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ASTRO Journals’ Data Sharing Policy and Recommended Best Practices

Transparency, openness, and reproducibility are important characteristics in scientific publishing. Although many researchers embrace these characteristics, data sharing has yet to become common practice. Nevertheless, data sharing is becoming an increasingly important topic among societies, publish...

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Detalles Bibliográficos
Autores principales: Tegbaru, Dawit, Braverman, Lisa, Zietman, Anthony L., Yom, Sue S., Lee, W. Robert, Miller, Robert C., Jackson, Isabel L., McNutt, Todd, Dekker, Andre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817515/
https://www.ncbi.nlm.nih.gov/pubmed/31673648
http://dx.doi.org/10.1016/j.adro.2019.08.002
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author Tegbaru, Dawit
Braverman, Lisa
Zietman, Anthony L.
Yom, Sue S.
Lee, W. Robert
Miller, Robert C.
Jackson, Isabel L.
McNutt, Todd
Dekker, Andre
author_facet Tegbaru, Dawit
Braverman, Lisa
Zietman, Anthony L.
Yom, Sue S.
Lee, W. Robert
Miller, Robert C.
Jackson, Isabel L.
McNutt, Todd
Dekker, Andre
author_sort Tegbaru, Dawit
collection PubMed
description Transparency, openness, and reproducibility are important characteristics in scientific publishing. Although many researchers embrace these characteristics, data sharing has yet to become common practice. Nevertheless, data sharing is becoming an increasingly important topic among societies, publishers, researchers, patient advocates, and funders, especially as it pertains to data from clinical trials. In response, ASTRO developed a data policy and guide to best practices for authors submitting to its journals. ASTRO's data sharing policy is that authors should indicate, in data availability statements, if the data are being shared and if so, how the data may be accessed.
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spelling pubmed-68175152019-10-31 ASTRO Journals’ Data Sharing Policy and Recommended Best Practices Tegbaru, Dawit Braverman, Lisa Zietman, Anthony L. Yom, Sue S. Lee, W. Robert Miller, Robert C. Jackson, Isabel L. McNutt, Todd Dekker, Andre Adv Radiat Oncol Special Collection: Advancing Radiation Oncology Practice Through Clinical Application of Data Science Transparency, openness, and reproducibility are important characteristics in scientific publishing. Although many researchers embrace these characteristics, data sharing has yet to become common practice. Nevertheless, data sharing is becoming an increasingly important topic among societies, publishers, researchers, patient advocates, and funders, especially as it pertains to data from clinical trials. In response, ASTRO developed a data policy and guide to best practices for authors submitting to its journals. ASTRO's data sharing policy is that authors should indicate, in data availability statements, if the data are being shared and if so, how the data may be accessed. Elsevier 2019-08-22 /pmc/articles/PMC6817515/ /pubmed/31673648 http://dx.doi.org/10.1016/j.adro.2019.08.002 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Special Collection: Advancing Radiation Oncology Practice Through Clinical Application of Data Science
Tegbaru, Dawit
Braverman, Lisa
Zietman, Anthony L.
Yom, Sue S.
Lee, W. Robert
Miller, Robert C.
Jackson, Isabel L.
McNutt, Todd
Dekker, Andre
ASTRO Journals’ Data Sharing Policy and Recommended Best Practices
title ASTRO Journals’ Data Sharing Policy and Recommended Best Practices
title_full ASTRO Journals’ Data Sharing Policy and Recommended Best Practices
title_fullStr ASTRO Journals’ Data Sharing Policy and Recommended Best Practices
title_full_unstemmed ASTRO Journals’ Data Sharing Policy and Recommended Best Practices
title_short ASTRO Journals’ Data Sharing Policy and Recommended Best Practices
title_sort astro journals’ data sharing policy and recommended best practices
topic Special Collection: Advancing Radiation Oncology Practice Through Clinical Application of Data Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817515/
https://www.ncbi.nlm.nih.gov/pubmed/31673648
http://dx.doi.org/10.1016/j.adro.2019.08.002
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