Causal Provenance
Causal Provenance is a type of data provenance that captures and represents the causal dependencies between data artifacts, specifically identifying which inputs and processes directly influence the generation of a given output.
15
Publications
874
Citations
27
Authors
16
Institutions
Publications per year
2017–2026
7
Parents
15
Alexandra Meliou, Wolfgang Gatterbauer, Joseph Y. Halpern et al. · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · 2010 · 88 citations · Full text
Causality and explanations in databases
Alexandra Meliou, Sudeepa Roy, Dan Suciu · Proceedings of the VLDB Endowment · 2014 · 74 citations
Drawing causal inference from Big Data
Richard M. Shiffrin · Proceedings of the National Academy of Sciences · 2016 · 71 citations · Full text
Computing, Data Science, Sociology +13
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16
University of Washington
Seattle, United States
5 h-index
17 publications
1.4K citations
Purdue University West Lafayette
West Lafayette, United States
2 h-index
3 publications
173 citations

University of Edinburgh
Edinburgh, United Kingdom
1 h-index
1 publications
30 citations
Menlo School
Atherton, United States
1 h-index
3 publications
186 citations
Rutgers Sexual and Reproductive Health and Rights
Utrecht, Netherlands
1 h-index
1 publications
49 citations
University of Wisconsin–Madison
Madison, United States
1 h-index
2 publications
124 citations
The University of Texas at San Antonio
San Antonio, United States
1 h-index
1 publications
62 citations
Bath Social and Development Research
Bath, United Kingdom
1 h-index
1 publications
16 citations
1–8 of 16
PVLDB · 2 publications · 259 citations
2
h-index
1 publications · 16 citations
1
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Repository · 1 publications · 88 citations
1
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Repository · 1 publications · 17 citations
1
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PNAS · 1 publications · 71 citations
1
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