Talk on Quality Control and Quality Assurance for ecological data, presented as an ignite talk for ESA 2014 meeting in Sacramento CA 12 Aug 2014

1. Ensuring That Your Data
are High Quality
Carly Strasser | @carlystrasser
California Digital Library
ESA 2014

2. Quality assurance & control:
Mechanisms for preventing errors
from entering a data set

3. Quality assurance & control:
Plan
Collect
Assure
Describe
Preserve
Discover
Integrate
Analyze

4. Why?

5. Why?

6. From:

7. Prevent
Minimize
Detect
Handle
4 Strategies:
From Flickr by Elliott Teel

8. Prevent Errors Before Collection
• Define & enforce standards
• Formats
• Codes
• Measurement units
• Metadata
FromFlickrbyStacieBee

9. Prevent Errors Before Collection
• Define & enforce standards
• Formats
• Codes
• Measurement units
• Metadata
• Assign responsibility
for data quality
FromFlickrbyStacieBee

10. Comments & notes fields
Allows handling of unexpected situations
Prevent Errors Before Collection
Allow “other” values
From Flickr by Olga Nohra

11. Minimize Errors During Collection
• Eliminate manual data entry
• Design data storage well
• Minimize repeat entry
• Use consistent terminology
• Atomize data
From Flickr by Butal Lee

12. You should invest time in learning databases if
your data sets are large or complex
Consider investing time in learning databases if
your data are small and humble
you ever intend to share your data
you are < 30 years old
From Mark Schildhauer
Minimize Errors: Use databases

13. Databases
• FileMaker Pro (Mac)
• Access (PC)
• LibreOffice
Minimize Errors: Tools

14. Databases
• FileMaker Pro (Mac)
• Access (PC)
• LibreOffice
Spreadsheets
• Google forms
• LibreOffice
• Lists & data validation in
Excel
Minimize Errors: Tools

15. Detect Errors After Collection
Look for outliers
Goal is not to eliminate outliers but to
identify potential data contamination
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10
20
30
40
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60
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16. Detect Errors After Collection
Look for outliers
Goal is not to eliminate outliers but to
identify potential data contamination
Strategies
• Normal probability plots
• Regression
• Scatter plots
• Maps
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10
20
30
40
50
60
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17. Handle Errors
• Case-by-case decision
• Flag them?
• Remove them?
• Fix them?
• Document all changes
readme.txt, scripts

18. Handle Errors
• Case-by-case decision
• Flag them?
• Remove them?
• Fix them?
• Document all changes
readme.txt, scripts
• Keep original data
separate
• Use scripts
Raw data as .csv
R script for QAQC

19. Prevent
Minimize
Detect
Handle
4 Strategies:
From Flickr by Elliott Teel

20. Website
Email
Twiter
Slides
carlystrasser.net
carlystrasser@gmail.com
@carlystrasser
slideshare.net/carlystrasser