Climate Data
Quality Control for Primary Data
Quality control (QC) of primary data plays an important role in the data publication process.
QC tasks and responsibilities are divided between:
- Data Publishing Agency performing automated checks on data and metadata consistency (Technical Quality Assurance - TQA), and
- Data Creator controlling the scientific data quality (Scientific Quality Assurance - SQA) .
Technical Quality Assurance at WDCC During the cross- and double-checks of WDCC's publication agent at least the following criteria are checked:
|
1. Number of data sets is correct and > 0 |
| 2. Size of every data set is > 0 |
| 3. The data sets and corresponding metadata are accessable |
| 4. The data sizes are controlled and correct |
| 5. The spatial-temporal coverage description (metadata) is consistent to the data, time steps are correct and the time coordinate is continuous |
| 6. The format is correct |
| 7. Variable description and data are consistent |
Contents of quality checks (especially in SQA) as well as definitions of quality levels and the overall quality procedures vary significantly between data types and scientific disciplines.
The World Data Center Climate (WDCC) at DKRZ is currently involved in two projects, in which quality assessment procedures are developed and applied:
CMIP5 (Coupled Model Intercomparison Project number 5):
with a QC tool suitable for model data TQA checks developed at WDCC: More information on the CMIP5 quality procedure at http://cmip5qc.wdc-climate.de.
Publication of Environmental Data:
with a QC package for observational data checks developed by the University
of Bonn (http://meteo.uni-bonn.de/) to support the data creator's SQA:
More information on the quality package at http://cran.r-project.org/web/packages/qat/.
