Policies can be managed in the Governance Console.
Once a policy is published, it becomes immutable, ensuring the lineage between a Governed Bundle and the approved policy can be maintained.
Note
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You’ll need to be assigned the GovernanceAdmin role in order to complete these tasks.
CloudAdmins and SysAdmins already have permissions associated with Domino Governance.
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This document explains the YAML configuration structure that defines various input fields, automated jobs, metadata, and guidance elements.
Structure Overview
The YAML configuration consists of a list of items, each representing a different element in the user interface or system configuration.
Each item has the following common properties:
-
artifactType
: Defines the type of artifact (e.g., input, automatedJob, metadata, guidance).
The details
section contains specific properties for each artifact type.
Evidence and evidence sets
Evidence includes inputs, approvals, and checks that should be gathered as part of the governance process within a given stage. Evidence sets represent logical groupings of evidence and can also be reused in other policies if needed.
yaml
evidenceSet:
- id: Local.sample
name: sample local evidence
description: Describe the sample local evidence
definition: Define the evidence
-
Local
: Local evidence should have the full definition included when appearing for the first time in the policy. It can later be referenced by id when using it in the YAML file. -
name
: Name of the evidence. -
description
: This is where the evidence is described. -
definition
: This is where artifacts are defined. Guidance artifact types must have a text field under details. Input artifact types must have type and label fields. Each artifact contains one UI element. Supported types include radio, textinput, textarea, select, multiselect, checkbox, date, and numeric.
Metrics checks
Model metrics in these cases refer to a set of metrics encapsulated by the policy YAML and there can be 1+n model metrics. Users can then add additional metrics to a set of model metrics and have multiple sets of model metrics. Each model metrics set will have the same required fields defined by the policy as a baseline.
yaml
metrics:
- id: Local.model-quality
name: Model Quality
description: Describe the model quality
definition:
- artifactType: metadata
details:
type: modelmetric
metrics:
- name: Acc
label: Accuracy
aliases:
- acc
- Correct Classification Rate
- Percentage Correct
threshold:
operator: '>='
value: 0.8
-
Local
: Local evidence should have the full definition included when appearing for the first time in the policy. It can later be referenced byid
when using it in the YAML file. -
name
: Name of the model metrics. -
description
: This is where the model quality is described. -
definition
: This is where model metrics are defined. -
label
: How the metric name appears in the evidence notebook. -
aliases
: Alternatives to name metrics, to be used in the search to automatically add the metric to the notebook. -
threshold
: Operations to define a threshold for the metric include operators such as equal "=", greater than ">", and less than "<", among other relational operators. -
value
: Represents the actual threshold.
Radio Buttons
yaml
- artifactType: input
details:
type: radio
label: "How would you rate the model risk?"
options:
- label: "High"
value: "High"
- label: "Medium"
value: "Medium"
- label: "Low"
value: "Low"
tooltip: "Guidance text"
-
type: radio
: Defines a set of radio buttons. -
label
: The question or prompt for the radio group. -
options
: A list of choices, each with alabel
(displayed text) andvalue
(submitted data). -
tooltip
: Additional information shown on hover.
Text Input
yaml
- artifactType: input
details:
type: textinput
label: "What are the expected business benefits?"
placeholder: "Explain the benefit"
helpText: "The text under the input box to help the user"
-
type: textinput
: Defines a single-line text input field. -
label
: The prompt for the input. -
placeholder
: Example text is shown when the field is empty. -
helpText
: Additional guidance is displayed below the input field.
Text Area
yaml
- artifactType: input
details:
type: textarea
label: "What are the expected business benefits?"
height: 10
placeholder: "Explain the benefit"
helpText: "The text under the input box to help the user"
-
type: textarea
: Defines a multi-line text input field. -
height
: Specifies the height of the text area in lines.
Select Dropdown
yaml
- artifactType: input
details:
type: select
label: "Please select the base model template."
options:
- label: "base model1"
value: "baseModel1"
- label: "base model2"
value: "baseModel2"
-
type: select
: Defines a dropdown selection field. -
options
: A list of choices, similar to radio buttons.
Multi-Select
yaml
- artifactType: input
details:
type: multiSelect
label: "Please select the data sets used in the model."
options:
- label: "data set1"
value: "dataset1"
- label: "data set2"
value: "dataset2"
- label: "data set3"
value: "dataset3"
-
type: multiSelect
: Defines a multi-select dropdown field and allows selection of multiple options.
Checkbox Group
yaml
- artifactType: input
details:
type: checkbox
label: "Please select the departments that will use the model?"
options:
- label: "Sales"
value: "DEPT001"
- label: "Customer Success"
value: "DEPT002"
-
type: checkbox
: Defines a group of checkboxes and allows selection of multiple options.
Guidance Artifacts
Guidance artifacts provide guidance or information to the user.
yaml
- artifactType: guidance
details:
type: textblock
text: >-
[Map 1.4](https://ournistpolicyreferenceurl.com) The business value or
context of business use has been clearly defined or - in the case of
assessing existing AI systems - re-evaluated
-
type: textblock
: Displays a block of text. -
text
: The content to display - supports Markdown formatting.
yaml
- artifactType: guidance
details:
type: banner
text: >-
[Map 1.4](https://ournistpolicyreferenceurl.com) The business value or
context of business use has been clearly defined or - in the case of
assessing existing AI systems - re-evaluated
-
type: banner
: Displays a prominent banner with text. -
Useful for important notices or key information
Approvals
Approvals are defined under stages. Each approval is defined with a name, a group of specified approvers, and evidence. Approvers must be Domino users or organizations and are specified by the user’s or organization’s name.
yaml
- name: 'Stage 4: validation sign off'
approvers:
- model-gov-org
evidence:
id: Local.validation-approval-body
name: Sign-off
description: The checklist for approvals
definition:
- artifactType: input
details:
label: "Have you read the model validation reports?"
type: radio
options:
- Yes
- No
Classification
Classification is a top-level variable often used to classify a Governed Bundle in a risk tier (low, medium, or high).
yaml
classification:
rule:
artifacts:
- model-risk
stages:
- name: classificationExample
- id: Local.model-risk
name: Model Risk
description: Describe the risk of the model
definition:
- artifactType: input
aliasForClassification: model-risk
details:
label: "How would you rate the model risk?"
type: radio
options:
- High
- Low
tooltip: guidance on how to rate the model risk within the organization
-
classification
: Policy-level classification. -
rule
: Classification rule definition; leave it empty if using the result of the artifact defined below. -
artifacts
: The artifact alias that is specified in the evidence definition. -
aliasForClassification
: Reference to classification artifacts.
Classification rule
Classification rules allow the construction of complex operations based on the outcome of multiple pieces of evidence.
func() string {
var sum float64
for _, value := range inputs {
sum += value
}
if sum >= 1 {
return "High"
}
return "Low"
}()
Visibility Rules
Visibility rules apply at an evidence-set level. Based on the visibility rule, we can customize whether to display a set of questions. For example, some evidence might be required only for Governed Bundles classified as high-risk.
yaml
evidenceSet:
- id: Global.type-of-development
visibilityRule: inputs=="High"
-
visibilityRule
: Optional, the visibility rule shows or hides evidence based on the classification value. In this example, the evidence set will only be displayed if the classification is High.