科学数据来源的时态表示

Peng Chen, Beth Plale, M. Aktaş
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引用次数: 29

摘要

数字科学数据的来源是数据对象元数据的重要组成部分。但是,由于捕获的粒度级别可能很高,因此它可以快速增长。它也可以是相当丰富的功能。提出了一种基于逻辑时间的来源数据表示方法,减少了特征空间。我们创建了来源的时域和频域表示,并对抽象表示应用聚类、分类和关联规则挖掘来确定时间表示的有用性。我们使用从一系列科学工作流程中捕获的现有的10gb来源数据库来评估时间表示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temporal representation for scientific data provenance
Provenance of digital scientific data is an important piece of the metadata of a data object. It can however grow voluminous quickly because the granularity level of capture can be high. It can also be quite feature rich. We propose a representation of the provenance data based on logical time that reduces the feature space. Creating time and frequency domain representations of the provenance, we apply clustering, classification and association rule mining to the abstract representations to determine the usefulness of the temporal representation. We evaluate the temporal representation using an existing 10 GB database of provenance captured from a range of scientific workflows.
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