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Analyzing University of Virginia Health publications using open data, Python, and Streamlit
As part of a larger project to understand the publishing choices of UVA Health authors and support open access publishing, a team from the Claude Moore Health Sciences Library analyzed an open data set from Europe PMC, which includes metadata from PubMed records. We used the Europe PMC REST API to s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
University Library System, University of Pittsburgh
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8608219/ https://www.ncbi.nlm.nih.gov/pubmed/34858105 http://dx.doi.org/10.5195/jmla.2021.1360 |
_version_ | 1784602708867547136 |
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author | Parker, Anson Heflin, Abbey Jones, Lucy Carr |
author_facet | Parker, Anson Heflin, Abbey Jones, Lucy Carr |
author_sort | Parker, Anson |
collection | PubMed |
description | As part of a larger project to understand the publishing choices of UVA Health authors and support open access publishing, a team from the Claude Moore Health Sciences Library analyzed an open data set from Europe PMC, which includes metadata from PubMed records. We used the Europe PMC REST API to search for articles published in 2017–2020 with “University of Virginia” in the author affiliation field. Subsequently, we parsed the JSON metadata in Python and used Streamlit to create a data visualization from our public GitHub repository. At present, this shows the relative proportions of open access versus subscription-only articles published by UVA Health authors. Although subscription services like Web of Science, Scopus, and Dimensions allow users to do similar analyses, we believe this is a novel approach to doing this type of bibliometric research with open data and open source tools. |
format | Online Article Text |
id | pubmed-8608219 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | University Library System, University of Pittsburgh |
record_format | MEDLINE/PubMed |
spelling | pubmed-86082192021-12-01 Analyzing University of Virginia Health publications using open data, Python, and Streamlit Parker, Anson Heflin, Abbey Jones, Lucy Carr J Med Libr Assoc Virtual Project As part of a larger project to understand the publishing choices of UVA Health authors and support open access publishing, a team from the Claude Moore Health Sciences Library analyzed an open data set from Europe PMC, which includes metadata from PubMed records. We used the Europe PMC REST API to search for articles published in 2017–2020 with “University of Virginia” in the author affiliation field. Subsequently, we parsed the JSON metadata in Python and used Streamlit to create a data visualization from our public GitHub repository. At present, this shows the relative proportions of open access versus subscription-only articles published by UVA Health authors. Although subscription services like Web of Science, Scopus, and Dimensions allow users to do similar analyses, we believe this is a novel approach to doing this type of bibliometric research with open data and open source tools. University Library System, University of Pittsburgh 2021-10-01 2021-10-01 /pmc/articles/PMC8608219/ /pubmed/34858105 http://dx.doi.org/10.5195/jmla.2021.1360 Text en Copyright © 2021 Anson Parker, Abbey Heflin, Lucy Carr Jones https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Virtual Project Parker, Anson Heflin, Abbey Jones, Lucy Carr Analyzing University of Virginia Health publications using open data, Python, and Streamlit |
title | Analyzing University of Virginia Health publications using open data, Python, and Streamlit |
title_full | Analyzing University of Virginia Health publications using open data, Python, and Streamlit |
title_fullStr | Analyzing University of Virginia Health publications using open data, Python, and Streamlit |
title_full_unstemmed | Analyzing University of Virginia Health publications using open data, Python, and Streamlit |
title_short | Analyzing University of Virginia Health publications using open data, Python, and Streamlit |
title_sort | analyzing university of virginia health publications using open data, python, and streamlit |
topic | Virtual Project |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8608219/ https://www.ncbi.nlm.nih.gov/pubmed/34858105 http://dx.doi.org/10.5195/jmla.2021.1360 |
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