Upgrade to Pro — share decks privately, control downloads, hide ads and more …

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
Tweet

More Decks by Juande Santander-Vela

Other Decks in Science

Transcript

  1. Citizen Science in the era of
    the Square Kilometre Array
    Juande Santander-Vela
    SKA Organisation

    View Slide

  2. Golden era of astronomy

    View Slide

  3. View Slide

  4. View Slide

  5. View Slide

  6. View Slide

  7. View Slide

  8. View Slide

  9. Possible through ICT innovation

    View Slide

  10. Possible through ICT innovation

    View Slide

  11. Possible through ICT innovation

    View Slide

  12. Possible through ICT innovation

    View Slide

  13. Possible through ICT innovation

    View Slide

  14. Same ICT innovation for companies
    and consumers

    View Slide

  15. #1 ICT innovation: broadband

    View Slide

  16. View Slide

  17. View Slide

  18. View Slide

  19. View Slide

  20. View Slide

  21. Digital data is easy to
    access from everywhere

    View Slide

  22. Digital data access is
    blind to who you are

    View Slide

  23. Digital data access is
    (mostly) blind to who you are

    View Slide

  24. Golden era of astronomy

    View Slide

  25. Golden era of amateur astronomy

    View Slide

  26. http://aladin.u-strasbg.fr/

    View Slide

  27. View Slide

  28. View Slide

  29. View Slide

  30. View Slide

  31. View Slide

  32. View Slide

  33. How is this possible?

    View Slide

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

    View Slide

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

    View Slide

  36. Hanny’s
    Voorwerp
    https://www.galaxyzoo.org/

    View Slide

  37. Hanny’s
    Voorwerp
    https://www.galaxyzoo.org/

    View Slide

  38. View Slide

  39. View Slide

  40. Citizen Science is science done by
    many citizens, looking at
    real scientific data

    View Slide

  41. Citizen Science ⟷ Crowdsourced
    Data Science

    View Slide

  42. 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…

    View Slide

  43. Citizen Science ⟷ Cloud Science

    View Slide

  44. 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?

    View Slide

  45. But this is the challenge we’re facing!

    View Slide

  46. ALMA

    View Slide

  47. ALMA

    View Slide

  48. ALMA SKA1

    View Slide

  49. ALMA SKA1

    View Slide

  50. View Slide

  51. View Slide

  52. 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

    View Slide

  53. 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


    View Slide

  54. 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
    ‘ !
    ‘ !

    View Slide

  55. Working on it!

    View Slide

  56. 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!

    View Slide

  57. 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!

    View Slide

  58. 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!

    View Slide

  59. View Slide

  60. ¿Questions?

    View Slide

  61. 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…

    View Slide