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Framework of Knowledge Management in Education Based on Knowledge Grid Xia Hongwen (College of Teachers’ Education,Zhejiang Normal University,Jinhua Zhejiang, 321004, China.) firstname.lastname@example.org Abstract—Knowledge Grid is a kind of knowledge sharing sustainable Internet application environment that enables environment based on the World Wide Web, and its essence is people or virtual roles (mechanisms that facilitate the synergy and sharing of internet knowledge resource and interoperation among users, applications, and resources) to knowledge service. KM (Knowledge Management) in effectively capture, publish, share and manage explicit Education based on KG (Knowledge Grid) makes use of the knowledge resources. It also provides on-demand services to grid technology and integrates the methods and tools of KM in support innovation, cooperative teamwork, problem-solving Education to support the whole cycle of Knowledge and decision making. It incorporates epistemology and Application. Based on the advantages of KM in Education, in ontology to reflect human cognition characteristics; exploits this paper, we construct a service-oriented model of KM in social, ecological and economic principles; and adopts the Education in order to achieve more effective knowledge sharing and knowledge service in education. techniques and standards developed during work toward the next-generation web.”  Keywords-Knowledge Grid; Knowledge Management in In addition, he figured out “the Knowledge Grid Education; Knowledge Service Environment consists of autonomous individuals, self- organized semantic communities, an adaptive networking mechanism, an evolving semantic overlay keeping I. INTRODUCTION meaningful connection between individuals, flows for The emergence of the Web provided an unprecedented dynamic resource sharing, and mechanisms supporting AI research and application platform. By providing access to effective resource management and providing appropriate human-readable content stored in any computer connected to knowledge services for problem-solving and innovation. It the Internet, it revolutionized business, scientific research, supports innovation and harmonious development of science, government, and public information services around the technology and culture”.  globe. How to uniformly, normatively and effectively A knowledge grid should synthesize the integration of the manage variety of resources, provide the machine- data, computing, and the network hardware, the development understandable semantic information and intelligent web of the software, and the coordination of a large and services for users will be the key issues of the next- distributed human infrastructure. KG is a kind of grid, which generation web. Knowledge Grid is the organic integration focus on knowledge management during computing. From and inevitable trend of the Grid, the Semantic Web and the viewpoints of Fran Berman and Hai Zhuge, we can Semantic Grid and it is a kind of knowledge-sharing summarize that Knowledge Grid is a knowledge carrier and environment based on the World Wide Web. Knowledge well controlled knowledge collections, and it defines the Grid achieves information processing and knowledge operation mode of Knowledge Management. Therefore, acquisition by the technology of Semantic Web; uses the using the technology of Knowledge Grid to implement layered architecture to build a resource and information education knowledge management and service has its sharing platform providing a higher level of integration and theoretical basis, technical support and practical significance. shared services; and its essence is the collaboration and sharing of the knowledge resources and knowledge service III. THE INTENSION OF KNOWLEDGE in WWW. MANAGEMENT IN EDUCATION BASED ON KNOWLEDGE GRID II. WHAT IS KNOWLEDGE GRID(KG) According to Fran Berman on the definition of The expert Fran Berman firstly put the concept of Knowledge Grid, Knowledge Management in Education Knowledge Grid forward that a Knowledge Grid (KG) is the based on Knowledge Grid should include two aspects: the convergence of a comprehensive computational education knowledge discovery and education knowledge infrastructure along with the scientific data collections and services. The education knowledge discovery is the applications for routinely supporting the synthesis of application in the field of education of knowledge discovery knowledge from that data.  The professor Hai Zhuge technology, which adopts a parallel distributed model of believed that “the Knowledge Grid is an intelligent and knowledge discovery. This model integrates algorithms, tools, and software of data-mining located in different category, knowledge-level, and location. The former two places; conceptualizes them by ontology, then organizes dimensions identify knowledge content, and the third these elements by metadata for forming a highly integrated dimension identifies the locations that store knowledge. Each system of knowledge discovery in education; and develops point in the space represents knowledge at a certain the service architecture of knowledge discovery in education. knowledge level of a knowledge category and is stored at a The education knowledge service is used to support certain location.  Some professional knowledge can be knowledge sharing in the field of education based on the easily and accurately labeled by the three-dimensional function of traditional knowledge service, and it is a kind of knowledge space which makes the personalized and service and technology applied to knowledge management. It specialized knowledge service become possible. The makes full use of the semantic and ontology of knowledge, Knowledge Grid Environment enables users to effectively and analyzes the semantic of knowledge to build the access, publish, share and manage knowledge resources; semantic knowledge services, semantic data integration, analyzes the user’s needs and preferences in specified and resource agent, workflow package in order to achieve detailed for creating the user's personal files based on sufficient and efficiency use for education knowledge. The ontology; uses semantic description norms of metadata to education knowledge service is mainly used to solve six accurately grasp the user's personality and needs; and timely challenges in knowledge life cycle: the acquisition, modeling, adjusts the contents to provide personalized knowledge retrieval, reuse, publishing and management for education service for users. knowledge. Integrating these six aspects will build a flexible, scalable and easy to reused framework of education services D. Intelligent learning and automated processing Ontology-based education knowledge can be identified IV. ADVANTAGES OF KM IN EDCATION BASED ON KG by the computer, and illustrate the semantic relationship of KM (Knowledge Management) in Education based on knowledge ontology to make intelligent learning possible. KG (Knowledge Grid) makes use of the grid technology and Knowledge Management in education based on KG is built integrates the methods and tools of KM in Education to on the basis of the Agent, and all the services are computer- support the whole cycle of Knowledge Application. The based automatic processing, which are not required the advantages are remarked as follows: participation of people. The powerful computing ability of Gird enables the computer automatically processing massive A. Parallel discovery of knowledge in education ontology-based educational information possible. Knowledge Grid adopts next-generation technologies and standards of Internet, and uses parallel distributed technology V. FRAMEWORK OF KNOWLEDGE MANAGEMENT IN to process and analyze distributed in geography, massive, EDUCATION BASED ON KNOWLEDGE GRID heterogeneous data, and found the knowledge which matches Based on the OGSA (Open Grid Services Architecture), the query conditions and meet customer needs from a wealth the service-oriented knowledge management in education of information in the collection, and achieves knowledge system (Fig. 1) is mainly used for the management and discovery in parallel. services of distributed education knowledge that is the most prominent feature of this architecture. The knowledge B. Intelligent aggregation and integration of knowledge in services of this architecture carries out in a more coordinated education mode, and the result of one task serves for another task in Knowledge storage in network is static and dynamic, and particular form. any search engine technology (such as Google, etc.) can not Yu He and Weidong Zhu believed that the process of reflect the changes of information on the Internet in real knowledge management in education includes four parts: time. Knowledge grid can intelligently and dynamically the creation, storage, sharing and application of education aggregate the knowledge distributed in all over the world knowledge.  through a single semantic entrance, thereby solve the above The model is a three-layer architecture consisting of the problems very well. In addition, in the environment of grid resource entity layer, the knowledge grid middle layer and knowledge management, you can remove the barriers among the knowledge grid application layer. According to the different web sites, integration of resources. Built on the process of knowledge management in education, we divide OGSA (Open Grid Services Architecture), Grid Knowledge this process into seven parts: knowledge acquisition; provides guarantees for the integration of knowledge. knowledge modeling; representation and storage of knowledge; resource management services; knowledge C. Personalized and specialized knowledge service portal; gird knowledge services; knowledge application. In the grid environment, the organization of knowledge is represented by three-dimensional coordinates: knowledge- KG Application Knowledge Intelligent Self-regulated … Course Knowledge Layer Presentation Search learning learning application Reasoning Visual Serving services Grid knowledge Knowledge services portal Evaluation Knowledge service Delivery Service Knowledge portal KG Middle Layer Knowledge Resource Resource Workflow Resources conversion coordination distribution service management service service service services Knowledge Ontology Representation and Repository storage of knowledge Knowledge Ontology model Knowledge modeling Resource Entity Resources Knowledge Knowledge in Knowledge Knowledge Layer on the Internet in mind communication in practice acquisition Figure 1. Framework of Knowledge Management in Education Based on Knowledge Grid degree, and lay the foundation for realizing the personalized A. Knowledge acquisition knowledge push services. KA (Knowledge Acquisition) is located in the front-end of the architecture, which is the starting point of the life B. Knowledge modeling cycle of knowledge management in education, and also is the Knowledge Modeling (KM) is intended to provide the foundation of providing knowledge services. The useful description for the elements and the structure of domain information and knowledge models are extracted from knowledge, and the primary function of KM is used to knowledge sources by the technology of knowledge represent the knowledge and solve practical problems. acquisition. The knowledge sources mainly refer to the Knowledge modeling reduces the distance between the distributional education resources on the Internet, the knowledge acquisition and the knowledge application, and knowledge in mind of learners’ (explicating the tacit retains the most useful knowledge and reasoning on the knowledge), the knowledge in the process of knowledge. communication, and the knowledge in practice. In the The knowledge consisting of domain ontology is made process of knowledge acquisition based on Knowledge Grid up of knowledge components and their relationships. services, the natural language needs to be tagged and Knowledge components can be divided into principles, described in semantic, and then ontology rules of domain concepts, rules, processes and examples. The relationship knowledge are structured. between knowledge components can be divided into Part of, In this framework, we use Dublin Core-based metadata Kind of, Instance of, Attribute of and so on.  standards to describe the characteristics of resources which Ontology-based knowledge modeling methods can mainly contain the common properties of resources, provide the common understanding on semantic for the education properties, technical attributes, as well as the knowledge in the field of education, identify the concepts evaluating information of resources. The metadata standards and vocabularies approved in education, and then elicit the are used to describe the characteristics of resources, which definitions of these concepts and vocabularies and a clear can solve the problem of interoperability and reuse, help the relationship between them from different levels. Using computer understand the contents of resources in some semantic metadata to model ontology for the knowledge in education can achieve the knowledge in education efficiently and automatically processed and support the creation, Knowledge conversion service: Knowledge conversion integration, classification and retrieval on semantic-level. service is mainly in charge of the semantic description Establishing rules of ontology in the field of education will of resources; these resources include the host location, lay the foundation for ontology services, effectively support data source, tools, the algorithm needed to extract, the the sharing and reuse of education knowledge in the network workflow of distribution knowledge, and the process environment, and improve the generality of the knowledge. and result of excavation. C. Representation and storage of knowledge Resource coordination service: Resource coordination service supervises the use of the resources and responses KR (Knowledge Representation) constructs the the request for the workflow implementing services. If knowledge on structure and semantic by way of the there are conflicts or unbalanced loads in resource computer understanding. Commonly used methods of utilization, it will allocate the relation of mapping. knowledge representation are showed as follows: first-order Resource distribution service: The ontology-based predicate logic representation, frame representation, matching algorithm can achieve adaptive distribution of semantic network representation, procedural representation, resources. According to the workflow represented by the and object-oriented representation. The choice of knowledge abstract semantic as well as the unified analysis of representation modes depends on the characteristics of resources available, the matching algorithm determines applications field, the requirements for dealing with the a constraint condition of using resources and makes a knowledge and the way of user interaction. Under the grid scheme of Resource distribution. environment, the mechanism of knowledge services also Workflow service: Workflow service will implement needs to solve the problem that how to release and retrieve the mapping between application services and resources, the knowledge. and send resource acquisition for each data mining In this framework, we use XML/Schema to represent the process. knowledge in semantic acquired from the KA (Knowledge Acquisition) stage. The greatest strengths of XML lies in E. Knowledge portal separating the data display format and the content using the Knowledge Portal is a key module of this service system, self-describing method, and creating markup languages in and it provides a view for education knowledge. Users can some specific area, thus effectively expresses the data retrieve and exchange the education knowledge they need by structure and semantic of unstructured or semi-structured Knowledge Portal. documents. XML Schema provides richer data types and a As the portal of education knowledge service system, set of commitment mechanisms to enhance the capacity for Knowledge Portal should possess four basic functions: knowledge description. Knowledge positioning: it refers the registration and On the basis of unified semantic descriptions of management in education knowledge service knowledge, we use RDF/RDF Schema for modeling components distributing in the knowledge base and knowledge. RDF is a kind of standardized specification on stored in multiple formats. semantic description of metadata, which adopts basic data Knowledge pushing and knowledge maintenance: This model composed of Resource, Property and Statement three involves using which method to show the education objects to establish a framework for the definition and use of knowledge to the use through Knowledge Portal as well meta-data. Thus the metadata can be effectively translated as maintaining knowledge by way of user-friendly. into machine-understandable information. As a supplement Security guard: This is the underlying structure used for to RDF, RDF Schema defines a number of classes and authentication and authorization in order to present, use properties used for describing other classes and properties, and update the knowledge in a safe manner. which builds up the capacity in resources description of Providing the registration and discovery mechanism for RDF. Being represented in semantic and modeled, the education knowledge services. knowledge is submitted to the Knowledge Base, and learners can access and operate the Knowledge Base through the F. Gird knowledge services human-computer interface. Consumers of knowledge are most concerned about the D. Resource management services means of knowledge access and use of knowledge. Under the KG environment, sharing knowledge among the Knowledge Resource management services make use of ontology Grid virtual organizations should fully consider the technique to uniformly define the education knowledge in characteristics of KM environment to build knowledge semantic, and realize the unified organization, management models and service models. Knowledge implementation and coordination for the distributed services offered in this system contains: visualization knowledge and data in order to effectively manage the service, reasoning service, personalized push service, and semantics, data elements, data mining tools and visualization evaluation service. tools. Metadata and Ontology are often considered as the basic tools of knowledge sharing and communication Visualization Service. Based on the association rule, between distributed users and applications. cluster model or class, the system builds a knowledge The main resource management services this system model, and then uses charts, images or other visual supported are related as follows: elements to display the non-spatial knowledge expressed services in the knowledge model. Doing that can help people to Knowledge management in education can help understand the relationships between all kinds of organizations to broaden the domain of knowledge knowledge and trends of development, and deepen the application and upgrade the quality of knowledge. In some understanding on knowledge. extent, it is a process of improvement in quality. Grid-based Reasoning service. It provides users with personalized knowledge management in education ultimately makes the knowledge reasoning services on the base of the fourth intelligent learning realized, and enhances the quality of stage of "resource management service". The system education and teaching by techniques of distributed founds and excavates the knowledge matching with knowledge discovery, intelligent aggregation of knowledge, user’s request by way of identifying, selecting, and personalized service of knowledge. downloading data mining tools, algorithms and rules, and then responses to user’s demand through knowledge VI. CONCLUSIONS positioning and knowledge pushing. Knowledge management in education is a comprehensive Personalized push service. Based on personality approach provided for exploring, excavating, managing and characteristics of users’, the push service for education analyzing education resources, and its aim is improving the knowledge provides personalized and proactive shabbily, interoperability, maintainability and reusability of information services. That is to say based on user’s knowledge to meet the learning needs of learners and personalized needs (including categories, subjects, improve the quality of teaching. Grid -based and service- keywords and the combinational conditions, etc.) and oriented knowledge management in education can realizes the different rules for push, the system sends different the smart aggregation to the education knowledge distributed messages for different users. In this framework, we use in all over the world and better management of knowledge, agent technology to push personalized knowledge for provide knowledge services for learners by a single semantic users based on the search conditions users setting. The entrance, and in the end make knowledge-sharing in agent will automatically search the knowledge meeting education and knowledge innovation a reality. In this paper, the requirements of users’, and regularly or irregularly the framework of knowledge management in education transmit the education knowledge on the Internet to based on KG is of some value to the management the users’ computer by way of Push or Web-casting declarative knowledge, procedural knowledge and tacit providing scheduled track services in order to achieve knowledge. the automatic and intelligent push for education knowledge. REFERENCES Evaluation service. 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