Our path to better science in less time using open data science tools : Nature Ecology & Evolution
lterrat's bookmarks 2017-05-24
Summary:
"Reproducibility has long been a tenet of science but has been challenging to achieve—we learned this the hard way when our old approaches proved inadequate to efficiently reproduce our own work. Here we describe how several free software tools have fundamentally upgraded our approach to collaborative research, making our entire workflow more transparent and streamlined. By describing specific tools and how we incrementally began using them for the Ocean Health Index project, we hope to encourage others in the scientific community to do the same—so we can all produce better science in less time.
Science, now more than ever, demands reproducibility, collaboration and effective communication to strengthen public trust and effectively inform policy. Recent high-profile difficulties in reproducing and repeating scientific studies have put the spotlight on psychology and cancer biology1,2,3, but it is widely acknowledged that reproducibility challenges persist across scientific disciplines4,5,6. Environmental scientists face potentially unique challenges in achieving goals of transparency and reproducibility because they rely on vast amounts of data spanning natural, economic and social sciences that create semantic and synthesis issues exceeding those for most other disciplines7,8,9. Furthermore, proposed environmental solutions can be complex, controversial and resource intensive, increasing the need for scientists to work transparently and efficiently with data to foster understanding and trust."