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dc.contributor.authorToelch, Ulf
dc.contributor.authorOstwald, Dirk
dc.date.accessioned2021-12-16T17:22:53Z
dc.date.available2021-12-16T17:22:53Z
dc.date.issued2018-07-26
dc.identifier.citation"Toelch U, Ostwald D (2018) Digital open science—Teaching digital tools for reproducible and transparent research. PLoS Biol 16(7): e2006022. https://doi.org/10.1371/journal. pbio.2006022 "es_MX
dc.identifier.issn1544-9173
dc.identifier.urihttps://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2006022
dc.identifier.urihttp://angola.redalyc.org//handle/123456789/21
dc.descriptionThe scientific process from idea to publication is complex and seldomly reflected in full in tra ditional research articles . As of 2015, only 13% of research articles include raw data , and even fewer include data analysis code .es_MX
dc.description.abstractAn important hallmark of science is the transparency and reproducibility of scientific results. Over the last few years, internet-based technologies have emerged that allow for a repre sentation of the scientific process that goes far beyond traditional methods and analysis descriptions. Using these often freely available tools requires a suite of skills that is not nec essarily part of a curriculum in the life sciences. However, funders, journals, and policy mak ers increasingly require researchers to ensure complete reproducibility of their methods and analyses. To close this gap, we designed an introductory course that guides students towards a reproducible science workflow. Here, we outline the course content and possible extensions, report encountered challenges, and discuss how to integrate such a course in existing curricula.es_MX
dc.language.isoenes_MX
dc.publisherPLoS Bioles_MX
dc.titleDigital open science—Teaching digital tools for reproducible and transparent researches_MX
dc.typeArticlees_MX


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