Integration and massive storage of hydro-meteorological data combining big data & semantic web technologies

Abstract

Ecuador contains an immense collection of hydro-meteorological data, informing us via standards how to locate and invoke them. If we want to make such data easier to understand and use, we need to store them in a common repository and annotate them by means of descriptive metadata. This paper proposes an approach for the massive storage, integration and semantic annotation of hydro-meteorological data using an open source integration container, NoSQL databases and Semantic Web technologies. The main contributions of this paper are: i) a shared common repository of hydro-meteorological data, ii) automatic semantic annotation to formally describe the data sources, and iii) efficient mechanisms for searching and retrieving hydro meteorological data.