Preparations for the CSV Import

The import of a CSV file is the most complex import variant. To minimize your change workload in crossTerm, there are a number of things you can do prior to the import.

First of all, it would be good for the import data (i.e. the column headers of the CSV file) to match the names of the data categories in the crossTerm instance.

Basic rules:
Every data category must have a separate column.
Every sublanguage requires a separate column.
You can map the columns of the CSV file to terms by means of their designation.

Example

CSV file example

If the CSV file contains several terms for an entry in different rows, I would recommend inserting a column with numbers. Simply enter a number for every entry (no matter what number). So if an entry with term X has the number 1215, give the additional row with the associated term the number 1215 as well.

Example: An entry with two terms

The column names in the CSV file will determine the mapping that crossTerm will perform during the import. Here an example:

CSV example

If you arrange your CSV file as shown above, crossTerm will detect the language during the import, but not the type of information. This means that you will have to do a lot of additional work in the Import Wizard and map an information type (e.g. term, data category, picklist) to the columns.

View in the Import Wizard

But if you select column headers like here ...

CSV file with good mapping

… Across will immediately recognize the type of information they contain:

Good mapping of information types

Influencing factors

Overview of all factors that influence the term import via CSV:

Designation in CSV column	Explanation
Language code in parentheses	(EN) will be identified as English with the standard sub-language.
ConceptDefinition(DE)	Will be identified as entry definition, i.e. definition at entry level in German.
Term(DE)	Will be identified as a German term entry.
TermDefinition	Will be identified as term definition, i.e. definition at term level.
[C:ATT]XY	Will be identified as picklist at entry level. C stands for Concept (entry).
[T:ATT]XY	Will be identified as picklist at term level. T stands for Term.
[C:TXT] [T:TXT]	Will be identified as text field at entry or term level.
[T:ATT]Status(DE)	Will be identified as term status (released/not released)
#	Entry ID (if the number is the same, the terms will automatically be associated with each other).

Tip

Prior to the import, consider what kind of information you have already created in your instance or would still like to add, and name the columns of your CSV file accordingly.