Seminar - Big Data Processing in Astronomy and Earth Observation: Synergies & Shared Challenges

Big (data) challenges

The challenges related to Big Data are similar for Astronomy & Earth Observation research. Both domains deal with ever-growing amounts of data and increasing complexity of data. Hence, mission and instrument teams are expected to deliver science/analysis-ready data products as it is not feasible anymore for the end-users to handle the pre-processing themselves.

Another effect of the increased data volumes and complexity is the migration of scientific workflows from desktops to Virtual Research Environments or HPC clusters. New AI algorithms and other optimizations are needed to plough through the huge datasets. And how is Big Data managed and shared in the context of the Open Science revolution? 

In this seminar, we bring together two research communities with similar challenges, and learn how innovative Big Data projects in Astronomy and Earth Observation deal with:

• data processing and analysis: how to get from raw data to science/analysis-ready data products and scientific workflows?
• data storage and management: how to manage distributed and heterogenous datasets and storage systems following Open Science and FAIR principles?
• emerging technologies: how to use AI, Quantum Computing, HPC, exascale computing to tackle Big Data challenges?

In addition to presentations, the seminar will include interactive breakout sessions  to stimulate interdisciplinary knowledge exchange and creative conversations.

Preliminary programme

Chair: Haili Hu (SURF)

Organisation Committee

• Haili Hu (SURF)
• Raymond Oonk (SURF)
• Irene Bonati (SURF)
• Jolien Diekema (NSO)
• Raymond Sluiter (NSO)