Making Provenance Work for You

被引:0
|
作者
Lerner, Barbara [1 ]
Boose, Emery [2 ]
Brand, Orenna [3 ]
Ellison, Aaron M. [4 ]
Fong, Elizabeth [1 ]
Lau, Matthew K. [5 ]
Ngo, Khanh [6 ]
Pasquier, Thomas [7 ]
Perez, Luis [8 ]
Seltzer, Margo [7 ]
Sheehan, Rose [6 ]
Wonsil, Joseph [7 ]
机构
[1] Mt Holyoke Coll, Comp Sci Dept, South Hadley, MA 01075 USA
[2] Harvard Univ, Harvard Forest, Petersham, MA 01366 USA
[3] Columbia Univ, New York, NY 10027 USA
[4] Sound Solut Sustainable Sci, Boston, MA 02135 USA
[5] Univ Hawaii West Oahu, Div Social Sci, Sustainable Community Food Syst Program, 91-1001 Farrington Hwy, Kapolei, HI 96707 USA
[6] Mt Holyoke Coll, South Hadley, MA 01075 USA
[7] Univ British Columbia, Dept Comp Sci, 2366 Main Mall 201, Vancouver, BC BCV6T1Z4, Canada
[8] Harvard Univ, Massachusetts Hall, Cambridge, MA 02138 USA
来源
R JOURNAL | 2022年 / 14卷 / 04期
关键词
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
To be useful, scientific results must be reproducible and trustworthy. Data provenance-the history of data and how it was computed-underlies reproducibility of, and trust in, data analyses. Our work focuses on collecting data provenance from R scripts and providing tools that use the provenance to increase the reproducibility of and trust in analyses done in R. Specifically, our "End-to -end provenance tools " ( "E2ETools ") use data provenance to: document the computing environment and inputs and outputs of a script's execution; support script debugging and exploration; and explain differences in behavior across repeated executions of the same script. Use of these tools can help both the original author and later users of a script reproduce and trust its results.
引用
收藏
页码:141 / 159
页数:19
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