Cargando…

Dataset of identified scholars mentioned in acknowledgement statements

Acknowledgements represent scholars’ relationships as part of the research contribution. While co-authors and citations are often provided as a well-formatted bibliometric database, acknowledged individuals are difficult to identify because they appear as part of the statements in the paper. We iden...

Descripción completa

Detalles Bibliográficos
Autores principales: Kusumegi, Keigo, Sano, Yukie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343655/
https://www.ncbi.nlm.nih.gov/pubmed/35915099
http://dx.doi.org/10.1038/s41597-022-01585-y
_version_ 1784761036481495040
author Kusumegi, Keigo
Sano, Yukie
author_facet Kusumegi, Keigo
Sano, Yukie
author_sort Kusumegi, Keigo
collection PubMed
description Acknowledgements represent scholars’ relationships as part of the research contribution. While co-authors and citations are often provided as a well-formatted bibliometric database, acknowledged individuals are difficult to identify because they appear as part of the statements in the paper. We identify acknowledged scholars who appeared in papers published in open-access journals by referring to the co-author and citation relationships stored in the Microsoft Academic Graph (MAG). Therefore, the constructed dataset is compatible with MAG, which accelerates and expands the acknowledgements as a data source of scholarly relationships similar to collaboration and citation analysis. Moreover, the implemented code is publicly available; thus, it can be applied in other studies.
format Online
Article
Text
id pubmed-9343655
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-93436552022-08-03 Dataset of identified scholars mentioned in acknowledgement statements Kusumegi, Keigo Sano, Yukie Sci Data Data Descriptor Acknowledgements represent scholars’ relationships as part of the research contribution. While co-authors and citations are often provided as a well-formatted bibliometric database, acknowledged individuals are difficult to identify because they appear as part of the statements in the paper. We identify acknowledged scholars who appeared in papers published in open-access journals by referring to the co-author and citation relationships stored in the Microsoft Academic Graph (MAG). Therefore, the constructed dataset is compatible with MAG, which accelerates and expands the acknowledgements as a data source of scholarly relationships similar to collaboration and citation analysis. Moreover, the implemented code is publicly available; thus, it can be applied in other studies. Nature Publishing Group UK 2022-08-01 /pmc/articles/PMC9343655/ /pubmed/35915099 http://dx.doi.org/10.1038/s41597-022-01585-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Kusumegi, Keigo
Sano, Yukie
Dataset of identified scholars mentioned in acknowledgement statements
title Dataset of identified scholars mentioned in acknowledgement statements
title_full Dataset of identified scholars mentioned in acknowledgement statements
title_fullStr Dataset of identified scholars mentioned in acknowledgement statements
title_full_unstemmed Dataset of identified scholars mentioned in acknowledgement statements
title_short Dataset of identified scholars mentioned in acknowledgement statements
title_sort dataset of identified scholars mentioned in acknowledgement statements
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343655/
https://www.ncbi.nlm.nih.gov/pubmed/35915099
http://dx.doi.org/10.1038/s41597-022-01585-y
work_keys_str_mv AT kusumegikeigo datasetofidentifiedscholarsmentionedinacknowledgementstatements
AT sanoyukie datasetofidentifiedscholarsmentionedinacknowledgementstatements