Tackling the Challenges of 21st-Century Open Science and Beyond: A Data Science Lab Approach
Author(s) -
Michael Hollaway,
Graham Dean,
Gordon S. Blair,
Mike Brown,
Peter A. Henrys,
John Watkins
Publication year - 2020
Publication title -
patterns
Language(s) - English
Resource type - Journals
ISSN - 2666-3899
DOI - 10.1016/j.patter.2020.100103
Subject(s) - open science , big data , e science , data science , citizen science , dissemination , discipline , space science , grand challenges , set (abstract data type) , space (punctuation) , engineering ethics , computer science , science policy , open data , political science , sociology , engineering , world wide web , social science , geography , telecommunications , geodesy , public administration , astronomy , aerospace engineering , biology , programming language , grid , operating system , physics , botany
Summary In recent years, there has been a drive toward more open, cross-disciplinary science taking center stage. This has presented a number of challenges, including providing research platforms for collaborating scientists to explore big data, develop methods, and disseminate their results to stakeholders and decision makers. We present our vision of a “data science lab” as a collaborative space where scientists (from different disciplines), stakeholders, and policy makers can create data-driven solutions to environmental science's grand challenges. We set out a clear and defined research roadmap to serve as a focal point for an international research community progressing toward a more data-driven and transparent approach to environmental data science, centered on data science labs. This includes ongoing case studies of good practice, with the infrastructural and methodological developments required to enable data science labs to support significant increase in our cross- and trans-disciplinary science capabilities.
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