大数据环境下学习资源元模型的研究与应用

The Research and Application of Learning Resources MetaModel in the Big Data Environment

为解决大数据环境下学习资源的描述困难,文章提出了基于元模型的学习资源描述体系,即在资源库平台中建立一套既符合学习资源著录标准的、又具有可扩展性的元数据模型定义模式。通过向通用元模型元素集引用或映射,获取各类资源的元数据模型的元素,以此实现不同元数据模型之间的相互兼容。元模型支持在实际应用中逐渐形成一套约束和推理规范,以实现元模型的自我建设和自我完善。论述了学习资源元模型的基本原理、创建过程、运行流程和存储方法,并对其实际应用的情况做了介绍和分析。

In order to solve the difficulty of resource description in the Big Data environment, the research creates a description system of learning resources based on the MOF＇s MetaModel. That is, creating MetaDataModel which meets learning resources description standard, and can be expanded in the resource pool platform. It obtains the MetaData model elements of all kinds of resource by reference or mapping from the MetaModel in order to realize the compatibility between different MetaDataModels. The MetaModel Form supports to create a set of constraints and inference rules in practical application to realize self construction and self perfection. The paper discusses the Learning Resources MetaModel＇s principle, constructive process, operation process and storage method. It also introduces and analyzes the application situation of the learning resources MetaModel.