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Make More Sense of Your Environmental Data with the Branch of Quality System’s Blind-Sample Products. IBSP & OBSP. Question. You see a trend or pattern in your environmental data that you didn’t expect. How might you explain this?. Blind Samples. What is a “Blind” sample?
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Make More Sense of Your Environmental Data with theBranch of Quality System’s Blind-Sample Products IBSP & OBSP
Question You see a trend or pattern in your environmental data that you didn’t expect.How might you explain this?
Blind Samples What is a “Blind” sample? A blind sample is a quality-control sample whose composition and origin is unknown except to those who are submitting the sample. It is disguised to appear like a regular environmental sample to the laboratory. Its purpose is to allow a realistic and uncensored measure of bias and variabilityof the entire laboratory process.
Blind Samples How do blind-samples results help data-users assess their environmental sample results from the NWQL? • Blind samples are treated the same as environmental samples and are designed to capture the same sources of variability as environmental samples • Inorganic-from login through NWIS • Organic-from login through StarLIMS • Blind samples and on-line QC samples are different
Blind Samples How do blind-samples results help data-users assess their environmental sample results from the NWQL? • User accessible data sets • Blind-sample results are retrieved, posted, and available to the data-user • Inorganic – Within 1-3 days of release from the NWQL • Organic – Data reviewed when available.
Current products that help aid in data interpretation • Time-series charts/box plots • To observe bias and variabilityover time • Recovery versus concentration charts • To assess recovery and variability at different concentration ranges • Blind-blank/false positive/false negative charts • To observe blank contamination and assess reporting levels
Current products that help aid in data interpretation • Raw data • Custom data packets • Data-quality assessment reports
Question You see a trend or pattern in your environmental data that you didn’t expect.How might you explain this?
Box Plots: OBSP BQS ORGANIC BLIND SAMPLES DETERMINATION: CYANAZINE, SCHEDULE: 2033 TESTIDCODE: 04041GCM35 , MEASURED IN MICROGRAMS PER LITER 04/03/08 TO 12/22/11 Open Data Set
Question You’re seeing unexpected results in your blank/low-level environmental sample data.How can you sort out these issues?
Question You expected to see a certain compound in your sample and instead you received a < (less than) as your result.Are the concentrations in your samples too low to be quantified?
Question You think quality-control charts are OK, but you would really just like to have the data to work with it yourself. How can you easily obtain a subset of the QC data in a user-friendly format?
Branch of Quality Systemsbqs.usgs.gov • Inorganic blind-sample project • Ted Struzeski • Organic blind-sample project • Suranne Stineman
Question The website can be overwhelming with so many QC charts for so many parameters.Can you just have a summary of suspecteddata-quality issues?
Data-quality assessment reports Inorganic: Every-other-month Organic: Data reviewed when available
Moving Forward…Inorganic Blind Sample Project • Method-to-method charts • To assess data-quality between methods • Method A versus method B • Filtered versus unfiltered • Old method versus new method • Concentration-dependent charts • To assess concentration-dependent bias and variability • Percent RSD charts • To assess variability at a given concentration • To characterize overall method variability
Inorganic Blind Sample Project • Potential Future Products • Analyte by different methods: ICP versus DA
Inorganic Blind Sample Project • Potential Future Products • Analyte in different phases: filtered versus unfiltered – Example 1
Inorganic Blind Sample Project • Potential Future Products • Analyte in different phases: filtered versus unfiltered – Example 2
Inorganic Blind Sample Project • Potential Future Products • Analyte by different methods: old method versus new method
Inorganic Blind Sample Project • Potential Future Products • Concentration-dependent recovery charts
Inorganic Blind Sample Project • Potential Future Products • % Relative Standard Deviation chart
Math! %RSD = (SD/mean)*100 SD = %RSD(mean)/100 Let %RSD = 3 and concentration = 20 mg/L SD = 3(20)/100 SD = 0.6
Moving Forward…Organic Blind Sample Projects • Analyte in multiple methods • To assess data-quality performance across multiple methods • Old method versus new method • Chart of expected and reported concentration versus time • To assess concentration-dependent bias over time • Annual false positive and false negative summaries • To assess potential contamination issues or interferences • To assess confidence in low-concentration results • Plot some “user defined limits” on the various charts • To assess how blind-sample results compare to these limits
Organic Blind Sample Project • Potential Future Products • Analyte by several different methods
Organic Blind Sample Project • Potential Future Products • Analyte by several different methods
Organic Blind Sample Project • Potential Future Products • Expected and reported concentration versus time
Organic Blind Sample Project • Potential Future Products • False positives and false negatives summary table
Organic Blind Sample Project • Potential Future Products • User defined limits on an existing time series chart ------- = Recovery range (50% to 150%)
Moving Forward…Inorganic & Organic Blind Sample Projects Modification to format of existing data-quality assessment reports Look into NWIS toolbox for IBSP and OBSP data analysis QA upcoming organic tissue and sediment methods Use more different types of matrices for the inorganic blind samples Provide information about the matrix for the inorganic blind samples
Moving Forward…Inorganic & Organic Blind Sample Projects • Requesting input from the data users • What do you want to see? • What would be useful to you?
Branch of Quality Systemsbqs.usgs.gov • Inorganic blind-sample project • Ted Struzeski • bqs.usgs.gov/ibsp/ • struzesk@usgs.gov • 303.236.1872 • Organic blind-sample project • Suranne Stineman • bqs.usgs.gov/obsp/ • stineman@usgs.gov • 303.236.1821