Advanced Technologies and Data Management Practices in Environmental Science: Lessons from Academia

Abstract

W ith the advent of recent technological and computational advances, scientists are using increasing numbers of in situ environmental sensors, model simulations, crowdsourcing tasks, and embedded networked systems that enable environmental studies to incorporate various spatiotemporal scales and to produce unprecedented amounts of data Such technologies and an increasing interest in synthesis studies of environmental phenomena have made data valuable beyond their immediate use The flood of data that digital technologies produce (Hey and Trefethen 2003) underscores the urgency of a rapid adoption of pertinent skills and best practices by environmental scientists in the proper management of data sets. Studies in which such preparedness in the environmental sciences is evaluated are absent; however, academic institutions may play a role in imparting the relevant knowledge and skills to the next generation of scientists.