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GigaDB: promoting data dissemination and reproducibility

Often papers are published where the underlying data supporting the research are not made available because of the limitations of making such large data sets publicly and permanently accessible. Even if the raw data are deposited in public archives, the essential analysis intermediaries, scripts or...

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Detalles Bibliográficos
Autores principales: Sneddon, Tam P., Si Zhe, Xiao, Edmunds, Scott C., Li, Peter, Goodman, Laurie, Hunter, Christopher I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3950661/
https://www.ncbi.nlm.nih.gov/pubmed/24622612
http://dx.doi.org/10.1093/database/bau018
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author Sneddon, Tam P.
Si Zhe, Xiao
Edmunds, Scott C.
Li, Peter
Goodman, Laurie
Hunter, Christopher I.
author_facet Sneddon, Tam P.
Si Zhe, Xiao
Edmunds, Scott C.
Li, Peter
Goodman, Laurie
Hunter, Christopher I.
author_sort Sneddon, Tam P.
collection PubMed
description Often papers are published where the underlying data supporting the research are not made available because of the limitations of making such large data sets publicly and permanently accessible. Even if the raw data are deposited in public archives, the essential analysis intermediaries, scripts or software are frequently not made available, meaning the science is not reproducible. The GigaScience journal is attempting to address this issue with the associated data storage and dissemination portal, the GigaScience database (GigaDB). Here we present the current version of GigaDB and reveal plans for the next generation of improvements. However, most importantly, we are soliciting responses from you, the users, to ensure that future developments are focused on the data storage and dissemination issues that still need resolving. Database URL: http://www.gigadb.org
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spelling pubmed-39506612014-03-13 GigaDB: promoting data dissemination and reproducibility Sneddon, Tam P. Si Zhe, Xiao Edmunds, Scott C. Li, Peter Goodman, Laurie Hunter, Christopher I. Database (Oxford) Original Article Often papers are published where the underlying data supporting the research are not made available because of the limitations of making such large data sets publicly and permanently accessible. Even if the raw data are deposited in public archives, the essential analysis intermediaries, scripts or software are frequently not made available, meaning the science is not reproducible. The GigaScience journal is attempting to address this issue with the associated data storage and dissemination portal, the GigaScience database (GigaDB). Here we present the current version of GigaDB and reveal plans for the next generation of improvements. However, most importantly, we are soliciting responses from you, the users, to ensure that future developments are focused on the data storage and dissemination issues that still need resolving. Database URL: http://www.gigadb.org Oxford University Press 2014-03-12 /pmc/articles/PMC3950661/ /pubmed/24622612 http://dx.doi.org/10.1093/database/bau018 Text en © The Author(s) 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Sneddon, Tam P.
Si Zhe, Xiao
Edmunds, Scott C.
Li, Peter
Goodman, Laurie
Hunter, Christopher I.
GigaDB: promoting data dissemination and reproducibility
title GigaDB: promoting data dissemination and reproducibility
title_full GigaDB: promoting data dissemination and reproducibility
title_fullStr GigaDB: promoting data dissemination and reproducibility
title_full_unstemmed GigaDB: promoting data dissemination and reproducibility
title_short GigaDB: promoting data dissemination and reproducibility
title_sort gigadb: promoting data dissemination and reproducibility
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3950661/
https://www.ncbi.nlm.nih.gov/pubmed/24622612
http://dx.doi.org/10.1093/database/bau018
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