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Best Practices. NMFS EDM. Context. EDM Scope. EDM Goals. Capability Speed Efficiency Accuracy Confidence. Best Practice Concepts. Integration & Consistency – All parts have to work together. Access – Data only has value if you can get to it.

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best practices

Best Practices

NMFS EDM

M. Brady

context
Context

M. Brady

edm scope
EDM Scope

M. Brady

edm goals
EDM Goals
  • Capability
  • Speed
  • Efficiency
  • Accuracy
  • Confidence

M. Brady

best practice concepts
Best Practice Concepts
  • Integration & Consistency – All parts have to work together.
  • Access – Data only has value if you can get to it.
  • Understanding – Data only has value if you understand it.
  • QA/QC – It’s only worth something if it’s right.
  • Design & Modernization (other than integration) – Everything works better with a great design.

M. Brady

integration consistency
Integration & Consistency
  • Controlled vocabularies
  • Proper use of database keys
  • Design of super-systems precedes subsystems
  • All observations of a single event share a single report (e.g. multistream fishing reporting)

M. Brady

integration consistency1
Integration & Consistency
  • Data collection
    • Eliminate redundant reporting
    • Don’t collect data unless used
    • Automation: reduction of human data entry or processing eliminates errors and speeds the process

M. Brady

integration consistency2
Integration & Consistency
  • Data collection
    • Better ergonomics
      • Prefill electronic forms
      • Provide only appropriate choices.
      • Reject initial invalid entries.
      • Provide immediate feedback for invalid entries.
      • Accept, quarantine, and report all persistent invalid entries.

M. Brady

integration consistency3
Integration & Consistency
  • Consistency between regulations and data (e.g. trip definitions by regulation are not the same as by VMS)
  • Use a master data store.
    • Data is discoverable
    • Repeatable and consistent analyses
    • System is carefully designed and data Qced.
  • Use calibration factors when combining data into a meta-analysis.

M. Brady

integration consistency4
Integration & Consistency
  • Standardize use of data types
    • Dates
    • Numeric vs. strings

M. Brady

access
Access
  • Permissions
    • All NOAA Analysts & Managers should have read access to all fisheries data.
  • Discoverable
    • Metadata
    • Controlled vocabularies
    • Master data store
    • Effective search engines

M. Brady

access1
Access
  • Protection
    • Security
    • Archiving

M. Brady

qa qc
QA/QC
  • All detected errors must be corrected!
  • Automatically check all records for validity.
  • Automatically detect duplicates.
  • Automatically check for orphans in potentially integrated data.
  • Other errors are primarily human detectable
    • Provide immediately accessible reporting mechanism (suggestion box)
    • Follow up assurance mechanism

M. Brady

understanding
Understanding
  • Documentation
    • Description of process
    • Down to the columns
  • Streamline processes (see Design)

M. Brady

design
Design
  • Use state of the art communication systems at sea or buffer data and transmit from shore.
  • Single use columns in tables – avoid kludgycodings

M. Brady

design1
Design
  • For bulk data, such as acoustic, store data on a server and provide analysis service at the same location. This allows collaboration of multiple investigators on a shared data set.
  • Streamline processes - use the simplest possible design.
  • Automate repetitive analyses

M. Brady