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Micropublication: incentivizing community curation and placing unpublished data into the public domain

Large volumes of data generated by research laboratories coupled with the required effort and cost of curation present a significant barrier to inclusion of these data in authoritative community databases. Further, many publicly funded experimental observations remain invisible to curation simply be...

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Detalles Bibliográficos
Autores principales: Raciti, Daniela, Yook, Karen, Harris, Todd W, Schedl, Tim, Sternberg, Paul W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5836261/
https://www.ncbi.nlm.nih.gov/pubmed/29688367
http://dx.doi.org/10.1093/database/bay013
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author Raciti, Daniela
Yook, Karen
Harris, Todd W
Schedl, Tim
Sternberg, Paul W
author_facet Raciti, Daniela
Yook, Karen
Harris, Todd W
Schedl, Tim
Sternberg, Paul W
author_sort Raciti, Daniela
collection PubMed
description Large volumes of data generated by research laboratories coupled with the required effort and cost of curation present a significant barrier to inclusion of these data in authoritative community databases. Further, many publicly funded experimental observations remain invisible to curation simply because they are never published: results often do not fit within the scope of a standard publication; trainee-generated data are forgotten when the experimenter (e.g. student, post-doc) leaves the lab; results are omitted from science narratives due to publication bias where certain results are considered irrelevant for the publication. While authors are in the best position to curate their own data, they face a steep learning curve to ensure that appropriate referential tags, metadata, and ontologies are applied correctly to their observations, a task sometimes considered beyond the scope of their research and other numerous responsibilities. Getting researchers to adopt a new system of data reporting and curation requires a fundamental change in behavior among all members of the research community. To solve these challenges, we have created a novel scholarly communication platform that captures data from researchers and directly delivers them to information resources via Micropublication. This platform incentivizes authors to publish their unpublished observations along with associated metadata by providing a deliberately fast and lightweight but still peer-reviewed process that results in a citable publication. Our long-term goal is to develop a data ecosystem that improves reproducibility and accountability of publicly funded research and in turn accelerates both basic and translational discovery. Database URL: www.micropublication.org
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spelling pubmed-58362612018-03-09 Micropublication: incentivizing community curation and placing unpublished data into the public domain Raciti, Daniela Yook, Karen Harris, Todd W Schedl, Tim Sternberg, Paul W Database (Oxford) Original Article Large volumes of data generated by research laboratories coupled with the required effort and cost of curation present a significant barrier to inclusion of these data in authoritative community databases. Further, many publicly funded experimental observations remain invisible to curation simply because they are never published: results often do not fit within the scope of a standard publication; trainee-generated data are forgotten when the experimenter (e.g. student, post-doc) leaves the lab; results are omitted from science narratives due to publication bias where certain results are considered irrelevant for the publication. While authors are in the best position to curate their own data, they face a steep learning curve to ensure that appropriate referential tags, metadata, and ontologies are applied correctly to their observations, a task sometimes considered beyond the scope of their research and other numerous responsibilities. Getting researchers to adopt a new system of data reporting and curation requires a fundamental change in behavior among all members of the research community. To solve these challenges, we have created a novel scholarly communication platform that captures data from researchers and directly delivers them to information resources via Micropublication. This platform incentivizes authors to publish their unpublished observations along with associated metadata by providing a deliberately fast and lightweight but still peer-reviewed process that results in a citable publication. Our long-term goal is to develop a data ecosystem that improves reproducibility and accountability of publicly funded research and in turn accelerates both basic and translational discovery. Database URL: www.micropublication.org Oxford University Press 2018-03-02 /pmc/articles/PMC5836261/ /pubmed/29688367 http://dx.doi.org/10.1093/database/bay013 Text en © The Author(s) 2018. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Raciti, Daniela
Yook, Karen
Harris, Todd W
Schedl, Tim
Sternberg, Paul W
Micropublication: incentivizing community curation and placing unpublished data into the public domain
title Micropublication: incentivizing community curation and placing unpublished data into the public domain
title_full Micropublication: incentivizing community curation and placing unpublished data into the public domain
title_fullStr Micropublication: incentivizing community curation and placing unpublished data into the public domain
title_full_unstemmed Micropublication: incentivizing community curation and placing unpublished data into the public domain
title_short Micropublication: incentivizing community curation and placing unpublished data into the public domain
title_sort micropublication: incentivizing community curation and placing unpublished data into the public domain
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5836261/
https://www.ncbi.nlm.nih.gov/pubmed/29688367
http://dx.doi.org/10.1093/database/bay013
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