Abstract
Reproducibility is a core component of the scientific process. Revisiting and reusing past results allow science to move forward - "standing on the shoulders of giants", as Newton once said. An impediment to the adoption of computational reproducibility is that authors find it difficult to generate a compendium that en compasses all the required components to correctly reproduce their experiments. Even when a compendium is available, reviewers and readers may have difficulties in verifying the results on platforms different from the ones where the experiments were originally run. As a step towards simplifying the process of creating reproducible experiments, we have developed ReproZip, a tool that automatically captures the provenance of experiments and packs all the necessary files, library dependencies and variables to reproduce the results. Reviewers can then unpack and run the experiments without having to install any additional software. We will demonstrate real use cases for ReproZip, how packages are created, and how reviewers can validate and explore experiments.
| Original language | English (US) |
|---|---|
| Title of host publication | SIGMOD 2013 - International Conference on Management of Data |
| Pages | 977-980 |
| Number of pages | 4 |
| DOIs | |
| State | Published - 2013 |
| Event | 2013 ACM SIGMOD Conference on Management of Data, SIGMOD 2013 - New York, NY, United States Duration: Jun 22 2013 → Jun 27 2013 |
Other
| Other | 2013 ACM SIGMOD Conference on Management of Data, SIGMOD 2013 |
|---|---|
| Country | United States |
| City | New York, NY |
| Period | 6/22/13 → 6/27/13 |
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Keywords
- Computational Reproducibility
- Provenance
- ReproZip
ASJC Scopus subject areas
- Software
- Information Systems
Cite this
Packing experiments for sharing and publication. / Chirigati, Fernando; Shasha, Dennis; Freire, Juliana.
SIGMOD 2013 - International Conference on Management of Data. 2013. p. 977-980.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Packing experiments for sharing and publication
AU - Chirigati, Fernando
AU - Shasha, Dennis
AU - Freire, Juliana
PY - 2013
Y1 - 2013
N2 - Reproducibility is a core component of the scientific process. Revisiting and reusing past results allow science to move forward - "standing on the shoulders of giants", as Newton once said. An impediment to the adoption of computational reproducibility is that authors find it difficult to generate a compendium that en compasses all the required components to correctly reproduce their experiments. Even when a compendium is available, reviewers and readers may have difficulties in verifying the results on platforms different from the ones where the experiments were originally run. As a step towards simplifying the process of creating reproducible experiments, we have developed ReproZip, a tool that automatically captures the provenance of experiments and packs all the necessary files, library dependencies and variables to reproduce the results. Reviewers can then unpack and run the experiments without having to install any additional software. We will demonstrate real use cases for ReproZip, how packages are created, and how reviewers can validate and explore experiments.
AB - Reproducibility is a core component of the scientific process. Revisiting and reusing past results allow science to move forward - "standing on the shoulders of giants", as Newton once said. An impediment to the adoption of computational reproducibility is that authors find it difficult to generate a compendium that en compasses all the required components to correctly reproduce their experiments. Even when a compendium is available, reviewers and readers may have difficulties in verifying the results on platforms different from the ones where the experiments were originally run. As a step towards simplifying the process of creating reproducible experiments, we have developed ReproZip, a tool that automatically captures the provenance of experiments and packs all the necessary files, library dependencies and variables to reproduce the results. Reviewers can then unpack and run the experiments without having to install any additional software. We will demonstrate real use cases for ReproZip, how packages are created, and how reviewers can validate and explore experiments.
KW - Computational Reproducibility
KW - Provenance
KW - ReproZip
UR - http://www.scopus.com/inward/record.url?scp=84880534236&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84880534236&partnerID=8YFLogxK
U2 - 10.1145/2463676.2465269
DO - 10.1145/2463676.2465269
M3 - Conference contribution
SN - 9781450320375
SP - 977
EP - 980
BT - SIGMOD 2013 - International Conference on Management of Data
ER -