Research On Linked Course Data Organization And Knowledge Managment

With the development of information technology and network technology, the global digital information dramatic increase in speed of1018bytes per year, massive learning resource, lacking semantic association, displaying heterogeneous and different normalization characteristic which restricted and the network learning resources management and knowledge sharing seriously. Most of knowledge information on the Internet are stored by learning resource document, its size and structure brought a lot of challenges in knowledge processing, integrating and management.In2006, Tim Berners-Lee proposed the concept of Linked Data. This concept gives us a new method to solve the problems mentioned above. Linked Data application technology on Knowledge Data releasing is the most important step of Web of Date; Ontology is a key technology for knowledge representation, knowledge reasoning, knowledge sharing and knowledge reusing on Semantic Web. Using the Resource Description Framework and description released by the World Wide Web Consortium (W3C) Resource Description Framework (RDF; RDF Scheme RDFS) and Web Ontology Language (OWL), the formal definition of the relationship between the concept and the concept of document, it global and machine readability enhanced semantic retrieval and human-computer synergy. The unstructured learning resources can be transformed into knowledge management. The most important role of the Linked Data is data integration and empowerment of semantics. At the same time, a lot of applications show that Linked Data in E-Learning System can provide a new semantic knowledge services. According analysis above, the paper argues that the data of Linked Course’s construction, organization and knowledge management are the main researching tendency on e-Learning in the future.This paper concerns the two main parts:(1)data of Linked Courses organization;(2)data of Linked Courses knowledge management. In the first part of the data of Linked Courses organization stage, learning resources automatic or semi-automatic have to be conversed to RDF data, and then the RDF data of knowledge extracted and processed in order to create link data between different knowledge data set which are in the LOD to build into related courses data, and then according to their OWL ontology language description to achieve the data linking. In the second part of the knowledge management stage, this paper discussed semantic data storage, indexing and coreference between the different data sets.This paper research on data transforming, linked course data construction, knowledge ontology construction, indexing&storage of linked data, data integration.(1) This paper innovate four-step data transforming method to transform the spreadsheet into RDF data. First step, linked with the column of table head with the class of LOD dataset; second step, linked the value of the cell to the instances of these classes; third step, find out the semantic relationships between columns in the table; in the end, output linked semantic annotation.(2) This paper proposed a Linked Courses data construction method and realized computer hardware courses RDF datasets based on computer interface and computer principle. Large-related data sets, such as LOD DBpedia etc. had been linked to those data by owl:sameA linking. After the construction of Linked Courses data, we introduced the idea of ontology into it by using facilitate knowledge-related and navigation predicate and adding subsequent cognitive order relationship of knowledge points. It can provide a better services platform for the application of the knowledge.(3) This paper proposed a storage system that uses five indexes, namely, Subject, Predicate, Object, Value and Class, on top of any column oriented DB. The main techniques used by the proposed scheme are horizontal partitioning of the logical indices and special indices for values and classes. This approach has the advantage of delivering better performance if the underlying column store technology improves. The proposed approach is conceptually much simpler than the state-of-the-art native-storage based proposals and roughly gives the same performance. The proposal extends an existing approach, SW-Store, that uses column oriented DBs and vertical partitioning and obtains a two/three fold performance improvement. (4) With respect to consolidation, we investigate (1) a baseline approach, which uses explicit owl:sameAs relations to perform consolidation;(2) extended entity consolidation which additionally uses a subset of OWL2RL/RDF rules to derive novel owl:same As relations through the semantics of inverse-functional properties, functional-properties and (max-)cardinality restrictions with value one.Finally, a large number of experiments based on the industry’s authoritative data set proved the effectiveness of the proposed algorithm research; prototype system developed and experiments result proved the effectiveness of the proposed architecture. All the results conduct the four key technologies application in this paper are innovative, feasible and effective on course data organization and knowledge management.