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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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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. |
format | Online Article Text |
id | pubmed-6817515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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