Abstract
Data science is receiving increased attention in a variety of geoscience disciplines and applications. Many successful data-driven geoscience discoveries have been reported recently, and the number of geoinformatics and data science sessions at many geoscience conferences has begun to increase. Across academia, industry, and government, there is strong interest in knowing more about current progress as well as the potential of data science for geoscience. To address that need, this paper provides a review from the perspective of a data life cycle. The key steps in the data life cycle include concept, collection, preprocessing, analysis, archive, distribution, discovery, and repurpose. Those subjects are intuitive and easy to follow even for geoscientists with very limited experience with cyberinfrastructure, statistics, and machine learning. The review includes two key parts. The first addresses the fundamental concepts and theoretical foundation of data science, and the second summarizes highlights and sharable experience from existing publications centered on each step in the data life cycle. At the end, a vision about the future trends of data science applications in geoscience is provided that includes discussion of open science, smart data, and the science of team science. We hope this review will be useful to data science practitioners in the geoscience community and will lead to more discussions on the best practices and future trends of data science for the geosciences.