Use the 'Import Template' tab to configure an Import Template based on a CSV file. An Import Template forms the connection between a CSV file and your Data Model in nodegoat. The column headings of a CSV file can be mapped to Object Descriptions, Sub-Objects, or Sub-Object Descriptions in your Data Model. Running an Import Template will write the values stored in cells of the CSV file to the mapped Object Descriptions, Sub-Objects, or Sub-Object Descriptions. An Import Template can be used to import multiple CSV files with the same column headings.
To add an Import Template, click 'Add Import Template'.
To edit an existing Import Template, click the blue 'edit' button at the relevant Import Template.
To delete an existing Import Template, click the red 'del' button at the relevant Import Template.
Select a CSV file as the 'Source' for the Import Template.
Select an Object Type or Classification as the 'Target' of the Import Template.
Specify the 'Mode' of the Import Template. The mode 'Add New Objects' allows you to enter a new Object for every row of the CSV file. The mode 'Update Existing Objects' allows you to update Objects that are present in your nodegoat domain. A value to find existing Objects needs to available in the CSV file.
Check the checkbox 'Show Log' to record a log of the run of the Import Template.
Specify the name of the Import Template. This name is used to identify the Import Template.
This section is only relevant for the mode 'Update Existing Objects'. When updating Objects in nodegoat by means of importing data, the Import Template needs to be configured to identify the Objects that will be updated. Objects can be identified by an Object ID or by a filter.
|Object ID||Use the option 'Object ID' if you have exported data from the same nodegoat domain that included an ID generated by nodegoat. You can reuse this ID to identify the Object during an import.|
The Object ID can be in the form of the 'Object ID' (e.g. '220839') or the 'nodegoat ID' (e.g. 'ngAQ3A96sAJ3kMmZiAQD3').
Use the dropdown menu to select the column of the CSV file in which the ID is stored.
|Filter||Use the option 'Filter' if you want to identify Objects by means of one or more values that match the data in the CSV file. Use this option when importing and updating a relational dataset from an external source.|
Use the dropdown menu to select one or more columns of the CSV file in which the matching data is stored. Click 'add' to add additional column headings. Click 'del' to remove empty column headings.
The filter follows the same logic as the nodegoat filter functionality. Filters can only be based on non-relational Object Descriptions, Sub-Objects, or Sub-Object Descriptions.
Every column of the selected CSV file can be mapped to one ore more Object Descriptions, Sub-Objects, or Sub-Object Descriptions. Click 'add' to add additional column headings. Click 'del' to remove empty column headings.
Use the first dropdown menu to select a column heading.
Optional: Use input field to specify a character to split the value into multiple values. Once a character has been entered you can use the dropdown menu that appears to either select a fixed position (1 to 5) of the multiple values, or select the 'multiple' option to store all the values in the split cell.
Use the next dropdown menu to select the target Object Description, Sub-Object, or Sub-Object Description.
Two dropdown menus will appear if the target Object Description or Sub-Object Description is a reference. The first (disabled) dropdown menu indicates the referenced Object Type or Classification. The second dropdown menu allows you to select an element of the referenced Object Type or Classification in which the value is stored that is to be used to make the reference. Use this option when importing a relational dataset from an external source.
Three dropdown menus will appear if the target is a Location Reference. The first dropdown menu allows you to select Object Type of the Location Reference. The second dropdown menu allows you to select the Sub-Object of the Location Reference. The third dropdown menu allows you to select an element of the referenced Object Type in which the value is stored that is to be used to make the reference. Use this option when importing a relational dataset from an external source.
If the mode of the Import Template is 'Update Existing Objects', you can click 'more' to specify additional options.
|Overwrite||Existing data will be overwritten.|
|Append||New data will be appended to existing data. This option is only available for Descriptions that have been configured as strings, integers, or texts, or Descriptions that have the 'Multiple' option enable (see the section on Object Descriptions).|
|Ignore when Empty||Select this option in combination with 'Overwrite' to only overwrite existing data with new data and take no action when a cell in the CSV file is empty. This ensures that existing data is not overwritten by blanks.|
Empty values are indicated in the log.
|Ignore when Identical||Select this option to take no action when new data is identical to existing data. |
Identical values are indicated in the log.
To run an Import Template, click the green 'run' button at the relevant Import Template. In the screen that follows you will be asked to select a CSV file as the source of the Import Template. The CSV file you used to create the Import Template will be selected by default.
After you have selected a CSV file, you will see an overview of the contents of the CSV File. The first, middle, and last row are displayed.
Click 'Next' to run the Import Template.
If the Import Template does not contain references, you will be shown the result of the run.
If the Import Template contains references, these references will be checked. Unambiguous references will be stored as String to Object Pairs. References that produce no or more than one result will be returned. You are asked to resolve any unmatched references. Once all unmatched references have been resolved, you can click 'Next' to continue. Matched references will be stored as String to Object Pairs.
If the CSV file produces more than 250 ambiguous references, the import process cannot be completed. References should be disambiguated before the Import Template is run.