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

January 23 @ 10:00 am - 5:00 pm

Do you engage with Big Data in your research in Astronomy or Earth Observation? Or do you want to learn about innovative projects in these domains with a strong data processing component? Then join this seminar, organised by SURF and NSO, bringing together the Astronomy and Earth Observation communities to discuss shared challenges and best practices.

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?

Innovative projects and inspiring speakers

Organisation Committee

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

For whom

Researchers, IT support and Project Managers that are active in Astronomy or Earth Observation.


SURF Utrecht
Moreelsepark 48
Utrecht, 3511 EP Netherlands
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