Creating Data Preparation Procedures in DIAdem

Use Data Preparation procedures (*.dpp) to harmonize measurement data from different sources. Data Preparation procedures contain information about the identifiers and values of properties you want to harmonize, the units you want to convert, and the data file format.

1. Open DIAdem SCRIPT.
2. Select Settings»SystemLink TDM»Data Preparation Procedure.
3. Click New Data Preparation Procedure.
4. Enter the name of the new data preparation procedure, a description, and the author, and click OK.
5. On the Replace Identifiers tab, specify how DIAdem replaces the labels of properties. If files from different sources contain different identifiers for an engine you want to test, for example, source 1: Engine, source 2: Engine_Type, source 3: Fuel, you can now specify Engine_Fuel_Type as the default identifier in this dialog box. The data preparation now assigns the identifier Engine_Fuel_Type to all properties from the different sources.

   	Source 1	Source 2	Source 3	Harmonized Identifier
   Identifier of the Property	Engine	Engine_Type	Fuel	Engine_Fuel_Type

6. On the Replace Values tab, specify how DIAdem replaces property values. If files from different sources also contain different values for the name of the engine to be tested, for example, source 1: Diesel, source 2: D, source 3: Fuel_Diesel, you can now specify Diesel as the default value in this dialog box. The data preparation now assigns the value Engine_Fuel_Type to all properties from the different sources.

   	Source 1	Source 2	Source 3	Harmonized Identifier
   Property Value	Diesel	D	Fuel_Diesel	Diesel

   After the replacement the identifiers and values are harmonized.

   Harmonized Identifier	Harmonized Value
   Engine_Fuel_Type	Diesel

7. Optional: On the Convert Units tab, specify the unit which DIAdem uses to save the processed data. For example, if temperatures were measured in the units °F and °C and are to be evaluated in the unit K, specify that DIAdem stores all temperatures in the unit K.
8. Optional: On the Statistics tab, calculate characteristic statistical values, such as means, quantiles, or dispersions. Data Preprocessor instances save the statistical results as custom properties in the processed data files.
9. Optional: On the V & V tab, check whether the data is plausible and complete. For validation and verification, create a script that checks whether a limit value is adhered to.
10. Optional: On the Convert File tab, specify the file format which a Data Preprocessor instance uses to save the processed data.
11. Click Save Data Preparation Procedure As, enter a name, and click Save.