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CTFS Database: Entering Luquillo LTER (LUQ) data into the system

CTFS Database: Entering Luquillo LTER (LUQ) data into the system. Presented at the Information Management Workshop for Forest Dynamic Plot Database 2009 Nantou , TAIWAN June 15 th , 2009. The CTFS database workshop II Smithsonian Tropical Research Institute (STRI) Panamá

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CTFS Database: Entering Luquillo LTER (LUQ) data into the system

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  1. CTFS Database: Entering Luquillo LTER (LUQ) data into the system Presented at the Information Management Workshop for Forest Dynamic Plot Database 2009 Nantou, TAIWAN June 15th, 2009

  2. The CTFS database workshop II Smithsonian Tropical Research Institute (STRI) Panamá September 29 to October 6, 2008. Participating Nations: Brasil - 1 plot Canada – 1 plot Colombia – 2 plots Ecuador – 1 plot DR of Congo – 1 plot US North America Temperate: Wisconsin – 1 plot Maryland – 1 plot Hawaii – 2 plots Puerto Rico – 1 plot Nantou, TAIWAN

  3. Luquillo Forest Dynamics Plot (LFDP) • A 16 ha plot • 500 m N-S and 320 m E-W • 16 X 25 grid • 400 20 x 20 m quadrats • 16 5 x 5 m sub-quadrats per quadrat • Plant census every 5 years • 4 censuses already • Measurements include: location, size, point of measurement, mortality, damage LUQ CTFS Plot data : location, dbh, mortality code, point of measurement

  4. The CTFS database workshop II: goal • Directed Neotropicaland African plot sites • Present and implement the newly designed database system • Load data from each (completed) plot into the database system • Work with data reports created by the database system • Work with the database editor for minor changes to the data • Demonstrate and examine the data entry program • Make concrete plans for how the databases will be distributed: • web applications; • sharing level up to ea. scientist Nantou, TAIWAN

  5. The CTFS database workshop II database objectives: • Store and manage: • enormous amount of plot data • store annual changes • store versions: tracking the history of data; modifications and corrections • Minimize errors: • Tree measurements errors • Mismatching errors in the database or at the field • Can be customized to add site specific data Nantou, TAIWAN

  6. Quality Control: data screening in R • Used of R to check species, quadrants, codes, match tags, etc - LUQ spent 2-3 days filtering data for the 3 censuses R Mayor Problem: tagging

  7. Data Entry: LUQ process • Mayor problems • X,Y coordinate definition-local to quadratnot to plot • Dead stem vs dead tree: CTFS database : dead trees VS LUQ : dead stems • Repetitions of records having <tag, stemtag> • Solutions: 1. Reduced the X,Y coordinate in a Paradox scripts 2. Series of queries to determine that all stems were dead, 3. Extracted records for further inspections.

  8. LUQ Entry Process: identify potential problems Eg., Duplicate Tag;Tree is in quadrat=1013” A false duplication error Eg., Another stem has larger dbh? : LUQ’s main stem was not always the one with the biggest diameter • Are this real problems that will cause substantial error in the analysis of these data? Data gathering protocols? Conceptual design? • DO WE NEED TO STANDARDIZE AT THE METHODOLOGY AND DATA ENTRY LEVEL?

  9. Data Entry Procedure • Using private online forms • Step-by-step set of forms

  10. Data Entry Procedure • Using private online forms • Step-by-step set of forms

  11. Convertspecies, codes, quadrant files into CTFS’ database format

  12. Data Entry Procedure: IM user Interface

  13. Data Entry Procedure: IM User Interface

  14. Data Entry Procedure: IM User Interface

  15. Data Querying Procedure: IM User Interface

  16. Data Querying Procedure

  17. Great quality control tool • Easy to use, once your data is “bug” free • PURPOSE OR CONCEPT BEHIND: • Database designed for storage and management of data in a standard way, • NOT FOR SHARING WITH OTHERS • “Forces” standardization in some ways: • Data design: codes and measurments definitions • Data gathering protocols • , My assessment of the system

  18. Importance of IM workshops: • Mix IM and scientists • Learning the system together • Both groups discussing the scientists’ needs and use of the system • IM and Scientists relationship • IM reason to exist: facilitate science • Scientists need of IM to manage large amount of data • When spreadsheets are just not enough • , Some Thoughts

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