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Scientific workflows for bibliometrics

Scientific workflows organize the assembly of specialized software into an overall data flow and are particularly well suited for multi-step analyses using different types of software tools. They are also favorable in terms of reusability, as previously designed workflows could be made publicly avai...

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Detalles Bibliográficos
Autores principales: Guler, Arzu Tugce, Waaijer, Cathelijn J. F., Palmblad, Magnus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4833826/
https://www.ncbi.nlm.nih.gov/pubmed/27122644
http://dx.doi.org/10.1007/s11192-016-1885-6
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author Guler, Arzu Tugce
Waaijer, Cathelijn J. F.
Palmblad, Magnus
author_facet Guler, Arzu Tugce
Waaijer, Cathelijn J. F.
Palmblad, Magnus
author_sort Guler, Arzu Tugce
collection PubMed
description Scientific workflows organize the assembly of specialized software into an overall data flow and are particularly well suited for multi-step analyses using different types of software tools. They are also favorable in terms of reusability, as previously designed workflows could be made publicly available through the myExperiment community and then used in other workflows. We here illustrate how scientific workflows and the Taverna workbench in particular can be used in bibliometrics. We discuss the specific capabilities of Taverna that makes this software a powerful tool in this field, such as automated data import via Web services, data extraction from XML by XPaths, and statistical analysis and visualization with R. The support of the latter is particularly relevant, as it allows integration of a number of recently developed R packages specifically for bibliometrics. Examples are used to illustrate the possibilities of Taverna in the fields of bibliometrics and scientometrics.
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spelling pubmed-48338262016-04-25 Scientific workflows for bibliometrics Guler, Arzu Tugce Waaijer, Cathelijn J. F. Palmblad, Magnus Scientometrics Article Scientific workflows organize the assembly of specialized software into an overall data flow and are particularly well suited for multi-step analyses using different types of software tools. They are also favorable in terms of reusability, as previously designed workflows could be made publicly available through the myExperiment community and then used in other workflows. We here illustrate how scientific workflows and the Taverna workbench in particular can be used in bibliometrics. We discuss the specific capabilities of Taverna that makes this software a powerful tool in this field, such as automated data import via Web services, data extraction from XML by XPaths, and statistical analysis and visualization with R. The support of the latter is particularly relevant, as it allows integration of a number of recently developed R packages specifically for bibliometrics. Examples are used to illustrate the possibilities of Taverna in the fields of bibliometrics and scientometrics. Springer Netherlands 2016-02-15 2016 /pmc/articles/PMC4833826/ /pubmed/27122644 http://dx.doi.org/10.1007/s11192-016-1885-6 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Guler, Arzu Tugce
Waaijer, Cathelijn J. F.
Palmblad, Magnus
Scientific workflows for bibliometrics
title Scientific workflows for bibliometrics
title_full Scientific workflows for bibliometrics
title_fullStr Scientific workflows for bibliometrics
title_full_unstemmed Scientific workflows for bibliometrics
title_short Scientific workflows for bibliometrics
title_sort scientific workflows for bibliometrics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4833826/
https://www.ncbi.nlm.nih.gov/pubmed/27122644
http://dx.doi.org/10.1007/s11192-016-1885-6
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