ProvCaRe: A Large-Scale Semantic Provenance Resource for Scientific Reproducibility-Reference-Cited by-同舟云学术

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ProvCaRe: A Large-Scale Semantic Provenance Resource for Scientific Reproducibility

Published:2020-12-28 Issue: Volume: Page:59-73
ISSN:1610-3947
Container-title:Provenance in Data Science
language:
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Author:

Liu Chang,Kim Matthew,Rueschman Michael,Sahoo Satya S.^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-67681-0_5

Reference23 articles.

1. (2020) The National Institute of Mental Health Data Archive (NDA). https://data-archive.nimh.nih.gov

2. Aronson AR, Lang FM (2010) An overview of MetaMap: historical perspective and recent advances. J Am Med Inform Assn 17(3):229–236. https://doi.org/10.1136/jamia.2009.002733

3. Baker M (2016) 1,500 scientists lift the lid on reproducibility. Nature 7604:452–454. https://doi.org/10.1038/533452a

4. Barga R, Simmhan Y, Withana EC, Sahoo S, Jackson J, Araujo N (2010) Provenance for scientific workflows towards reproducible research. IEEE Data Eng Bull 33:50–58. https://cci.case.edu/cci/images/e/e5/Barga.pdf

5. Begley CG, Ellis LM (2012) Raise standards for preclinical cancer research. Nature 483:531–533. https://doi.org/10.1038/483531a

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1. LLMs for the Post-Hoc Creation of Provenance;2024 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW);2024-07-08

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