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Best Practices

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

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  1. Best Practices NMFS EDM M. Brady

  2. Context M. Brady

  3. EDM Scope M. Brady

  4. EDM Goals • Capability • Speed • Efficiency • Accuracy • Confidence M. Brady

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. Integration & Consistency • Standardize use of data types • Dates • Numeric vs. strings M. Brady

  11. 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

  12. Access • Protection • Security • Archiving M. Brady

  13. 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

  14. Understanding • Documentation • Description of process • Down to the columns • Streamline processes (see Design) M. Brady

  15. 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

  16. 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

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