title: Recommendations for open data science.
abstract: Life science research increasingly relies on large-scale computational analyses. However, the code and data used for these analyses are often lacking in publications. To maximize scientific impact, reproducibility, and reuse, it is crucial that these resources are made publicly available and are fully transparent. We provide recommendations for improving the openness of data-driven studies in life sciences.
authors.affiliation: Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA USA ; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA USA.
authors.forename: Melissa
authors.initials: M
authors.lastname: Gymrek
authors.affiliation: Data Science and Data Engineering, Broad Institute of MIT and Harvard, Cambridge, MA USA.
authors.forename: Yossi
authors.initials: Y
authors.lastname: Farjoun
mesh_terms: D001690:Biological Science Disciplines; D019295:Computational Biology / Q000379:methods; D017408:Guidelines as Topic; D006801:Humans; D033181:Information Dissemination; D066295:Open Access Publishing; D015203:Reproducibility of Results
keywords: Best practices; Open science; Reproducible research