CTFS Database: Entering Luquillo LTER (LUQ) data

into the systemPresented at the Information Management Workshop for Forest

Dynamic Plot Database 2009Nantou, TAIWAN

June 15th, 2009

Nantou, TAIWAN

The CTFS database workshop IISmithsonian Tropical Research Institute (STRI) PanamáSeptember 29 to October 6, 2008.

Monday, June 15, 2009

Participating Nations:Brasil - 1 plotCanada – 1 plotColombia – 2 plotsEcuador – 1 plotDR of Congo – 1 plotUS North America

Temperate:Wisconsin – 1 plot Maryland – 1 plot

Hawaii – 2 plotsPuerto Rico – 1 plot

Luquillo Forest Dynamics Plot (LFDP)

LUQ CTFS Plot data : location, dbh, mortality code, point of measurement

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

Nantou, TAIWAN

Directed Neotropical and 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 Monday, June 15, 2009

The CTFS database workshop II: goal

Nantou, TAIWAN

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

Monday, June 15, 2009

The CTFS database workshop II database objectives:

Quality Control: data screening in R

R Mayor Problem: tagging

Used of R to check species, quadrants, codes, match tags, etc

- LUQ spent 2-3 days filtering data for the 3 censuses

Data Entry: LUQ process Mayor problems

1. X,Y coordinate definition-local to quadrat not to plot2. Dead stem vs dead tree:

CTFS database : dead trees VS LUQ : dead stems3. Repetitions of records having <tag, stemtag>

Solutions:1. Reduced the X,Y coordinate in a Paradox scripts2. Series of queries to determine that all stems were

dead, 3. Extracted records for further inspections.

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?

LUQ Entry Process: identify potential problems

Using private online forms

Step-by-step set of forms

Data Entry Procedure

Using private online forms

Step-by-step set of forms

Data Entry Procedure

Convert species, codes, quadrant files into CTFS’ database format

Data Entry Procedure: IM user Interface

Data Entry Procedure: IM User Interface

Data Entry Procedure: IM User Interface

Data Querying Procedure: IM User Interface

Data Querying Procedure

My assessment of the system

•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

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Some Thoughts

• 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

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