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注意你的元数据:利用语义的配置,适应,和科学的工作流程中的出处

Mind Your Metadata: Exploiting Semantics for Configuration, Adaptation, and Provenance in Scientific Workflows
课程网址: http://videolectures.net/iswc2011_szekely_workflows/  
主讲教师: Pedro Szekely
开课单位: 南加州大学
开课时间: 2011-11-25
课程语种: 英语
中文简介:
包含科学数据的语义描述的科学元数据捕获起来很昂贵,并且通常不用于整个数据分析过程。我们提出了一种方法,在准备科学数据时生成语义元数据,然后用于配置模型并根据数据对其进行自定义。捕获的元数据包括传感器描述,数据特征,数据类型和流程文档。然后,在工作流系统中使用此元数据动态选择分析模型并自动设置模型参数。此外,数据处理的所有方面都有记录,系统能够基于元数据为新数据产品生成大量的起源记录。结果,系统可以基于其正在处理的数据的元数据属性动态地选择分析模型,从而生成更准确的结果。我们展示了分析流域生态系统管理的流代谢的结果。
课程简介: Scientific metadata containing semantic descriptions of scientific data is expensive to capture and is typically not used across entire data analytic processes. We present an approach where semantic metadata is generated as scientific data is being prepared, and then subsequently used to configure models and to customize them to the data. The metadata captured includes sensor descriptions, data characteristics, data types, and process documentation. This metadata is then used in a workflow system to select analytic models dynamically and to set up model parameters automatically. In addition, all aspects of data processing are documented, and the system is able to generate extensive provenance records for new data products based on the metadata. As a result, the system can dynamically select analytic models based on the metadata properties of the data it is processing, generating more accurate results. We show results in analyzing stream metabolism for watershed ecosystem management.
关 键 词: 语义元数据; 配置模型; 代谢流分析
课程来源: 视频讲座网
最后编审: 2020-06-28:yumf
阅读次数: 53