Transcription Hackathon

Notes from Nature/iDigBio Hackathon to Further Enable Public Participation in the Online Transcription of Biodiversity Specimen Labels

December 16–20 at the University of Florida, Gainesville

Agenda and Logistics

• Hackathon Advertisement
• Tentative Agenda
• Logistics Document
• Participants List
• AdobeConnect room for planning prior to the hackathon, then for connection to the workshop remotely (Send an email to Austin Mast, if you'd like to use the room for planning prior to the hackathon.)

Coordination

• Interoperability Track
• OCR Integration Track
• QA/QA and Reconciliation of Replicates Track
• User Engagement Track

Development Resources

• Existing crowdsourcing datasets from Notes From Nature: datasets with transcriptions of different types of collections labels:
  • [1] Herbarium labels—The filenames with "USAM_" represent a nearly complete set of recent transcriptions from a collection (the University of South Alabama Herbarium), four replicates for most specimens (I think).
  • [2] Entomology labels
  • [3] Field notebooks
  • [4] Macrofungi labels

• Existing solution datasets to assess quality of crowdsourcing consensus:
  • Herbarium labels ideal response: link to be provided by Austin
  • Entomology labels ideal response: link to be provided by Austin
  • Field notebooks ideal response: link to be provided by Austin

• Notes From Nature web interface:
  • Code available at https://github.com/zooniverse/notesFromNature
  • Forked version for the Hackathon available at: https://github.com/idigbio-citsci-hackathon/notesFromNature
  • Vagrant script to build a VM with Notes From Nature web interface: link to be provided by Alex
  • Install Vagrant from http://downloads.vagrantup.com/tags/v1.3.5 and virtualBox from https://www.virtualbox.org/wiki/Downloads

• CYWG iDigBio Image Ingestion Appliance:
  • The appliance can be used to ingest the images to be used by the crowdsourcing service into the iDigBio storage, and made publicly accessible through HTTP. The relationship between the image filenames and the URL can be exported by the appliance in CSV format.

• Code from the aOCR Hackthon:
  • HandwritingDetection (https://github.com/idigbio-aocr): an algorithm that separates images into sets with no handwriting, little handwriting (mostly text typed or printed), lots of handwriting, based on the noise generated by the OCR software. Read more at Ben's blog. This could be used to rank which images are in more need for human transcription.
  • Dictionaries to improve crowdsourcing consensus (e.g., names of collectors, scientific names): link to be provided by aOCR?
    • (Some botantists: RDF and tab-delimited.)