A procedure to import seismological data into the Ophidia big data analytics framework

Abstract

The term Big Data identifies large data sets that cannot be managed with traditional processing software. Volume, Variety and Velocity are properties used to classify Big Data. Velocity, the most relevant property, refers to high speed of data acquisition and processing. Management of Big Data, and particularly Velocity, has become an open issue for scientific communities. The EC project INDIGO-Datacloud was conceived to tackle some of the Big Data challenges that scientific communities are facing. In the context of INDIGO-Datacloud we defined a case study in which one of the goals was the improvement of processing performance on seismological data. Starting with a practical case study, we identified, as possible software solution, Ophidia, a big data analytics framework. The first step to exploit the framework functionalities required the import of the seismological data in Ophidia. For this purpose, we designed and implemented a software module that enables the import of seismological data in SAC format. As a second step, we tested the capabilities of Ophidia through a performance test to evaluate the framework potential.