Data’s quality assurance
1- Maintenance and metrology of ORACLE device:
The metrological aspect with establishment of rigorous protocols for device installation, systematization of the procedures, rigorous and regular maintenance is the first step in our quality approach.
2- Data processing
The data processing stage includes frequent repatriation of the data, verification of the consistency of the series, as well as verification of the consistency of the variables and parameters with respect to each other. This step is all the more important as it must allow rapid validation of Oracle’s 34,000 monthly data.
1. Repatriation of data
Rainfall and Limnimetric records are automated and directly remotely transmitted on an internal database, every hour.
Limnimetric data are stored after validation on the HYDRO bank, managed by the MEEDDAT.
Other data are repatriated at regular frequency on an internal database (every two months on average).
2. Data validation
All data are validated by the research engineer, manager of the Observatory. Semi-automated routines were set up to allow a faster validation, but also a certain repeatability of the validation.
The use of statistical tools (e.g., average, quartiles…) makes it possible:
I) to carry out an inter-comparison on data set over the full period of observation
II) to check series coherence.
3- Reconstitution of data :
The objective is to bring in work a number of provisions at the managerial and technical level to lead to reliable results and to be able to prove this reliability (concept of confidence). This work is based in particular on recommendations for quality in research, such as the AFNOR document, FDX50-551.