COMPUTER SCIENCE. Accessible Reproducible Research

By Jill P. Mesirov. Science, 2010

295 citations recorded by the source corpus.

As use of computation in research grows, new tools are needed to expand recording, reporting, and reproduction of methods and data. Scientific publications have at least two goals: (i) to announce a result and (ii) to convince readers that the result is correct. Mathematics papers are expected to contain a proof complete enough to allow knowledgeable readers to fill in any details. Papers in experimental science should describe the results and provide a clear enough protocol to allow successful repetition and extension.

Subfields: Biophysics, Information Systems, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/db871292f2a5bb7b93ed367e6d0dd93623b2a036

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Citations in the corpus

Directions in abusive language training data, a systematic review: Garbage in, garbage out (2020, background): “It would (1) enable greater collaboration amongst researchers, (2) enhance the reproducibility of research [123–125] and (3) substantively advance the field by enabling researchers to better understand the limitations of existing research and to identify new research directions.”
Identification of Reproducible Subsets for Data Citation, Sharing and Re-Use (2016, background): “A scientific process is reproducible if an independent peer scientist can re-execute the experiment and validate the results [15].”
Directions in Abusive Language Training Data: Garbage In, Garbage Out (2020, background): “…sharing would (1) greater collaboration amongst researchers, (2) enhance the reproducibility of research by encouraging greater scrutiny [54, 77, 80] and (3) substantively advance the field by enabling future researchers to better understand the biases and limitations of existing research…”
Anserini (2018, background): “Just focusing on the computational sciences (in particular, setting aside the medical sciences), there has already been much discussion [21, 24, 37, 44] as well as concrete proposals to improve the state of affairs [20, 25, 46].”
The case for open computer programs (2012, methodology): “Two examples here are Sweave associated with the programming language R and the text-processing systems LaTeX and LyX, and GenePattern-Word RRS , a system specific to genomic researc”
A standard protocol for reporting species distribution models (2020, background): “In summary, ODMAP will help answer the clarion calls for reproducible computational science (Peng 2011), and for improved recording and reporting of methods and data (Mesirov 2010, Munafò et al. 2017), within the field of species distribution modelling, a crucial tool for science and conservation.”
Why Linked Data is Not Enough for Scientists (2010, background): “Mesirov [4] describes the notion of Accessible Reproducable Research, where scientific publications should provide clear enough descriptions of the protocols to enable allow successful repetition and extension.”
Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences (2010, methodology): “To support reproducible computational research, the concept of a Reproducible Research System (RRS) has been proposed [11].”
Advances in global change research require open science by individual researchers (2012, background): “Increasingly, global change science is indirect (Mesirov, 2010), that is, datasets are too large to visually handle and thus researchers must process data without seeing every row personally.”
Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science (2016, background): “As computational approaches increasingly become more complex reproducibility issue will also become more important as the development of novel algorithmic approach will become the focus of future publication results (Mesirov 2010).”