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Developing a modern data workflow for regularly updated data

Over the past decade, biology has undergone a data revolution in how researchers collect data and the amount of data being collected. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. Regula...

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Detalles Bibliográficos
Autores principales: Yenni, Glenda M., Christensen, Erica M., Bledsoe, Ellen K., Supp, Sarah R., Diaz, Renata M., White, Ethan P., Ernest, S. K. Morgan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368360/
https://www.ncbi.nlm.nih.gov/pubmed/30695030
http://dx.doi.org/10.1371/journal.pbio.3000125
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author Yenni, Glenda M.
Christensen, Erica M.
Bledsoe, Ellen K.
Supp, Sarah R.
Diaz, Renata M.
White, Ethan P.
Ernest, S. K. Morgan
author_facet Yenni, Glenda M.
Christensen, Erica M.
Bledsoe, Ellen K.
Supp, Sarah R.
Diaz, Renata M.
White, Ethan P.
Ernest, S. K. Morgan
author_sort Yenni, Glenda M.
collection PubMed
description Over the past decade, biology has undergone a data revolution in how researchers collect data and the amount of data being collected. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. Regularly updated data present unique challenges in quality assurance and control, data publication, archiving, and reproducibility. We developed a workflow for a long-term ecological study that addresses many of the challenges associated with managing this type of data. We do this by leveraging existing tools to 1) perform quality assurance and control; 2) import, restructure, version, and archive data; 3) rapidly publish new data in ways that ensure appropriate credit to all contributors; and 4) automate most steps in the data pipeline to reduce the time and effort required by researchers. The workflow leverages tools from software development, including version control and continuous integration, to create a modern data management system that automates the pipeline.
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spelling pubmed-63683602019-02-22 Developing a modern data workflow for regularly updated data Yenni, Glenda M. Christensen, Erica M. Bledsoe, Ellen K. Supp, Sarah R. Diaz, Renata M. White, Ethan P. Ernest, S. K. Morgan PLoS Biol Community Page Over the past decade, biology has undergone a data revolution in how researchers collect data and the amount of data being collected. An emerging challenge that has received limited attention in biology is managing, working with, and providing access to data under continual active collection. Regularly updated data present unique challenges in quality assurance and control, data publication, archiving, and reproducibility. We developed a workflow for a long-term ecological study that addresses many of the challenges associated with managing this type of data. We do this by leveraging existing tools to 1) perform quality assurance and control; 2) import, restructure, version, and archive data; 3) rapidly publish new data in ways that ensure appropriate credit to all contributors; and 4) automate most steps in the data pipeline to reduce the time and effort required by researchers. The workflow leverages tools from software development, including version control and continuous integration, to create a modern data management system that automates the pipeline. Public Library of Science 2019-01-29 /pmc/articles/PMC6368360/ /pubmed/30695030 http://dx.doi.org/10.1371/journal.pbio.3000125 Text en © 2019 Yenni et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Community Page
Yenni, Glenda M.
Christensen, Erica M.
Bledsoe, Ellen K.
Supp, Sarah R.
Diaz, Renata M.
White, Ethan P.
Ernest, S. K. Morgan
Developing a modern data workflow for regularly updated data
title Developing a modern data workflow for regularly updated data
title_full Developing a modern data workflow for regularly updated data
title_fullStr Developing a modern data workflow for regularly updated data
title_full_unstemmed Developing a modern data workflow for regularly updated data
title_short Developing a modern data workflow for regularly updated data
title_sort developing a modern data workflow for regularly updated data
topic Community Page
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368360/
https://www.ncbi.nlm.nih.gov/pubmed/30695030
http://dx.doi.org/10.1371/journal.pbio.3000125
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