Abstract
Recent growth in the scale and variety of Earth science data has provided unprecedented opportunities to big data analytics research for understanding the Earth's physical processes. An upsurge of Earth science datasets in the past few decades are being continually collected using various modes of acquisition, at different scales of observation, and in diverse data types and formats. Earth science datasets, however, exhibit some unique characteristics (such as adherence to physical properties and spatiotemporal constraints) that present challenges to traditional data-centric approaches. In this article, the authors briefly introduce the different categories of Earth science datasets and further describe some of the major data-centric challenges in analyzing Earth science data.
Original language | English (US) |
---|---|
Article number | 7310923 |
Pages (from-to) | 14-18 |
Number of pages | 5 |
Journal | Computing in Science and Engineering |
Volume | 17 |
Issue number | 6 |
DOIs | |
State | Published - Nov 1 2015 |
Bibliographical note
Publisher Copyright:© 1999-2011 IEEE.
Keywords
- Earth science data
- Scientific computing
- climate data