LabelFlow: Exploiting Workflow Provenance to Surface Scientific Data Provenance

被引：5

作者：

Alper, Pinar ^{[1
]}

Belhajjame, Khalid ^{[2
]}

Goble, Carole A. ^{[1
]}

Karagoz, Pinar ^{[3
]}

机构：

[1] Univ Manchester, Sch Comp Sci, Manchester, Lancs, England

[2] Univ Paris 09, Paris, France

[3] Middle E Tech Univ, Dept Comp Engn, TR-06531 Ankara, Turkey

来源：

PROVENANCE AND ANNOTATION OF DATA AND PROCESSES (IPAW 2014) | 2015年 / 8628卷

基金：

英国工程与自然科学研究理事会;

关键词：

Provenance; Annotation; Scientific workflows; SEMANTIC PROVENANCE; WEB;

D O I：

10.1007/978-3-319-16462-5_7

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Provenance traces captured by scientific workflows can be useful for designing, debugging and maintenance. However, our experience suggests that they are of limited use for reporting results, in part because traces do not comprise domain-specific annotations needed for explaining results, and the black-box nature of some workflow activities. We show that by basic mark-up of the data processing within activities and using a set of domain specific label generation functions, standard workflow provenance can be utilised as a platform for the labelling of data artefacts. These labels can in turn aid selection of data subsets and proxy for data descriptors for shared datasets.

引用

页码：84 / 96

页数：13

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