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Towards adopting open and data-driven science practices in bed form dynamics research,and some steps to this end
Authors:Ronald R Gutierrez  Alice Lefebvre  Francisco Núñez-González  Humberto Avila
Institution:1. IDEHA, Universidad del Norte, Barranquilla, 500001 Colombia;2. MARUM, University of Bremen, Bremen, 28359 Germany;3. Leichtweiß-Institut für Wasserbau, University of Braunschweig, Braunschweig, 38106 Germany
Abstract:In recent years, open and data-driven science has fostered very important scientific breakthroughs. This study describes the challenges and opportunities for the scientific community devoted to bed form dynamics research in adopting such scientific paradigms through, for example, engineered data sharing, formal recognition of scientists who collect the data, and collaborative development of free accessible software. It highlights that once these actions are completed, the potential application of deep learning techniques could substantially improve bed form models and the scientific understanding of bed form dynamics. Likewise, it discusses the potential of Bedforms-ATM, a free available software, to standardize some bed form data analysis techniques. We propose that the technical challenges be tackled by following scholarly accepted/proposed standards (e.g. FAIR Guiding Principles, Geoscience Papers of the Future), using the body of knowledge being built on the matter by some institutions (e.g. Federation of Earth Science Information Partners), and through technical discussions at scientific meetings such as MARID. © 2020 John Wiley & Sons, Ltd.
Keywords:bed forms  open science  data-driven science  deep learning  scientific software
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