Title :
A Guide to Earth Science Data: Summary and Research Challenges
Author :
Karpatne, Anuj ; Liess, Stefan
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.
Keywords :
Big Data; data analysis; geophysics computing; Earth science data; big data analytics research; data-centric approaches; Atmospheric modeling; Data models; Meteorology; Ocean temperature; Remote sensing; Sea surface; Earth science data; climate data; scientific computing;
Journal_Title :
Computing in Science Engineering
DOI :
10.1109/MCSE.2015.127