public sealed class DataLabelingJob : IMessage<DataLabelingJob>, IEquatable<DataLabelingJob>, IDeepCloneable<DataLabelingJob>, IBufferMessage, IMessage
Reference documentation and code samples for the Vertex AI v1beta1 API class DataLabelingJob.
DataLabelingJob is used to trigger a human labeling job on unlabeled data
from the following Dataset:
public ActiveLearningConfig ActiveLearningConfig { get; set; }
Parameters that configure the active learning pipeline. Active learning
will label the data incrementally via several iterations. For every
iteration, it will select a batch of data based on the sampling strategy.
public MapField<string, string> AnnotationLabels { get; }
Labels to assign to annotations generated by this DataLabelingJob.
Label keys and values can be no longer than 64 characters
(Unicode codepoints), can only contain lowercase letters, numeric
characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
System reserved label keys are prefixed with "aiplatform.googleapis.com/"
and are immutable.
Required. Dataset resource names. Right now we only support labeling from a
single Dataset. Format:
projects/{project}/locations/{location}/datasets/{dataset}
Required. The user-defined name of the DataLabelingJob.
The name can be up to 128 characters long and can consist of any UTF-8
characters.
Display name of a DataLabelingJob.
Required. Points to a YAML file stored on Google Cloud Storage describing
the config for a specific type of DataLabelingJob. The schema files that
can be used here are found in the
https://storage.googleapis.com/google-cloud-aiplatform bucket in the
/schema/datalabelingjob/inputs/ folder.
Required. The Google Cloud Storage location of the instruction pdf. This
pdf is shared with labelers, and provides detailed description on how to
label DataItems in Datasets.
The labels with user-defined metadata to organize your DataLabelingJobs.
Label keys and values can be no longer than 64 characters
(Unicode codepoints), can only contain lowercase letters, numeric
characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
System reserved label keys are prefixed with "aiplatform.googleapis.com/"
and are immutable. Following system labels exist for each DataLabelingJob:
"aiplatform.googleapis.com/schema": output only, its value is the
[inputs_schema][google.cloud.aiplatform.v1beta1.DataLabelingJob.inputs_schema_uri]'s
title.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-28 UTC."],[[["\u003cp\u003eThe \u003ccode\u003eDataLabelingJob\u003c/code\u003e class in the Vertex AI v1beta1 API is used to initiate and manage human labeling tasks on datasets, supporting the incremental labeling of data through active learning.\u003c/p\u003e\n"],["\u003cp\u003eThis class supports the configuration of active learning pipelines, allowing for iterative data labeling, including defining the number of labelers and the selection strategy for each iteration.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eDataLabelingJob\u003c/code\u003e can be configured with encryption keys for data security, and manages labels, progress, and cost estimation of the labeling process, offering detailed insight into the job's state and performance.\u003c/p\u003e\n"],["\u003cp\u003eThe class can handle multiple datasets and specialist pools, where each job requires a defined input schema URI and instruction URI for the labeling task, alongside custom user-defined metadata.\u003c/p\u003e\n"],["\u003cp\u003eThe latest version is 1.0.0-beta21, and it inherits and implements several interfaces to offer enhanced functionality.\u003c/p\u003e\n"]]],[],null,["# Vertex AI v1beta1 API - Class DataLabelingJob (1.0.0-beta47)\n\nVersion latestkeyboard_arrow_down\n\n- [1.0.0-beta47 (latest)](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.DataLabelingJob)\n- [1.0.0-beta46](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/1.0.0-beta46/Google.Cloud.AIPlatform.V1Beta1.DataLabelingJob) \n\n public sealed class DataLabelingJob : IMessage\u003cDataLabelingJob\u003e, IEquatable\u003cDataLabelingJob\u003e, IDeepCloneable\u003cDataLabelingJob\u003e, IBufferMessage, IMessage\n\nReference documentation and code samples for the Vertex AI v1beta1 API class DataLabelingJob.\n\nDataLabelingJob is used to trigger a human labeling job on unlabeled data\nfrom the following Dataset: \n\nInheritance\n-----------\n\n[object](https://learn.microsoft.com/dotnet/api/system.object) \\\u003e DataLabelingJob \n\nImplements\n----------\n\n[IMessage](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IMessage-1.html)[DataLabelingJob](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.DataLabelingJob), [IEquatable](https://learn.microsoft.com/dotnet/api/system.iequatable-1)[DataLabelingJob](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.DataLabelingJob), [IDeepCloneable](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IDeepCloneable-1.html)[DataLabelingJob](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.DataLabelingJob), [IBufferMessage](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IBufferMessage.html), [IMessage](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IMessage.html) \n\nInherited Members\n-----------------\n\n[object.GetHashCode()](https://learn.microsoft.com/dotnet/api/system.object.gethashcode) \n[object.GetType()](https://learn.microsoft.com/dotnet/api/system.object.gettype) \n[object.ToString()](https://learn.microsoft.com/dotnet/api/system.object.tostring)\n\nNamespace\n---------\n\n[Google.Cloud.AIPlatform.V1Beta1](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1)\n\nAssembly\n--------\n\nGoogle.Cloud.AIPlatform.V1Beta1.dll\n\nConstructors\n------------\n\n### DataLabelingJob()\n\n public DataLabelingJob()\n\n### DataLabelingJob(DataLabelingJob)\n\n public DataLabelingJob(DataLabelingJob other)\n\nProperties\n----------\n\n### ActiveLearningConfig\n\n public ActiveLearningConfig ActiveLearningConfig { get; set; }\n\nParameters that configure the active learning pipeline. Active learning\nwill label the data incrementally via several iterations. For every\niteration, it will select a batch of data based on the sampling strategy.\n\n### AnnotationLabels\n\n public MapField\u003cstring, string\u003e AnnotationLabels { get; }\n\nLabels to assign to annotations generated by this DataLabelingJob.\n\nLabel keys and values can be no longer than 64 characters\n(Unicode codepoints), can only contain lowercase letters, numeric\ncharacters, underscores and dashes. International characters are allowed.\nSee \u003chttps://goo.gl/xmQnxf\u003e for more information and examples of labels.\nSystem reserved label keys are prefixed with \"aiplatform.googleapis.com/\"\nand are immutable.\n\n### CreateTime\n\n public Timestamp CreateTime { get; set; }\n\nOutput only. Timestamp when this DataLabelingJob was created.\n\n### CurrentSpend\n\n public Money CurrentSpend { get; set; }\n\nOutput only. Estimated cost(in US dollars) that the DataLabelingJob has\nincurred to date.\n\n### DataLabelingJobName\n\n public DataLabelingJobName DataLabelingJobName { get; set; }\n\n[DataLabelingJobName](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.DataLabelingJobName)-typed view over the [Name](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.DataLabelingJob#Google_Cloud_AIPlatform_V1Beta1_DataLabelingJob_Name) resource name property.\n\n### Datasets\n\n public RepeatedField\u003cstring\u003e Datasets { get; }\n\nRequired. Dataset resource names. Right now we only support labeling from a\nsingle Dataset. Format:\n`projects/{project}/locations/{location}/datasets/{dataset}`\n\n### DatasetsAsDatasetNames\n\n public ResourceNameList\u003cDatasetName\u003e DatasetsAsDatasetNames { get; }\n\n[DatasetName](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.DatasetName)-typed view over the [Datasets](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.DataLabelingJob#Google_Cloud_AIPlatform_V1Beta1_DataLabelingJob_Datasets) resource name property.\n\n### DisplayName\n\n public string DisplayName { get; set; }\n\nRequired. The user-defined name of the DataLabelingJob.\nThe name can be up to 128 characters long and can consist of any UTF-8\ncharacters.\nDisplay name of a DataLabelingJob.\n\n### EncryptionSpec\n\n public EncryptionSpec EncryptionSpec { get; set; }\n\nCustomer-managed encryption key spec for a DataLabelingJob. If set, this\nDataLabelingJob will be secured by this key.\n\nNote: Annotations created in the DataLabelingJob are associated with\nthe EncryptionSpec of the Dataset they are exported to.\n\n### Error\n\n public Status Error { get; set; }\n\nOutput only. DataLabelingJob errors. It is only populated when job's state\nis `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.\n\n### Inputs\n\n public Value Inputs { get; set; }\n\nRequired. Input config parameters for the DataLabelingJob.\n\n### InputsSchemaUri\n\n public string InputsSchemaUri { get; set; }\n\nRequired. Points to a YAML file stored on Google Cloud Storage describing\nthe config for a specific type of DataLabelingJob. The schema files that\ncan be used here are found in the\n\u003chttps://storage.googleapis.com/google-cloud-aiplatform\u003e bucket in the\n/schema/datalabelingjob/inputs/ folder.\n\n### InstructionUri\n\n public string InstructionUri { get; set; }\n\nRequired. The Google Cloud Storage location of the instruction pdf. This\npdf is shared with labelers, and provides detailed description on how to\nlabel DataItems in Datasets.\n\n### LabelerCount\n\n public int LabelerCount { get; set; }\n\nRequired. Number of labelers to work on each DataItem.\n\n### LabelingProgress\n\n public int LabelingProgress { get; set; }\n\nOutput only. Current labeling job progress percentage scaled in interval\n\\[0, 100\\], indicating the percentage of DataItems that has been finished.\n\n### Labels\n\n public MapField\u003cstring, string\u003e Labels { get; }\n\nThe labels with user-defined metadata to organize your DataLabelingJobs.\n\nLabel keys and values can be no longer than 64 characters\n(Unicode codepoints), can only contain lowercase letters, numeric\ncharacters, underscores and dashes. International characters are allowed.\n\nSee \u003chttps://goo.gl/xmQnxf\u003e for more information and examples of labels.\nSystem reserved label keys are prefixed with \"aiplatform.googleapis.com/\"\nand are immutable. Following system labels exist for each DataLabelingJob:\n\n- \"aiplatform.googleapis.com/schema\": output only, its value is the \\[inputs_schema\\]\\[google.cloud.aiplatform.v1beta1.DataLabelingJob.inputs_schema_uri\\]'s title.\n\n### Name\n\n public string Name { get; set; }\n\nOutput only. Resource name of the DataLabelingJob.\n\n### SpecialistPools\n\n public RepeatedField\u003cstring\u003e SpecialistPools { get; }\n\nThe SpecialistPools' resource names associated with this job.\n\n### State\n\n public JobState State { get; set; }\n\nOutput only. The detailed state of the job.\n\n### UpdateTime\n\n public Timestamp UpdateTime { get; set; }\n\nOutput only. Timestamp when this DataLabelingJob was updated most recently."]]
