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% Generated by Paperpile. Check out https://paperpile.com for more information.
% BibTeX export options can be customized via Settings -> BibTeX.
@article{lowenberg_2021, title={Data Citation: Let\'s Choose Adoption Over Perfection}, DOI={10.5281/zenodo.4701079}, abstractNote={<p>This perspective piece on the perceived barriers and ways forward to advance data citation practices was written by members of the Make Data Count team which is funded by the Alfred P. Sloan Foundation. For more information on our initiative, visit <a href="https://makedatacount.org/">https://makedatacount.org</a>.</p>}, publisher={Zenodo}, author={Lowenberg, Daniella and Lammey, Rachael and Jones, Matthew B and Chodacki, John and Fenner, Martin}, year={2021}, month={Apr} }
@article{Leipzig2021,
title = {The Role of Metadata in Reproducible Computational Research},
language = {en},
journal = {Patterns},
author = {Jeremy Leipzig, Daniel Nüst, Charles Tapley Hoyt, Stian Soiland-Reyes, Karthik Ram, Jane Greenberg},
doi = {10.1016/j.patter.2021.100322},
url = {https://doi.org/10.1016/j.patter.2021.100322},
year = {2021}
}
@article{Fowler_Barratt_Walsh_2018, title={Frictionless Data: Making Research Data Quality Visible}, volume={12}, url={http://dx.doi.org/10.2218/ijdc.v12i2.577}, DOI={10.2218/ijdc.v12i2.577}, abstractNote={<jats:p>There is significant friction in the acquisition, sharing, and reuse of research data. It is estimated that eighty percent of data analysis is invested in the cleaning and mapping of data (Dasu and Johnson,2003). This friction hampers researchers not well versed in data preparation techniques from reusing an ever-increasing amount of data available within research data repositories. Frictionless Data is an ongoing project at Open Knowledge International focused on removing this friction. We are doing this by developing a set of tools, specifications, and best practices for describing, publishing, and validating data. The heart of this project is the “Data Package”, a containerization format for data based on existing practices for publishing open source software. This paper will report on current progress toward that goal.</jats:p>}, number={2}, journal={International Journal of Digital Curation}, publisher={Edinburgh University Library}, author={Fowler, Dan and Barratt, Jo and Walsh, Paul}, year={2018}, month={May}, pages={274–285} }
@misc{lowenberg_daniella_2021b, title={Data Citation: Prioritizing Adoption},
DOI={10.5281/zenodo.4726087},
publisher={Zenodo},
author={Lowenberg, Daniella},
year={2021},
month={Apr} }
@article{schofield2009,
title = {Post-publication sharing of data and tools},
volume = {461},
copyright = {2009 Nature Publishing Group},
issn = {1476-4687},
url = {https://www.nature.com/articles/461171a},
doi = {10.1038/461171a},
abstract = {Despite existing guidelines on access to data and bioresources, good practice is not widespread. A meeting of mouse researchers in Rome proposes ways to promote a culture of sharing.},
language = {en},
number = {7261},
urldate = {2021-08-11},
journal = {Nature},
author = {Schofield, Paul N. and Bubela, Tania and Weaver, Thomas and Portilla, Lili and Brown, Stephen D. and Hancock, John M. and Einhorn, David and Tocchini-Valentini, Glauco and Hrabe de Angelis, Martin and Rosenthal, Nadia},
month = sep,
year = {2009},
pages = {171--173},
}
@article{vanpaemel2015,
title = {Are {We} {Wasting} a {Good} {Crisis}? {The} {Availability} of {Psychological} {Research} {Data} after the {Storm}},
volume = {1},
issn = {2376-6832},
shorttitle = {Are {We} {Wasting} a {Good} {Crisis}?},
url = {https://doi.org/10.1525/collabra.13},
doi = {10.1525/collabra.13},
abstract = {To study the availability of psychological research data, we requested data from 394 papers, published in all issues of four APA journals in 2012. We found that 38\% of the researchers sent their data immediately or after reminders. These findings are in line with estimates of the willingness to share data in psychology from the recent or remote past. Although the recent crisis of confidence that shook psychology has highlighted the importance of open research practices, and technical developments have greatly facilitated data sharing, our findings make clear that psychology is nowhere close to being an open science.},
number = {1},
journal = {Collabra},
author = {Vanpaemel, Wolf and Vermorgen, Maarten and Deriemaecker, Leen and Storms, Gert},
month = oct,
year = {2015},
}
@book{lowenberg_2019, title={Open Data Metrics: Lighting the Fire}, DOI={10.5281/zenodo.3525349}, abstractNote={<p>Research data is at the center of science. To realize the benefits of open data sharing practices and the impact of research data, we need a practical implementation of tools and community buy-in that will aid in the development of data metrics. We will benefit the most if our community-developed standards, tools, and services are guided by a shared direction and vision for a future of open, transparent, and trusted data metrics.</p> <p>Approaches towards this future state must remain researcher-focused, have easily understandable motivations, and be easily implementable. In this book, we describe the journey towards open data metrics, prompting community discussion and providing implementation examples along the way.</p>}, note={This book was written in a five-day Book Sprint utilizing the Book Sprints methodology (www.booksprints.net).}, publisher={Zenodo}, author={Lowenberg, Daniella and Chodacki, John and Fenner, Martin and Kemp, Jennifer and Jones, Matthew B.}, year={2019}, month={Nov} }
@misc{nosek_2021,
title={Replicability, Robustness, and Reproducibility in Psychological Science},
url={psyarxiv.com/ksfvq},
DOI={10.31234/osf.io/ksfvq},
publisher={PsyArXiv},
author={Nosek, Brian A and Hardwicke, Tom E and Moshontz, Hannah and Allard, Aurélien and Corker, Katherine S and Dreber, Anna and Fidler, Fiona and Hilgard, Joseph and Kline Struhl, Melissa and Nuijten, Michele B and et al.},
year={2021},
month={Feb}
}
@article{Moles2013,
title = {A response to {Poisot} et al.: {Publishing} your dataset is not always virtuous},
volume = {6},
copyright = {Copyright (c) 2015 Angela Moles, John B. Dickie, Habacuc Flores-Moreno},
issn = {1918-3178},
shorttitle = {A response to {Poisot} et al.},
url = {https://ojs.library.queensu.ca/index.php/IEE/article/view/5093},
language = {en},
number = {2},
urldate = {2021-08-04},
journal = {Ideas in Ecology and Evolution},
author = {Moles, Angela and Dickie, John B. and Flores-Moreno, Habacuc},
month = dec,
year = {2013},
keywords = {citation, data ownership, data sharing},
}
@article{White2013,
title = {Nine simple ways to make it easier to (re)use your data},
volume = {6},
copyright = {Copyright (c) 2015 Ethan P White, Elita Baldridge, Zachary T. Brym, Kenneth J. Locey, Daniel J. McGlinn, Sarah R. Supp},
issn = {1918-3178},
url = {https://ojs.library.queensu.ca/index.php/IEE/article/view/4608},
language = {en},
number = {2},
urldate = {2021-08-04},
journal = {Ideas in Ecology and Evolution},
author = {White, Ethan P. and Baldridge, Elita and Brym, Zachary T. and Locey, Kenneth J. and McGlinn, Daniel J. and Supp, Sarah R.},
month = aug,
year = {2013},
keywords = {data, data reuse, data sharing, data structure},
}
@article{Goodman2014,
doi = {10.1371/journal.pcbi.1003542},
author = {Goodman, Alyssa AND Pepe, Alberto AND Blocker, Alexander W. AND Borgman, Christine L. AND Cranmer, Kyle AND Crosas, Merce AND Di Stefano, Rosanne AND Gil, Yolanda AND Groth, Paul AND Hedstrom, Margaret AND Hogg, David W. AND Kashyap, Vinay AND Mahabal, Ashish AND Siemiginowska, Aneta AND Slavkovic, Aleksandra},
journal = {PLOS Computational Biology},
publisher = {Public Library of Science},
title = {Ten Simple Rules for the Care and Feeding of Scientific Data},
year = {2014},
month = {04},
volume = {10},
url = {https://doi.org/10.1371/journal.pcbi.1003542},
pages = {1-5},
abstract = {null},
number = {4},
}
@article{Hart2016,
doi = {10.1371/journal.pcbi.1005097},
author = {Hart, Edmund M. AND Barmby, Pauline AND LeBauer, David AND Michonneau, François AND Mount, Sarah AND Mulrooney, Patrick AND Poisot, Timothée AND Woo, Kara H. AND Zimmerman, Naupaka B. AND Hollister, Jeffrey W.},
journal = {PLOS Computational Biology},
publisher = {Public Library of Science},
title = {Ten Simple Rules for Digital Data Storage},
year = {2016},
month = {10},
volume = {12},
url = {https://doi.org/10.1371/journal.pcbi.1005097},
pages = {1-12},
abstract = {null},
number = {10},
}
@article{Boland2017,
doi = {10.1371/journal.pcbi.1005278},
author = {Boland, Mary Regina AND Karczewski, Konrad J. AND Tatonetti, Nicholas P.},
journal = {PLOS Computational Biology},
publisher = {Public Library of Science},
title = {Ten Simple Rules to Enable Multi-site Collaborations through Data Sharing},
year = {2017},
month = {01},
volume = {13},
url = {https://doi.org/10.1371/journal.pcbi.1005278},
pages = {1-12},
abstract = {null},
number = {1},
}
@article{Marwick2018,
author = {Ben Marwick and Carl Boettiger and Lincoln Mullen},
title = {Packaging Data Analytical Work Reproducibly Using R (and Friends)},
journal = {The American Statistician},
volume = {72},
number = {1},
pages = {80-88},
year = {2018},
publisher = {Taylor & Francis},
doi = {10.1080/00031305.2017.1375986},
URL = {
https://doi.org/10.1080/00031305.2017.1375986
},
eprint = {
https://doi.org/10.1080/00031305.2017.1375986
}
}
@ARTICLE{Fowler2017,
title = "Frictionless Data: Making Research Data Quality Visible",
author = "Fowler, Dan and Barratt, Jo and Walsh, Paul",
journal = "IJDC",
publisher = "dcc-drupal.edina.ac.uk",
volume = 12,
number = 2,
pages = "274--285",
year = 2017
}
@ARTICLE{Stodden2018,
title = "An empirical analysis of journal policy effectiveness for
computational reproducibility",
author = "Stodden, Victoria and Seiler, Jennifer and Ma, Zhaokun",
abstract = "A key component of scientific communication is sufficient
information for other researchers in the field to reproduce
published findings. For computational and data-enabled research,
this has often been interpreted to mean making available the raw
data from which results were generated, the computer code that
generated the findings, and any additional information needed
such as workflows and input parameters. Many journals are
revising author guidelines to include data and code availability.
This work evaluates the effectiveness of journal policy that
requires the data and code necessary for reproducibility be made
available postpublication by the authors upon request. We assess
the effectiveness of such a policy by (i) requesting data and
code from authors and (ii) attempting replication of the
published findings. We chose a random sample of 204 scientific
papers published in the journal Science after the implementation
of their policy in February 2011. We found that we were able to
obtain artifacts from 44\% of our sample and were able to
reproduce the findings for 26\%. We find this policy-author
remission of data and code postpublication upon request-an
improvement over no policy, but currently insufficient for
reproducibility.",
journal = "Proc. Natl. Acad. Sci. U. S. A.",
volume = 115,
number = 11,
pages = "2584--2589",
month = mar,
year = 2018,
keywords = "code access; data access; open science; reproducibility policy;
reproducible research",
language = "en"
}
% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@INPROCEEDINGS{Zagalsky2015,
title = "The Emergence of {GitHub} as a Collaborative Platform for
Education",
booktitle = "Proceedings of the 18th {ACM} Conference on Computer Supported
Cooperative Work \& Social Computing",
author = "Zagalsky, Alexey and Feliciano, Joseph and Storey, Margaret-Anne
and Zhao, Yiyun and Wang, Weiliang",
abstract = "… experience for students and teachers. Only a few years after
GitHub's 2007 release, well-known computer science educator Greg
Wilson suggested4 that GitHub could be used for learning
materials despite some limitations …",
publisher = "Association for Computing Machinery",
pages = "1906--1917",
series = "CSCW '15",
month = feb,
year = 2015,
address = "New York, NY, USA",
keywords = "github, learning, education, distributed version control, cscl,
cscw, social media, qualitative methodology",
location = "Vancouver, BC, Canada"
}
@ARTICLE{Ram2013,
title = "Git can facilitate greater reproducibility and increased
transparency in science",
author = "Ram, Karthik",
abstract = "BACKGROUND: Reproducibility is the hallmark of good science.
Maintaining a high degree of transparency in scientific reporting
is essential not just for gaining trust and credibility within
the scientific community but also for facilitating the
development of new ideas. Sharing data and computer code
associated with publications is becoming increasingly common,
motivated partly in response to data deposition requirements from
journals and mandates from funders. Despite this increase in
transparency, it is still difficult to reproduce or build upon
the findings of most scientific publications without access to a
more complete workflow. FINDINGS: Version control systems (VCS),
which have long been used to maintain code repositories in the
software industry, are now finding new applications in science.
One such open source VCS, Git, provides a lightweight yet robust
framework that is ideal for managing the full suite of research
outputs such as datasets, statistical code, figures, lab notes,
and manuscripts. For individual researchers, Git provides a
powerful way to track and compare versions, retrace errors,
explore new approaches in a structured manner, while maintaining
a full audit trail. For larger collaborative efforts, Git and Git
hosting services make it possible for everyone to work
asynchronously and merge their contributions at any time, all the
while maintaining a complete authorship trail. In this paper I
provide an overview of Git along with use-cases that highlight
how this tool can be leveraged to make science more reproducible
and transparent, foster new collaborations, and support novel
uses.",
journal = "Source Code Biol. Med.",
volume = 8,
number = 1,
pages = "7",
month = feb,
year = 2013,
language = "en"
}
@ARTICLE{Pugachev2019,
title = "What Are`` The Carpentries'' and What Are They Doing in the
Library?",
author = "Pugachev, Sarah",
journal = "portal: Libraries and the Academy",
publisher = "Johns Hopkins University Press",
volume = 19,
number = 2,
pages = "209--214",
year = 2019
}
@BOOK{Nielsen2020,
title = "Reinventing Discovery: The New Era of Networked Science",
author = "Nielsen, Michael",
abstract = "How the internet and powerful online tools are democratizing and
accelerating scientific discoveryReinventing Discovery argues
that we are living at the dawn of the most dramatic change in
science in more than three hundred years. This change is being
driven by powerful cognitive tools, enabled by the internet,
which are greatly accelerating scientific discovery. There are
many books about how the internet is changing business, the
workplace, or government. But this is the first book about
something much more fundamental: how the internet is
transforming our collective intelligence and our understanding
of the world. From the collaborative mathematicians of the
Polymath Project to the amateur astronomers of Galaxy Zoo,
Reinventing Discovery tells the exciting story of the
unprecedented new era in networked science. It will interest
anyone who wants to learn about how the online world is
revolutionizing scientific discovery---and why the revolution is
just beginning.",
publisher = "Princeton University Press",
month = apr,
year = 2020,
language = "en"
}
@ARTICLE{Collberg2014,
title = "Measuring reproducibility in computer systems research",
author = "Collberg, Christian and Proebsting, Todd and Moraila, Gina and
Shankaran, Akash and Shi, Zuoming and Warren, Alex M",
journal = "Department of Computer Science, University of Arizona, Tech. Rep",
volume = 37,
year = 2014
}
@ARTICLE{Barnes2010,
title = "Publish your computer code: it is good enough",
author = "Barnes, Nick",
journal = "Nature",
volume = 467,
number = 7317,
pages = "753",
month = oct,
year = 2010,
language = "en"
}
@ARTICLE{Peng2011,
title = "Reproducible research in computational science",
author = "Peng, Roger D",
abstract = "Computational science has led to exciting new developments, but
the nature of the work has exposed limitations in our ability to
evaluate published findings. Reproducibility has the potential to
serve as a minimum standard for judging scientific claims when
full independent replication of a study is not possible.",
journal = "Science",
volume = 334,
number = 6060,
pages = "1226--1227",
month = dec,
year = 2011,
language = "en"
}
@ARTICLE{Roche2015,
title = "Public Data Archiving in Ecology and Evolution: How Well Are We
Doing?",
author = "Roche, Dominique G and Kruuk, Loeske E B and Lanfear, Robert and
Binning, Sandra A",
abstract = "Policies that mandate public data archiving (PDA) successfully
increase accessibility to data underlying scientific
publications. However, is the data quality sufficient to allow
reuse and reanalysis? We surveyed 100 datasets associated with
nonmolecular studies in journals that commonly publish ecological
and evolutionary research and have a strong PDA policy. Out of
these datasets, 56\% were incomplete, and 64\% were archived in a
way that partially or entirely prevented reuse. We suggest that
cultural shifts facilitating clearer benefits to authors are
necessary to achieve high-quality PDA and highlight key
guidelines to help authors increase their data's reuse potential
and compliance with journal data policies.",
journal = "PLoS Biol.",
volume = 13,
number = 11,
pages = "e1002295",
month = nov,
year = 2015,
language = "en"
}
@MISC{Jupyter2018,
title = "Binder 2.0 - Reproducible, interactive, sharable environments for
science at scale",
author = "Jupyter, Project and {Project Jupyter} and Bussonnier, Matthias
and Forde, Jessica and Freeman, Jeremy and Granger, Brian and
Head, Tim and Holdgraf, Chris and Kelley, Kyle and Nalvarte,
Gladys and Osheroff, Andrew and Pacer, M and Panda, Yuvi and
Perez, Fernando and Ragan-Kelley, Benjamin and Willing, Carol",
journal = "Proceedings of the 17th Python in Science Conference",
year = 2018
}
@ARTICLE{Smith2018,
title = "Journal of Open Source Software ({JOSS)}: design and first-year
review",
author = "Smith, Arfon M and Niemeyer, Kyle E and Katz, Daniel S and
Barba, Lorena A and Githinji, George and Gymrek, Melissa and
Huff, Kathryn D and Madan, Christopher R and Mayes, Abigail
Cabunoc and Moerman, Kevin M and Prins, Pjotr and Ram, Karthik
and Rokem, Ariel and Teal, Tracy K and Guimera, Roman Valls and
Vanderplas, Jacob T",
abstract = "This article describes the motivation, design, and progress of
the Journal of Open Source Software (JOSS). JOSS is a free and
open-access journal that publishes articles describing research
software. It has the dual goals of improving the quality of the
software submitted and providing a mechanism for research
software developers to receive credit. While designed to work
within the current merit system of science, JOSS addresses the
dearth of rewards for key contributions to science made in the
form of software. JOSS publishes articles that encapsulate
scholarship contained in the software itself, and its rigorous
peer review targets the software components: functionality,
documentation, tests, continuous integration, and the license. A
JOSS article contains an abstract describing the purpose and
functionality of the software, references, and a link to the
software archive. The article is the entry point of a JOSS
submission, which encompasses the full set of software
artifacts. Submission and review proceed in the open, on GitHub.
Editors, reviewers, and authors work collaboratively and openly.
Unlike other journals, JOSS does not reject articles requiring
major revision; while not yet accepted, articles remain visible
and under review until the authors make adequate changes (or
withdraw, if unable to meet requirements). Once an article is
accepted, JOSS gives it a digital object identifier (DOI),
deposits its metadata in Crossref, and the article can begin
collecting citations on indexers like Google Scholar and other
services. Authors retain copyright of their JOSS article,
releasing it under a Creative Commons Attribution 4.0
International License. In its first year, starting in May 2016,
JOSS published 111 articles, with more than 40 additional
articles under review. JOSS is a sponsored project of the
nonprofit organization NumFOCUS and is an affiliate of the Open
Source Initiative (OSI).",
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year = 2018,
keywords = "Research software; Code review; Computational research; Software
citation; Open-source software; Scholarly publishing",
language = "en"
}
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title = "An introduction to Docker for reproducible research",
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@ARTICLE{Donoho2017,
title = "50 Years of Data Science",
author = "Donoho, David",
journal = "Journal of computational and graphical statistics: a joint
publication of American Statistical Association, Institute of
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@article{McKiernan2016, title={How open science helps researchers succeed}, volume={5}, url={http://dx.doi.org/10.7554/eLife.16800}, DOI={10.7554/elife.16800}, abstractNote={<jats:p>Open access, open data, open source and other open scholarship practices are growing in popularity and necessity. However, widespread adoption of these practices has not yet been achieved. One reason is that researchers are uncertain about how sharing their work will affect their careers. We review literature demonstrating that open research is associated with increases in citations, media attention, potential collaborators, job opportunities and funding opportunities. These findings are evidence that open research practices bring significant benefits to researchers relative to more traditional closed practices.</jats:p>}, journal={eLife}, publisher={eLife Sciences Publications, Ltd}, author={McKiernan, Erin C and Bourne, Philip E and Brown, C Titus and Buck, Stuart and Kenall, Amye and Lin, Jennifer and McDougall, Damon and Nosek, Brian A and Ram, Karthik and Soderberg, Courtney K and et al.}, year={2016}, month={Jul} }
@ARTICLE{Colavizza2020,
title = "The citation advantage of linking publications to research data",
author = "Colavizza, Giovanni and Hrynaszkiewicz, Iain and Staden, Isla and
Whitaker, Kirstie and McGillivray, Barbara",
abstract = "Efforts to make research results open and reproducible are
increasingly reflected by journal policies encouraging or
mandating authors to provide data availability statements. As a
consequence of this, there has been a strong uptake of data
availability statements in recent literature. Nevertheless, it is
still unclear what proportion of these statements actually
contain well-formed links to data, for example via a URL or
permanent identifier, and if there is an added value in providing
such links. We consider 531, 889 journal articles published by
PLOS and BMC, develop an automatic system for labelling their
data availability statements according to four categories based
on their content and the type of data availability they display,
and finally analyze the citation advantage of different statement
categories via regression. We find that, following mandated
publisher policies, data availability statements become very
common. In 2018 93.7\% of 21,793 PLOS articles and 88.2\% of
31,956 BMC articles had data availability statements. Data
availability statements containing a link to data in a
repository-rather than being available on request or included as
supporting information files-are a fraction of the total. In 2017
and 2018, 20.8\% of PLOS publications and 12.2\% of BMC
publications provided DAS containing a link to data in a
repository. We also find an association between articles that
include statements that link to data in a repository and up to
25.36\% ($\pm$ 1.07\%) higher citation impact on average, using a
citation prediction model. We discuss the potential implications
of these results for authors (researchers) and journal publishers
who make the effort of sharing their data in repositories. All
our data and code are made available in order to reproduce and
extend our results.",
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number = 4,
pages = "e0230416",
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year = 2020,
language = "en"
}
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title = "The {FAIR} Guiding Principles for scientific data management and
stewardship",
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Jsbrand Jan and Appleton, Gabrielle and Axton, Myles and Baak,
Arie and Blomberg, Niklas and Boiten, Jan-Willem and da Silva
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Brookes, Anthony J and Clark, Tim and Crosas, Merc{\`e} and
Dillo, Ingrid and Dumon, Olivier and Edmunds, Scott and Evelo,
Chris T and Finkers, Richard and Gonzalez-Beltran, Alejandra and
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Mulligen, Erik and Velterop, Jan and Waagmeester, Andra and
Wittenburg, Peter and Wolstencroft, Katherine and Zhao, Jun and
Mons, Barend",
abstract = "There is an urgent need to improve the infrastructure supporting
the reuse of scholarly data. A diverse set of
stakeholders-representing academia, industry, funding agencies,
and scholarly publishers-have come together to design and jointly
endorse a concise and measureable set of principles that we refer
to as the FAIR Data Principles. The intent is that these may act
as a guideline for those wishing to enhance the reusability of
their data holdings. Distinct from peer initiatives that focus on
the human scholar, the FAIR Principles put specific emphasis on
enhancing the ability of machines to automatically find and use
the data, in addition to supporting its reuse by individuals.
This Comment is the first formal publication of the FAIR
Principles, and includes the rationale behind them, and some
exemplar implementations in the community.",
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year = 2016,
language = "en"
}
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title = "How to Automatically Document Data With the codebook Package to
Facilitate Data Reuse",
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@ARTICLE{Wilson2014,
title = "Software Carpentry: lessons learned",
author = "Wilson, Greg",
abstract = "Since its start in 1998, Software Carpentry has evolved from a
week-long training course at the US national laboratories into a
worldwide volunteer effort to improve researchers' computing
skills. This paper explains what we have learned along the way,
the challenges we now face, and our plans for the future.",
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pages = "62",
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year = 2014,
keywords = "Education; Scientific Computing; Software Carpentry; Training",
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}
@misc{ccby-short,
title = {CCBY Short Guide},
howpublished = {https://creativecommons.org/licenses/by/4.0/},
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title = {CCBY Full License},
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title = "Data organization in spreadsheets",
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title = "How to share data for collaboration",
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year = 2017,
language = "en"
}
@misc{EML-about,
url = {https://knb.ecoinformatics.org/#external//emlparser/docs/index.html},
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}
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publisher = {Foundation for Open Access Statistic},
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title = {Tidy Data},
journal = {Journal of Statistical Software}
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title = "Sharing detailed research data is associated with increased
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@misc{plos-comp-bio-data,
title = {PLOS Computational Biology},
url = {https://journals.plos.org/ploscompbiol/s/data-availability},
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@ARTICLE{google-data-search,
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@misc{Maerz2014,
title={Stream salamander mark-recapture abundance study at the Coweeta Hydrologic Laboratory, Otto, NC.},
url={https://portal.edirepository.org/nis/mapbrowse?packageid=knb-lter-cwt.3091.13},
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@misc{Schleunes2020,
title = {Top spider biologist’s research under fire},
url = {https://www.the-scientist.com/news-opinion/top-spider-biologists-research-under-fire-67083},
abstract = {After the initial announcements of two retractions, scientists have mobilized to interrogate the data in nearly 150 of Jonathan Pruitt's papers.},
language = {en},
urldate = {2020-09-23},
journal = {The Scientist},
author = {Schleunes, Amy},
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title = "'Avalanche' of spider-paper retractions shakes
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