Edinburgh Data-Intensive Research

The presentation was given to the 41st Workshop of the International School of Geophysics, Erice, Italy, "A Roadmap for Earth Science in Europe: The next generation of Geophysical Research Infrastructures". The meeting was organised by EPOS, ORFEUS, COOPEUS and NERA. I was supposed to talk about massive data processing strategies, but as you will see, I saw that many other frequently occurring impediments to success with data were more dominant, so I tried to draw attention to these issues.

Molecular simulations are indispensable methods in areas like material science, structural biology, and drug design. These methods address data-intensive and compute-intensive problems, which demand high-performance computing to allow data analysis in an acceptable time. The project MoSGrid (Molecular Simulation Grid) offers a workflow-enabled grid portal allowing access to molecular simulation tools on distributed resources in an intuitive manner. Users are able to exchange workflows and data via repositories and, thus, to exchange knowledge about the specific application domain.

Typical of the digital revolution, seismology is changing rapidly: the number of deployed seismometers grows rapidly, their performance and connectivity improve and seismologists employ data from other sources, such as LIDAR, satellite images and GPS. But their computational behavior is also changing: they used to just focus on earthquakes, today the use all of the continuous waveform. Just what does this mean for the science and the computational infrastructure to support it? The VERCE project is pioneering this approach and will provide examples during the talk.