Learning object metadata interchange mechanism : a thesis presented in partial fulfillment of the requirements for the degree of Master of Information Science at Massey University, Palmerston North, New Zealand

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dc.contributor.authorZhang, Yuejun
dc.date.accessioned2018-02-15T00:54:19Z
dc.date.available2018-02-15T00:54:19Z
dc.date.issued2005
dc.description.abstractIn spite of the current lack of conceptual clarity in the multiple definitions and uses, the term learning objects is still frequently used in content creation and aggregation in the online-learning field. In the mean time, considerable efforts have been initiated in the past few years for the standardization of metadata elements for consistent description of learning objects, so that learning objects can be identified, searched and retrieved effectively and efficiently across multiple contexts. However, there are currently a large number of standardization bodies and an even much larger number of ongoing standard initiatives in the learning field, and different learning objects repositories are likely to apply different metadata schemas to meet the specific needs of their intended communities. An interchange mechanism for the conversion between various metadata schemas, therefore, becomes necessary for intensive interoperability. In this thesis, we first make a brief introduction to the concept learning objects, then the term metadata, followed by a description of the functional requirements of learning objects. the purposes of metadata, and the importance of metadata for learning objects. After that, this thesis investigates metadata schemas in various fields in general, focused on several mainstream metadata specifications developed for learning objects in particular. The differences among these metadata schemas for learning objects are analyzed and a mapping between their elements is identified. On the basis of literature review, a framework for interchange of metadata schemas is proposed and a prototype to demonstrate the functionalities of the framework is developed. For the high scalability and the high accuracy of the developed system, a so-called LOM-intermediated approach is suggested, and a so-called dynamic-database methodology is adopted. The LOM- intermediated approach significantly simplifies the metadata mapping issues by undertaking the schema-schema mapping in a way of schema-LOM-schema mapping, while the dynamic-database methodology effectively prevents any data-loss resulting as a by-product from the use of LOM-intermediated approach. The prototype currently generates and outputs XML metadata in IMS, EdNA, Dublin Core and LOM. It is a web- based three-tier architecture, using Java technologies for implementation, MySQL as the database server and JDBC for database access.en_US
dc.identifier.urihttp://hdl.handle.net/10179/12767
dc.language.isoenen_US
dc.publisherMassey Universityen_US
dc.rightsThe Authoren_US
dc.subjectMetadataen_US
dc.subjectDatabase managementen_US
dc.subjectInformation storage and retrieval systemsen_US
dc.subjectData miningen_US
dc.titleLearning object metadata interchange mechanism : a thesis presented in partial fulfillment of the requirements for the degree of Master of Information Science at Massey University, Palmerston North, New Zealanden_US
dc.typeThesisen_US
massey.contributor.authorZhang, Yuejun
thesis.degree.disciplineInformation Systemsen_US
thesis.degree.grantorMassey Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Information Science (M. Inf. Sc.)en_US
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