AMIGA : Technological developments

Since AMIGA started (2003), fundamental science has been complemented with applied e-Science research aiming to support astronomers to cope with the

Since AMIGA started (2003), fundamental science has been complemented with applied e-Science research aiming to support astronomers to cope with the data and computational complexity while doing reproducible science, as a way to compete at the highest level in the scientific exploitation of the data deluge from instruments like the SKA. E.g. SKA1 follow-up of the science described in AMIGA6 will produce final data products of ~300GB in a 12h observing run. Hence, VO standards for radioastronomy cubes, workflows for their analysis, and a more efficient exploitation of the currently available computational and storage infrastrucuture are needed. Within AMIGA team a significant effort is being performed in this direction within the following front lines: Reproducible Science. Participation in the SKA Science Data Processor consortium. Contribution to the Virtual Observatory: standards and tools. Optimization the use of Distributed Computing Infrastructures
 

Technological developments

Since AMIGA started (2003), fundamental science has been complemented with applied e-Science research aiming to support astronomers to cope with the data and computational complexity while doing reproducible science, as a way to compete at the highest level in the scientific exploitation of the data deluge from instruments like the SKA.

E.g. SKA1 follow-up of the science described in AMIGA6 will produce final data products of ~300GB in a 12h observing run. Hence, VO standards for radioastronomy cubes, workflows for their analysis, and a more efficient exploitation of the currently available computational and storage infrastrucuture are needed. Within AMIGA team a significant effort is being performed in this direction within the following front lines:

  • Reproducible Science.
  • Participation in the SKA Science Data Processor consortium.
  • Contribution to the Virtual Observatory:  standards and tools.
  • Optimization the use of Distributed Computing Infrastructures