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Cornell Lab of Ornithology


Refine Protocols: How-to's


Keep objectives in mind and...

  • use proper study design to meet scientific objectives
  • understand and account for potential biases of research design
  • ensure study design also facilitates other objectives (e.g., educational)
  • develop a clearly written protocol


Be aware of volunteer abilities/interests,

  • choose protocols within capacity of volunteers (be realistic)
    • is the project overly ambitious (too tedious or complex)?
    • is it underestimating volunteer skills (not interesting/challenging)?
  • keep protocols transparent (observers should know why they're being asked to do things a certain way)
  • plan for reasonable equipment intensity (cost, maintenance, usability)


Pilot test data forms that facilitate...

  • users filling in all fields
  • geo-referencing data
  • temporally referencing data
  • collection of negative data
  • identification of observer for each data point
  • early identification of "outliers"
    • allows differentiation of typos from unusual sightings
    • provides an opportunity to request confirmation

Plan ahead for usable data,

  • choose protocols within capacity of volunteers
  • ensure the protocols are clearly written and accessible to all participants
  • build ID guides and data confirmation steps into data collection tools
  • consult with a statistician and:
    • determine the necessary sample size for your study
    • determine the necessary number of study sites
    • address the potential for sampling bias
  • decide up front how to handle questionable data
  • pilot test all stages of project development


Make smart use of technology,

  • minimize errors by making data collection electronic at the earliest stage
  • but, consider that a pencil and paper datasheet can be sufficient
  • identify particular needs of different users/clients (scientists, volunteers, etc.)
  • provide different data forms for different audiences that collect the same data (e.g., paper and electronic)
  • assess appropriate technology options (see tech tools)
  • be creative and opportunistic


"Monetize" data for project efficiency:

  • compare how much it costs to collect...
    • X records of quality A vs...
    • Y records of quality B
  • account for necessary training and support expenses
  • remember to also value and account for other goals (e.g., educational)
  • use efficiency measures to guide protocol design, equipment choices, etc. 


Adapt and improve as necessary,

  • respond to pilot tests, formative evaluations, and participant feedback regarding:
    • data forms
    • use of protocols
    • technology tools
    • available training and support
  • make improvements in a timely, transparent, and coherent manner


Have any How-to ideas for this step?  Soon you will be able to share them through our discussion forum.


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(form a team)

(recruit participants)

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