Skills and Knowledge for Data-Intensive Environmental Research. (3rd May 2017)

• Record Type: Journal Article
• Authors: Hampton, Stephanie E.; Jones, Matthew B.; Wasser, Leah A.; Schildhauer, Mark P.; Supp, Sarah R.; Brun, Julien; Hernandez, Rebecca R.; Boettiger, Carl; Collins, Scott L.; Gross, Louis J.; Fernández, Denny S.; Budden, Amber; White, Ethan P.; Teal, Tracy K.; Labou, Stephanie G.; Aukema, Juliann E.
• Is Part Of: BioScience. Volume 67:Number 6(2017:Jun.)
• Page Start: 546
• Page End: 557
• Publication Date: 2017-05-03
• Subjects: ecology -- informatics -- data management -- workforce development -- computing; Life sciences -- Periodicals; Life sciences -- Research -- Periodicals; Life sciences -- United States -- Periodicals; Life sciences -- Government policy -- United States -- Periodicals; Biology -- Periodicals; Biotechnology industries -- Periodicals; 570
• DOI: 10.1093/biosci/bix025
• Languages: English
• ISSNs: 0006-3568

Abstract

Abstract: The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.