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DEVA Data Management Workshop Devil’s Hole Pupfish Project Quality Assurance
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DEVA Data Management Workshop Devil’s Hole Pupfish Project
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“mechanisms [that] are designed to prevent the introduction of errors into a data set, a process known as data contamination” QA/QC from Brunt 2000 Commission: Incorrect or inaccurate data are entered into a dataset – Can be easy to find – Malfunctioning instrumentation Sensor drift Low batteries Damage Animal mischief – Data entry errors Omission: Data or metadata are not recorded – Difficult or impossible to find – Inadequate documentation of data values, sampling methods, anomalies in field, human errors
![mechanisms [that] are designed to prevent the introduction of errors into a data set, a process known as data contamination QA/QC from Brunt 2000 Commission: Incorrect or inaccurate data are entered into a dataset – Can be easy to find – Malfunctioning instrumentation Sensor drift Low batteries Damage Animal mischief – Data entry errors Omission: Data or metadata are not recorded – Difficult or impossible to find – Inadequate documentation of data values, sampling methods, anomalies in field, human errors](http://images.slideplayer.com/26/8499890/slides/slide_3.jpg "mechanisms [that] are designed to prevent the introduction of errors into a data set, a process known as data contamination QA/QC from Brunt 2000 Commission: Incorrect or inaccurate data are entered into a dataset – Can be easy to find – Malfunctioning instrumentation Sensor drift Low batteries Damage Animal mischief – Data entry errors Omission: Data or metadata are not recorded – Difficult or impossible to find – Inadequate documentation of data values, sampling methods, anomalies in field, human errors")
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DEVA Data Management Workshop Devil’s Hole Pupfish Project Verification and Validation Verification – has data been entered correctly? Validation – does data make sense ecologically? Handout 5-1: Example of data verification request Handout 5-2: Response from person responsible for data entry Handout 5-3: Example of a data sheet with quality assurance samples Handout 5-4: Example of a data sheet with a missing value
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DEVA Data Management Workshop Devil’s Hole Pupfish Project Verification and Validation Handout 5-6: Total carbon duplicates - to test precision of measurements Handout 5-7: Total carbon duplicates – to establish measurement quality objectives Handout 5-8: % plant cover duplicates – comparison of results from routine field crews with an independent QA crew
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DEVA Data Management Workshop Devil’s Hole Pupfish Project Verification Process Types Visual review at data entry (2 nd person check) Visual review after data entry (print out and review) Duplicate data entry (enter random data in a testing DB) Project Leaders are fully responsible for data (both verification and validation) 100% of records checked by data entry staff >= 10% random records checked by Project Leader for verification
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DEVA Data Management Workshop Devil’s Hole Pupfish Project NPS Director’s Order 11B Ensuring Quality of Information Disseminated by the NPS Defines quality as three key components Objectivity Utility Integrity You Passed!
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