What will the future of cloud-based astronomical data processing look like?

Andrew W. Green, Elizabeth Mannering, Lloyd Harischandra, Minh Vuong, Simon O'Toole, Katrina Sealey, Andrew M. Hopkins

Research output: Contribution to journalArticlepeer-review


Astronomy is rapidly approaching an impasse: very large datasets require remote or cloud-based parallel processing, yet many astronomers still try to download the data and develop serial code locally. Astronomers understand the need for change, but the hurdles remain high. We are developing a data archive designed from the ground up to simplify and encourage cloud-based parallel processing. While the volume of data we host remains modest by some standards, it is still large enough that download and processing times are measured in days and even weeks. We plan to implement a python based, notebook-like interface that automatically parallelises execution. Our goal is to provide an interface sufficiently familiar and user-friendly that it encourages the astronomer to run their analysis on our system in the cloud - astroinformatics as a service. We describe how our system addresses the approaching impasse in astronomy using the SAMI Galaxy Survey as an example.

Original languageEnglish
Pages (from-to)27-31
Number of pages5
JournalProceedings of the International Astronomical Union
Issue numberS325
Publication statusPublished - 2016
Externally publishedYes


  • astronomical data bases: miscellaneous
  • methods: data analysis


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