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Crowdsourcing Citizen Science Data Quality with a Human-Computer Learning Network

Presentation at the Human Computation for Science and Computational Sustainability workshop at NIPS 2012 in Lake Tahoe, NV.

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Crowdsourcing Citizen Science
       Data Quality with a
Human-Computer Learning Network
      Wiggins, Gerbracht, Lagoze,Yu, Wong, & Kelling


                  7 December, 2012 ~ Lake Tahoe, NV
Workshop on Human Computation for Science and Computational Sustainability
Crowdsourcing Scientific Work
eBird
• Online checklist
  program for bird
  abundance &
  distribution
• Data (mostly)
  from recreational
  birders; used
  widely
• Over 100 million
  records & growing      eBird observations per month
Data Quality




Dogbird                  Catbird
Data Quality




X
Dogbird                  Catbird
The eBird HCLN




S Kelling, C Lagoze, W-K Wong, J Yu, T Damoulas, J Gerbracht, D Fink, C Gomes. 2012. eBird: A Human/Computer Learning
                     Network to Improve Biodiversity Conservation and Research. Artificial Intelligence.

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Crowdsourcing Citizen Science Data Quality with a Human-Computer Learning Network

  • 1. Crowdsourcing Citizen Science Data Quality with a Human-Computer Learning Network Wiggins, Gerbracht, Lagoze,Yu, Wong, & Kelling 7 December, 2012 ~ Lake Tahoe, NV Workshop on Human Computation for Science and Computational Sustainability
  • 3. eBird • Online checklist program for bird abundance & distribution • Data (mostly) from recreational birders; used widely • Over 100 million records & growing eBird observations per month
  • 6. The eBird HCLN S Kelling, C Lagoze, W-K Wong, J Yu, T Damoulas, J Gerbracht, D Fink, C Gomes. 2012. eBird: A Human/Computer Learning Network to Improve Biodiversity Conservation and Research. Artificial Intelligence.
  • 7. Emergent Filters Kelling, S., J.Yu, J. Gerbracht, and W. K. Wong. 2011. Emergent Filters: Automated Data Verification in a Large-scale Citizen Science Project. Proceedings of the IEEE eScience Conference.
  • 8. Modeling Expertise Environmental Occupancy Detection Covariates (Latent) Detection Covariates oi dit Xi$ Zi$ Yit$ Wit$ t=1,…,Ti$ i=1,…,N$
  • 9. Occupancy-Detection-Expertise Expertise Expertise Covariates vj Uj Ej j=1,…,M oi dit, fit Xi Zi Yit Wit$ t=1,…,Ti i=1,…,N
  • 10. Average Detection Probabilities 0.20 0.15 0.10 0.05 0.00 h o w n er al y h tc re o Ja s lo in h ru er ha Vi as -0.05 al rd ue Th H r ut Sw Ca d Th Bl e N de d lu oo n ed n ea d B er ow te W g -h at th as in Br ue re or re w G Bl N h- -b ug te hi Ro W n er th or N Common birds Hard-to-detect birds Yu, J., W. K. Wong, and R. A. Hutchinson. 2010. Modeling Experts and Novices in Citizen Science Data for Species Distribution Modeling. IEEE 10th International Conference on Data Mining (ICDM),
  • 11. Emergent Filters + Expertise Spizella passerina
  • 12. Emergent Filters + Expertise Spizella 50" 45" passerina 40" 35" 30" 25" 20" 15" 10" 5" 0" 8)Jan" 8)Feb"8)Mar" 8)Apr" 8)May" 8)Jun" 8)Jul" 8)Aug" 8)Sep" 8)Oct" 8)Nov" 8)Dec"
  • 13. Emergent Filters + Expertise Spizella 50" 45" passerina 40" 35" 30" 25" 20" 15" 10" 5" 0" 8)Jan" 8)Feb"8)Mar" 8)Apr" 8)May" 8)Jun" 8)Jul" 8)Aug" 8)Sep" 8)Oct" 8)Nov" 8)Dec" 50" 45" 40" 35" 30" 25" 20" 15" 10" 5" 0" 8)Jan" 8)Feb"8)Mar" 8)Apr"8)May" 8)Jun" 8)Jul" 8)Aug" 8)Sep" 8)Oct" 8)Nov" 8)Dec"
  • 14. Emergent Filters + Expertise Spizella 50" 45" passerina 40" 35" 30" 25" 20" 15" 10" 5" 0" 8)Jan" 8)Feb"8)Mar" 8)Apr" 8)May" 8)Jun" 8)Jul" 8)Aug" 8)Sep" 8)Oct" 8)Nov" 8)Dec" 50" 50" 45" 45" 40" 40" 35" 35" 30" 30" 25" 25" 20" 20" 15" 15" 10" 10" 5" 5" 0" 0" 8)Jan" 8)Feb"8)Mar" 8)Apr"8)May" 8)Jun" 8)Jul" 8)Aug" 8)Sep" 8)Oct" 8)Nov" 8)Dec" 1(Jan" 1(Feb"1(Mar" 1(Apr"1(May" 1(Jun" 1(Jul" 1(Aug" 1(Sep" 1(Oct" 1(Nov"1(Dec"
  • 15. Improving Spatial Coverage Locations in NY with eBird submissions in 2009
  • 16. Improving Spatial Coverage Areas with enough data for emergent filters
  • 17. Future Work • Preliminary studies integrated into eBird for better data quality on multiple levels • Resulting human-computer learning network will use eBird data in new ways • Evaluation of motivation, learning, and skills related to expertise ranking & birding routes
  • 18. Thanks! www.ebird.org @AndreaWiggins andrea.wiggins@cornell.edu www.andreawiggins.com Acknowledgements • Leon Levy Foundation • Wolf Creek Foundation • National Science Foundation Grants OCI-0830944, CCF-0832782, ITR-0427914, DBI-1049363, DBI-0542868, DUE-0734857, IIS-0748626, IIS-0844546, IIS-0612031, IIS-1050422, IIS-0905385, IIS-0746500, IIS-1209589, AGS-0835821, CNS-0751152, CNS-0855167.