Modern science is interdisciplinary and data-intensive. For instance, in the 1000 Genomes Project (www.1000genomes.org), the comparative study of 629 individuals has already generated 7.3 TB of data. Analogous situations exist in fields such as astronomy, agriculture, social sciences, etc. Ten years ago, the problem was how to obtain data. Today, the bottleneck is the need for new computational strategies and tools so that scientists can manage these massive volumes of heterogeneous, distributed, data, so that they can generate new knowledge from the processing, analysis and visualization of the data. This launched the basis of the so-called eScience: the combination of advanced research in computer science and mathematical modeling to allow and accelerate research in other knowledge domains.