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A large dataset of scientific text reuse in Open-Access publications

We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications. It contains 91 million cases of reused text passages found in 4.2 million unique open-access publications. Cases range from overlap of as few as eight words to near-duplicate publicatio...

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Autores principales: Gienapp, Lukas, Kircheis, Wolfgang, Sievers, Bjarne, Stein, Benno, Potthast, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879940/
https://www.ncbi.nlm.nih.gov/pubmed/36702840
http://dx.doi.org/10.1038/s41597-022-01908-z
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author Gienapp, Lukas
Kircheis, Wolfgang
Sievers, Bjarne
Stein, Benno
Potthast, Martin
author_facet Gienapp, Lukas
Kircheis, Wolfgang
Sievers, Bjarne
Stein, Benno
Potthast, Martin
author_sort Gienapp, Lukas
collection PubMed
description We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications. It contains 91 million cases of reused text passages found in 4.2 million unique open-access publications. Cases range from overlap of as few as eight words to near-duplicate publications and include a variety of reuse types, ranging from boilerplate text to verbatim copying to quotations and paraphrases. Featuring a high coverage of scientific disciplines and varieties of reuse, as well as comprehensive metadata to contextualize each case, our dataset addresses the most salient shortcomings of previous ones on scientific writing. The Webis-STEREO-21 does not indicate if a reuse case is legitimate or not, as its focus is on the general study of text reuse in science, which is legitimate in the vast majority of cases. It allows for tackling a wide range of research questions from different scientific backgrounds, facilitating both qualitative and quantitative analysis of the phenomenon as well as a first-time grounding on the base rate of text reuse in scientific publications.
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spelling pubmed-98799402023-01-28 A large dataset of scientific text reuse in Open-Access publications Gienapp, Lukas Kircheis, Wolfgang Sievers, Bjarne Stein, Benno Potthast, Martin Sci Data Data Descriptor We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications. It contains 91 million cases of reused text passages found in 4.2 million unique open-access publications. Cases range from overlap of as few as eight words to near-duplicate publications and include a variety of reuse types, ranging from boilerplate text to verbatim copying to quotations and paraphrases. Featuring a high coverage of scientific disciplines and varieties of reuse, as well as comprehensive metadata to contextualize each case, our dataset addresses the most salient shortcomings of previous ones on scientific writing. The Webis-STEREO-21 does not indicate if a reuse case is legitimate or not, as its focus is on the general study of text reuse in science, which is legitimate in the vast majority of cases. It allows for tackling a wide range of research questions from different scientific backgrounds, facilitating both qualitative and quantitative analysis of the phenomenon as well as a first-time grounding on the base rate of text reuse in scientific publications. Nature Publishing Group UK 2023-01-26 /pmc/articles/PMC9879940/ /pubmed/36702840 http://dx.doi.org/10.1038/s41597-022-01908-z Text en © The Author(s) 2023 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
Gienapp, Lukas
Kircheis, Wolfgang
Sievers, Bjarne
Stein, Benno
Potthast, Martin
A large dataset of scientific text reuse in Open-Access publications
title A large dataset of scientific text reuse in Open-Access publications
title_full A large dataset of scientific text reuse in Open-Access publications
title_fullStr A large dataset of scientific text reuse in Open-Access publications
title_full_unstemmed A large dataset of scientific text reuse in Open-Access publications
title_short A large dataset of scientific text reuse in Open-Access publications
title_sort large dataset of scientific text reuse in open-access publications
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879940/
https://www.ncbi.nlm.nih.gov/pubmed/36702840
http://dx.doi.org/10.1038/s41597-022-01908-z
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