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Citizen Science in the era of the Square Kilometre Array

Citizen Science in the era of the Square Kilometre Array

Talk given as part of the Bluedot Festival. Tries to emphasise the current trends in Citizen Science, how are they powered by the same ICT innovation that powers other industries, and how curation and metadata are key both for professional and citizen scientist, and facilities to perform that will be needed.

Juande Santander-Vela

July 24, 2016
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Transcript

  1. Citizen Science in the era of the Square Kilometre Array

    Juande Santander-Vela SKA Organisation
  2. How is this possible? • Analog → Digital Data •

    Common Data Formats • Anonymous Access • Lots of scientific Meta-Data
  3. How is this possible? • Analog → Digital Data •

    Common Data Formats • Anonymous Access • Lots of scientific Meta-Data Hidden treasures!
  4. Citizen Science ⟷ Crowdsourced Data Science • Data (and metadata!)

    needs to be very well curated/mantained/ tagged so that both the existing data exposed to citizens, and the data provided by them, can be meaningfully linked together. → Spatial: Telescope Centric (Az/Alt), Earth centric (RA/Dec, FK4, FK5, ICRS), Solar centric (Ecliptic), Galactic centric (Galactic coordinates), Super galactic… → Temporal: UTC, TAI, Julian date, HA… and cosmology times/ distances! → Observable: Polarisation, Flux…
  5. Citizen Science ⟷ Cloud Science • The only way to

    gather everyone is in the cloud • Working on local copies is hard → remote tools allow for easier integration of contributions • Do you have the tool? • Do you know there the data is? • Do I have permission to change this?
  6. What tools can we use to… • Visualise those datasets?

    → Remote vs Local visualisation and interaction • Process those datasets for additional science → Remote vs Local processing
  7. What tools can we use to… • Visualise those datasets?

    → Remote vs Local visualisation and interaction • Process those datasets for additional science → Remote vs Local processing ‘ ‘
  8. What tools can we use to… • Visualise those datasets?

    → Remote vs Local visualisation and interaction • Process those datasets for additional science → Remote vs Local processing ‘ ! ‘ !
  9. Conclusions • Citizen Science is enabled by ICT… and so

    is science for new large research facilities • Challenges for Citizen Science are challenges for normal science in the SKA era • Citizen Science makes some new science possible ⟷ Asynchronous Pro/Amateur collaboration • Techniques are multi-disciplinary, not just for astronomy!
  10. Conclusions • Citizen Science is enabled by ICT… and so

    is science for new large research facilities • Challenges for Citizen Science are challenges for normal science in the SKA era → we need to sort it out! • Citizen Science makes some new science possible ⟷ Asynchronous Pro/Amateur collaboration • Techniques are multi-disciplinary, not just for astronomy!
  11. Conclusions • Citizen Science is enabled by ICT… and so

    is science for new large research facilities • Challenges for Citizen Science are challenges for normal science in the SKA era → we need to sort it out! • Citizen Science makes some new science possible ⟷ Asynchronous Pro/Amateur collaboration → more people looking in the haystack! • Techniques are multi-disciplinary, not just for astronomy!
  12. We have not spoken about… • Digital literacy ⟷ Coding

    • Open Data ⟷ Virtual Observatory :: Social Siences ⟷ Astronomy • Metadata and Curation • Citizen Science-like Infrastructures: e-Government, Integrated Healthcare…