CSV file for term and classification assignment based on rules

General formatting rules

The CSV file must comply with the Common Format and MIME Type for comma-separated values (CSV) Files and must be encoded in UTF-8.

Rule columns

The CSV file can contain mandatory and optional columns.

To define the rule condition, include these columns:

OBJECT_TYPE

The type of object where terms should be assigned. Valid values:

• asset
• column

This column is mandatory and must not be empty.

PROPERTY

The property to match. Valid values:

• name: The name of the data asset or column.
• description: The description of the data asset or column.
• mostfreqvalues: Any of the most frequent values of the data profile. Rules with this property require data profiling before the rule can be properly applied.
  OBJECT_TYPE must be column.
• dataclassname: The name of the data class that is assigned to a column.
  OBJECT_TYPE must be column.
• assetid: The ID of the data asset.
• parentassetname: The name of the data asset that contains the column.
  OBJECT_TYPE must be column.
• parentassetdescription: The description of the data asset that contains the column.
  OBJECT_TYPE must be column.

This column is mandatory and must not be empty.

MATCH_STRING

The string to match against the property. You can set any value. This column is mandatory and must not be empty.

MATCH_TYPE

Describes how the match string should be matched against the property. This column is mandatory and must not be empty. Valid values:

• equals
  Case-insensitive exact match.

• equalscs
  Case-sensitive exact match.

• contains
  Match if the property contains the match string. Matching is case-insensitive.

• containscs
  Match if the property contains the match string. Matching is case-sensitive.

• regex
  Match if the match string is a regular expression and matches the property. For security reasons, this is disabled by default.

  An instance administratior can enable the use of regular expressions. For more information, see Enable the use of regular expressions for rule-based term assignment in the IBM Software Hub documentation.

To define which terms and classifications to assign with which confidence, include these columns

TERM_NAME

The name of the term including the category path as described in Category path. For example, Category 1 >> Category2 >> MyTerm.

To assign a term, either TERM_NAME or TERM_ID must be present. You can specify both. In that case, TERM_ID takes precedence. If you plan to use the rules file in different systems with similar terms and category hierarchies, use term names instead of term IDs.

TERM_ID

The ID of the term. You can use the artifact ID or the global ID.

To assign a term, either TERM_NAME or TERM_ID must be present. You can specify both. In that case, TERM_ID takes precedence. If you plan to use the rules file in different systems with similar terms and category hierarchies, use term names instead of term IDs.

CLASSIFICATION_NAME

The name of the classification including the category path as described in Category path. For example, Category 1 >> Category2 >> MyClassification.

To assign a classification, either CLASSIFICATION_NAME or CLASSIFICATION_ID must be present. You can specify both. In that case, CLASSIFICATION_ID takes precedence. If you plan to use the rules file in different systems with similar classifications and category hierarchies, use classification names instead of classification IDs.

CLASSIFICATION_ID

The ID of the classification. You can use the artifact ID or the global ID.

To assign a classification, either CLASSIFICATION_NAME or CLASSIFICATION_ID must be present. You can specify both. In that case, CLASSIFICATION_ID takes precedence. If you plan to use the rules file in different systems with similar classifications and category hierarchies, use classification names instead of classification IDs.

CONFIDENCE

A float value between 0 and 1 that indicates the confidence for the term or classification assignment. The default value is 1.0 (=100%). Independent of the locale, the decimal point is .

Additional columns that you can include:

ACTIVE

If you set the value no, the rule is not considered during assignment. During development, you might want to disable certain rules without removing them from the CSV file.

GROUP

A group of rules that allows you to set up more complex assignment rules, such as, If a column name contains X and its description contains Y, then assign term T1 and T2.

At least one condition and one action must be defined per rule group.

Rule file options

You can supply additional options to influence how rules are applied in the description field of the uploaded rule file. Add lines in the format <option-name>=<option-value>. The description field can contain any other text as well.

default_confidence_if_missing

A float value between 0 and 1 that indicates a default confidence other than 1.0 if the CONFIDENCE column is empty.

use_expanded_names

Defines when a generated name should also be considered when rules are evaluated. This option is valid only if gen AI based enrichment capabilities are enabled.

Possible values:

• NEVER: Do not consider generated names.
• SUGGESTED: Consider a suggested generated name.
• ACCEPTED: Consider an assigned generated name.

Default value is ACCEPTED.

use_generated_descriptions

Defines when a generated description should also be considered as a description when rules are evaluated. This option is valid only if gen AI based enrichment capabilities are enabled.

Possible values:

• NEVER: Do not consider generated descriptions
• SUGGESTED: Consider a suggested generated description.
• ACCEPTED: Consider an assigned generated description.

Default value is ACCEPTED.

Examples

See some rule and rule group examples.

This the best rule file in the world.

default_confidence_if_missing = 0.95
use_expanded_names = ACCEPTED
use_generated_descriptions = SUGGESTED

Closing remarks.