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Good enough practices in scientific computing.
Wilson, Greg; Bryan, Jennifer; Cranston, Karen; Kitzes, Justin; Nederbragt, Lex; Teal, Tracy K.
Afiliação
  • Wilson G; Software Carpentry Foundation, Austin, Texas, United States of America.
  • Bryan J; RStudio and Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada.
  • Cranston K; Department of Biology, Duke University, Durham, North Carolina, United States of America.
  • Kitzes J; Energy and Resources Group, University of California, Berkeley, Berkeley, California, United States of America.
  • Nederbragt L; Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway.
  • Teal TK; Data Carpentry, Davis, California, United States of America.
PLoS Comput Biol ; 13(6): e1005510, 2017 Jun.
Article em En | MEDLINE | ID: mdl-28640806
ABSTRACT
Computers are now essential in all branches of science, but most researchers are never taught the equivalent of basic lab skills for research computing. As a result, data can get lost, analyses can take much longer than necessary, and researchers are limited in how effectively they can work with software and data. Computing workflows need to follow the same practices as lab projects and notebooks, with organized data, documented steps, and the project structured for reproducibility, but researchers new to computing often don't know where to start. This paper presents a set of good computing practices that every researcher can adopt, regardless of their current level of computational skill. These practices, which encompass data management, programming, collaborating with colleagues, organizing projects, tracking work, and writing manuscripts, are drawn from a wide variety of published sources from our daily lives and from our work with volunteer organizations that have delivered workshops to over 11,000 people since 2010.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa / Ciência / Software / Segurança Computacional / Metodologias Computacionais / Confiabilidade dos Dados Tipo de estudo: Guideline Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa / Ciência / Software / Segurança Computacional / Metodologias Computacionais / Confiabilidade dos Dados Tipo de estudo: Guideline Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos