communication model mainstay of the heterogeneous information systems. According to the communication model design, the method effectively addresses the interoperability issues among heteroge- neous information systems. Meanwhile, the core part of the model was applied into a system to test, and got satisfied results. However, in complex systems integration applications, the capacity and speed of the model remain not to be done further study. We intend to develop new and more complex case studies in order to better evaluate the usability and usefulness of our communications model. Acknowledgment This paper was supported by the Zhejiang provincial Natural Science Foundation of China (Grant No. Y106039), the Key Research Foundation of Zhejiang Education Department of China (Grant No. 20060491), and the Innovation Foundation of Zheji- ang Normal University Graduate School. References 1. JYGLBZ-XX-2002, Enterprise Management Information Standards, the Ministry of the People’s Republic of Enterprises (2002) 2. Web Services Architecture[S]. W3C Working Group (2004) 3. Seely, SOAP: Cross-Platform Development Technology Web Services. Machinery Indus- try Press, Beijing (2002) 4. SOAP Implementation Directory [EB/OL] (2004), http://www.soapware.org/directory/4/implemen-tations 5. Coyle, F.P.: XML, Web Services, and the Data Revolution. Tsinghua University Press, Beijng (2003) 6. Banerjee, A., Corera, A., et al.: C# Web Services—Building Web Services With. NET. Tsinghua University Press, Beijng (2002) 7. Liu, X.H.: Net Web Services Development Guide. Electronics Industry Press, Beijing (2002) 8. Scott Short: Building XML Web Services for the Microsoft. NET Platform. Tsinghua University Press, Beijing (2002) 9. Kacsuk, P., Vajda, F.: Network-based Distributed Computing (Meta-computing). ER- CIM[C] (1999) 10. Humphrey, W.S., Kellner, M.: Software process modeling: Principles of entity process models, Soft. Eng. Inst., Carnegie Mellon Univ., Pittsburgh, PA, Tech. Rep. CMU-SEI-89- TR-2 (Feburary 1989) 11. Deephouse, C., Mukhopadhyay, T., Goldenson, D.R., Kellner, M.I.: Software processes and project performance. J. Manage. Inf. Syst. 12(3), 187–205 (1996) 12. Guarino, N.: Formal ontology, conceptual analysis and knowledge representation. Int. J. Human-Comput. Stud. 43(5–6), 625–640 (1995) 13. Chandrasekaran, B., Josephson, J.R., Benjamins, V.R.: What are ontologies, and why do we need them? IEEE Intell. Syst. 14(1), 20–26 (1999) 456 W. Tan et al. 14. Genesereth, M.R., Nilsson, N.J.: Logical Foundations of Artificial Intelligence. Morgan Kaufmann, Palo Alto (1987) 15. Wand, Y., Weber, R.: An ontological model of an information system. IEEE Trans. Soft. Eng. 16(11), 1282–1292 (1990) 16. Parsons, J., Wand, Y.: Using objects in systems analysis. Commun. ACM 40(12), 104–110 (1997) 17. Arkin, S., Askary, S., Fordin, S., et al.: Web Service Choreography Interface (WSCI) 1.0 (2002), http://www.w3.org/TR/wsci/ 18. Sun, K., Chen, D.R.: Based on UDDI and Web Service Application Model. Computer Ap- plication (5), 133–139 (2003) 19. Sun, B., Sun, S.: Web Service Based on the Development of the System of Enterprise Re- sources. Information enterprises of China 10(201), 77–81 (2003) F. Li et al. (Eds.): ICWL 2008, LNCS 5145, pp. 457–467, 2008. © Springer-Verlag Berlin Heidelberg 2008 A Semantic Grid Application for E-Learning Data Sharing Wenya Tian 1,2 and Yuxin Mao 2 1 Information Technology Department, Zhejiang Economic & Trade Polytechnic, Hangzhou 310018, China 2 College of Computer Science, Zhejiang University, Hangzhou 310027, China Twy@zjiet.edu.cn, maoyx@zju.edu.cn Abstract. In an E-learning scenario, educational resources, such as course documents, videos, test-bases, courseware, and teacher information etc., are needed to be shared across different schools. DartGrid is a semantic grid toolkit for data integration using technologies from Semantic Web and Grid. In this paper, a Semantic Grid for E-leaning based on DartGrid is introduced, and it provides a Semantic-based distributed infrastructure for E-learning data re- source sharing. We explore the essential and fundamental roles played by RDF semantics for E-learning. We also introduce a set of semantically enabled tools and grid services for E-learning such as semantic browser, ontology service, semantic query service, and semantic registration service. 1 Introduction The Semantic Web [3] is an effort to improve the current Web by making Web re- sources machine-understandable by enriching current Web resources with machine- understandable semantics [5,6]. It provides a common framework that allows data to be shared and reused across applications, enterprises, and community boundaries. It is based on the Resource Description Framework (RDF), which integrates a variety of applications using XML as syntax and URIs for naming. The Grid [1] tries to connect a wide variety of geographically distributed resources such as Personal Computers, workstations and clusters, storage systems, data sources, databases and special purpose scientific instruments and presents them as an inte- grated resource, and it is a technology that makes it possible for distributed computing resources to be shared, managed, coordinated, and controlled. The Semantic Grid [4] is an Internet-centered interconnection environment that can effectively organize, share, cluster, fuse, and manage globally distributed versatile resources based on the interconnection semantics. In short, the Semantic Grid [7] vision is to achieve a high degree of easy-to-use and seamless automation in an effort to facilitate flexible collaborations and computations on a global scale. It takes advan- tage of machine-understandable knowledge on the Grid. Nowadays, in an E-learning scenario, educational resources, such as course docu- ments, videos, test-bases, courseware, and teacher information etc, are needed to be 458 W. Tian and Y. Mao shared across different colleges and schools. Typically, teachers from different colleges in different districts work together for teaching. As a result of the develop- ment of modern information technology, E-learning is the primary method of building life long people education system in this knowledge economy age. E-learning gives students the freedom to study anywhere at anytime and is widely developed and de- ployed in our country recently. To build an E-learning environment, we often need to integrate E-learning services across distributed, heterogeneous, dynamic “virtual organizations” formed by disparate education resources within a single enterprise and/or external sharing education resource via service provider relationships. This integration can be technically challenging because it requires achieving various quali- ties of E-learning service while dealing with different scholastic platforms DartGrid 1 is a data integration toolkit using technologies from semantic web and grid, and it offers a generic semantic infrastructure for building database grid applica- tions. Roughly speaking, DartGrid is a set of semantically enabled tools and grid services such as semantic browser, semantic mapping tools, ontology service, seman- tic query service, semantic registration service. All that support the development of database grid applications. In this paper, a Semantic Grid for E-leaning based on DartGrid is introduced, and it provides a semantically distributed infrastructure for E-learning scenarios as we men- tioned before. We explore the essential and fundamental roles played by RDF seman- tics for E-learning grids, and implement a set of semantically enabled tools and grid services for E-learning resource sharing such as semantic browser, ontology service, semantic query service, and semantic registration service. This paper is outlined as following: Section 2 introduces the architecture and the core components of a Semantic Grid for E-leaning from a technical perspective. Sec- tion 3 introduces a working scenario for the E-learning grid application. Section 4 mentions some related works. Section 5 gives the summary. 2 Technical Approach and System Architecture 2.1 Technical Approach The system is built upon two basic technologies. Firstly, RDF is employed to define the E-Learning ontology in order to integrate heterogeneous databases. Secondly, the system takes the service-oriented architecture and uses Globus toolkit to develop the core E-learning grid services. 2.1.1 RDF At the present, the most popular languages for data semantics are RDF framework and OWL language. OWL language is proposed in Semantic Web research area and standardize-ed by W3C organization. The Resource Description Framework (RDF) is a language for representing web information in a minimally constraining, extensible, but meaningful way. 1 DartGrid Official Website: http://ccnt.zju.edu.cn/projects/dartgrid . proposed in Semantic Web research area and standardize-ed by W3C organization. The Resource Description Framework (RDF) is a language for representing web information in a minimally constraining,. for E-Learning Data Sharing Wenya Tian 1,2 and Yuxin Mao 2 1 Information Technology Department, Zhejiang Economic & Trade Polytechnic, Hangzhou 310018, China 2 College of Computer Science,. data integration using technologies from Semantic Web and Grid. In this paper, a Semantic Grid for E-leaning based on DartGrid is introduced, and it provides a Semantic-based distributed infrastructure