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

页码：141 / 159

页数：19

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