Data-Intensive architecture for scientific knowledge discovery

This paper presents a data-intensive architecture that demonstrates the ability to support applications from a wide range of application domains, and support the different types of users involved in defining, designing and executing data-intensive processing tasks. The prototype architecture is introduced, and the pivotal role of DISPEL as a canonical language is explained. The architecture promotes the exploration and exploitation of distributed and heterogeneous data and spans the complete knowledge discovery process, from data preparation, to analysis, to evaluation and reiteration. The architecture evaluation included large-scale applications from astronomy, cosmology, hydrology, functional genetics, imaging processing and seismology.

Study of seismic vulnerability and the damage seen in the town of Lorca after the earthquake of 2011.

Análisis de los factores de vulnerabilidad que mas influencia han tenido en el daño del terremoto de Lorca.

Analysis of urban parameters in the characterization of seismic vulnerability: application to the city of Lorca.

Estimación de la intensidad tras el terremoto de Lorca.