文章基本信息

标题：Revealing the Detailed Lineage of Script Outputs Using Hybrid Provenance
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作者：Qian Zhang ; Yang Cao ; Qiwen Wang 等
期刊名称：International Journal of Digital Curation
印刷版ISSN：1746-8256
出版年度：2017
出版社：University of Edinburgh
摘要：We illustrate how combining retrospective and prospectiveprovenance can yield scientifically meaningful hybrid provenance representations of the computational histories of data produced during a script run. We use scripts from multiple disciplines (astrophysics, climate science, biodiversity data curation, and social network analysis), implemented in Python, R, and MATLAB, to highlight the usefulness of diverse forms of retrospective provenance when coupled with prospective provenance. Users provide prospective provenance, i.e., the conceptual workflows latent in scripts, via simple YesWorkflow annotations, embedded as script comments. Runtime observables can be linked to prospective provenance via relational views and queries. These observables could be found hidden in filenames or folder structures, be recorded in log files, or they can be automatically captured using tools such as noWorkflow or the DataONE RunManagers. The YesWorkflow toolkit, example scripts, and demonstration code are available via an open source repository.