Datasets

Learn about datasets and how you create and use them in Data Labeling.

Datasets are core to Data Labeling. They are made up of data records and their associated labels.

Creating a Dataset

Learn how to create a dataset in Data Labeling.

  1. On the navigation menu, click Analytics and AI.
  2. Click Data Labeling.
  3. From the Datasets page in Data Labeling, click Create dataset.
  4. In the Add dataset details page, populate the fields as follows:
    Name
    Give the dataset a suitable name.
    Description
    (Optional) Give the dataset a relevant description that you can use to help search for it.
    Labeling instructions
    (Optional) Enter instructions and directions for your team labeling the data.
    Dataset format
    Click Images, Text, or Documents, depending on whether you want to label images, pieces of text, or documents.
    File type
    If you select Text as the dataset format, this field is displayed. Select TXT or CSV, depending on whether you want to label a text file or a CSV file.
    Annotation class
    Select one of the options, Single Label or Multiple Label, for images, text, or documents. Images and text each have a different third option, Object Detection for images and Entity Extraction for text.
    Tags
    (Optional) If using tags, select a Tag Namespace and populate Tag Key and Value. You can add more tags by clicking + Another Tag and populating Tag Namespace, Tag Key, and Value.
    Note

    The system generates two tags, CreatedBy and CreatedOn, when you create the dataset.
  5. Click Next.
  6. In the Add files page, click Upload local files or Select from Object Storage.
    • To upload local files:
      1. Populate the Object Storage destination where you load the local files:
        Object Storage URL
        A read-only field.
        Compartment
        Choose the compartment from the list.
        Namespace
        Auto-populated based on the compartment selected.
        Bucket
        Click the field, and select a bucket from the list. If the list is long, you can choose to view all buckets. If you click it, a panel opens listing all the available buckets. If you need to create a bucket, click the link in the tooltip.
        (Optional) Prefix
        Enter a prefix string added to the start of the files' names or paths. Use it to limit the files returned.
      2. Drag and drop the files you want to load.
        • If the files to load are not CSV format:
          • Drag and drop them to Selected Files, or click select files... to select the files from your file manager.
        • If the files to load are CSV format:
            1. Select the Column delimiter. If you choose Custom, enter it in Custom column delimiter.
            2. (Optional) Select the Line delimiter. If you choose Custom, enter it in Custom line delimiter. If you leave it empty, it is detected from the CSV file.
            3. (Optional) Select the Escape character. If you choose Custom, enter it in Custom escape character. If you leave it empty, then none of the text is escaped.
          1. Drag and drop the files to Selected files, or click select files... to select the files from your file manager.
            Note

            All the files must be UTF-8 encoded and have the same column headers and indexes. If not, the dataset goes into the Needs Attention state.
          2. Select a file to display a preview of its contents.
            Note

            Only the first five columns and rows are displayed.
          3. For the column you want to label, select its Column name. If the column has no name, the index number is displayed instead.
      Note

      You can load no more than 100 local files at a time in the Console. The number of files selected is displayed. If you want to load more files at a time, either load them into Object Storage before creating the dataset, or use the CLI or SDK.
    • To load files from Object Storage:
      1. In Object Storage location populate the fields as follows:
        Object Storage URL
        A read-only field, already populated.
        Compartment
        Choose the compartment from the list.
        Namespace
        Auto-populated based on the compartment selected.
        Bucket
        Click the field, and select a bucket from the list. If the list is long, you can choose to View all buckets. If you click it, a panel opens listing all the available buckets.
        (Optional) Prefix
        Enter a prefix string added to the start of the files' names or paths. Use it to limit the files returned.
      2. (Optional) If using CSV format:
        1. Select the Column delimiter. If you choose Custom, enter it in Custom column delimiter.
        2. (Optional) Select the Line delimiter. If you choose Custom, enter it in Custom line delimiter. If you leave it empty, it is detected from the CSV file.
        3. (Optional) Select the Escape character. If you choose Custom, enter it in Custom escape character. If you leave it empty, then none of the text is escaped.
        4. Select a file to display a preview of its contents.
          Note

          Only the first five columns and rows are displayed.
        5. Select the Column name of the column to be labeled. If the column has no name, the index number is displayed instead.
        Note

        All the files must be UTF-8 encoded and have the same column headers and indexes. If not, the dataset goes into the Needs Attention state.
      See Supported File Formats for the list of allowed file formats.
  7. In Labels enter the labels to use with your dataset. After entering each label, press Return.
  8. Click Next.
  9. In the Review page, check Dataset details and Files and Labels. If the dataset details need editing, click Edit. If the files and labels details need editing, click Edit.
  10. Click Create.
    The records are generated when the dataset is created. The dataset state changes to Updating while the records are generated.

Editing a Dataset

Follow these steps to edit a dataset in Data Labeling.

  1. On the Datasets page:
    • Click the name of the dataset you want to edit.
    • Or click the action icon at the end of the row for the dataset, and click View details from the menu.
  2. In the Dataset Details page, click Edit to display the Edit Dataset page.
  3. In Edit Dataset, you can update the Name, Description, or Labeling instructions.
  4. All the fields in Object Storage location are read-only.
  5. In Selected files you can add new files by dragging and dropping them on the area, or by clicking select files.. to select them from your file manager.
    Note

    You can load no more than 100 local files at a time in the Console. The number of files selected is displayed. If you want to load more files at a time, either load them into Object Storage before creating the dataset, or use the CLI or SDK.
    Note

    If the dataset contains CSV files, any CSV files added are parsed as for the files already in the dataset.
  6. Click Save changes to save your changes, or click Cancel to cancel them.
    If you added files, record generation starts automatically when you click Save changes.

Adding Labels to a Dataset

Apart from adding labels when creating a dataset, you can add labels to a dataset after it is created. You can add labels to a dataset from the Dataset Details page, or from the Labeling screen.

  1. (Optional) From the Dataset Details page, click Add labels.
  2. (Optional) From the Labeling screen, click +Label in the Labels panel.
  3. On the Add Label dialog box, enter a new label in Label set.
    Note

    The maximum limit number of labels is 255. They are all listed under Label set, including the existing ones.
  4. Click Add when you have added all the labels.

Adding Tags to a Dataset

You can add tags to a dataset in Data Labeling.

  1. From the Dataset details page, click More Actions, and click Add Tags.
  2. A pop up window, Add Tags, displays. Select the Tag Namespace.
  3. Add the Tag Key and Value.
  4. (Optional) Click + Another Tag to add more tags.
  5. Click Add Tags when done.

Deleting a Dataset

There are two ways to delete a dataset in Data Labeling.

  1. On the Datasets page, click the action icon at the end of the row for the datset, and select Delete from the menu.
  2. Or, on the Datasets page, click the name of the dataset you want to delete. In the Dataset Details page, click More Actions and select Delete from the menu.
    Note

    When you delete a dataset, you delete all records and annotations in it.

Exporting the Dataset

You can export datasets in Data Labeling in various text and image formats, and snapshot JSONL files.

You can export datasets in Data Labeling to any Object Storage location in the tenancy. Thus, you can maintain versions, or use the dataset elsewhere, for example, as an input to machine learning model development. The output file location is included in the export panel. After export, the destination is available in the associated work request. The destination is also displayed in the Dataset Details page, but only while the work request exists.

For documents, you can export to JSONL files.

For images, you have the choice of exporting to the following file formats:
  • JSONL
  • YOLO V5
  • COCO
  • PASCAL VOC
For text, you have the choice of exporting to the following file formats:
  • JSONL
  • JSONL Compact Plus Content
  • spaCy
  • CoNLL V2003
    Note

    If you export text in the CoNLL format, recursive and overlapping entities are ignored.
Note

For CSV, the only option is to export to JSONL.
  1. In the dataset details page, click Export to display the Export Dataset panel.
  2. Namespace is read-only and shows where the JSON files are stored.
  3. Choose export file format.
  4. (Optional) To change the compartment where the Object Storage bucket resides, click Change Compartment.
  5. Select the Bucket from the list.
  6. (Optional) Enter a Prefix.
    The exported dataset files are stored starting with this path prefix.
  7. (Optional) To export all records, including those records yet to be labeled, click Include unlabeled records to export.
  8. (Optional) To export the dataset and records as a single file, click Consolidate dataset and record file into a single file.
    Note

    This option is only available for JSONL files, and is disabled for other export formats.
  9. Click Export dataset.

Examples of Exported Document, Image, and Text Datasets

Examples of the the JSON files created when a dataset is exported in Data Labeling.

Example of an Exported Consolidated JSON File

An example of an exported consolidated JSON file.

{
	"id": "ocid1.datalabelingdatasetdev.oc1.iad.amaaaaaazaehrjyag7jcbu3xnpw4dcn3tmniarzorpxbtegnipsw5oleeauq",
	"compartmentId": "ocid1.compartment.oc1..aaaaaaaaihdqc5z4zq4sqt7t4c7vbwc6lbf5dr6mky2phcpvdlh7c3p5mtuq",
	"displayName": "test-check",
	"description": "test  check",
	"labelsSet": [{
		"name": "location"
	}, {
		"name": "university"
	}],
	"annotationFormat": "ENTITY_EXTRACTION",
	"datasetSourceDetails": {
		"namespace": "idrcdhfxwqwa",
		"bucket": "test-sachin-cucket"
	},
	"datasetFormatDetails": {
		"formatType": "TEXT"
	}
} {
	"id": "ocid1.datalabelingrecord.oc1.iad.amaaaaaazaehrjyahykmu6hvdksayw64a3wmur7mk2366hgitlypk6u2soea",
	"timeCreated": "2021-10-12 12:09:37",
	"sourceDetails": {
		"sourceType": "OBJECT_STORAGE",
		"path": "sample-text.txt"
	},
	"annotations": [{
		"id": "ocid1.datalabelingannotation.oc1.iad.amaaaaaazaehrjyat64zcfbjviu3pttykthabv5jiuicva3dkv6oikstzd7q",
		"timeCreated": "2021-10-12 12:16:51",
		"createdBy": "ocid1.user.oc1..aaaaaaaaktqgvx2skco6bfyziwjzfjaxensoewscqbk7p44sjqyrxmz4qozq",
		"entities": [{
			"entityType": "TEXTSELECTION",
			"labels": [{
				"label_name": "university"
			}],
			"textSpan": {
				"offset": 60,
				"length": 11
			}
		}]
	}]
}
Example of an Exported Document Dataset JSON File

An example of an exported document dataset JSON file.

{
   "id":"ocid1.datalabelingdatasetint.oc1.iad.amaaaaaaniob46iafkiyw6a4uwgrnpy4lfxjoslocap7elaj257mxh4fzuwq",
   "compartmentId":"ocid1.compartment.oc1..aaaaaaaajqiw27knoagxurhzjlihw7ijnoshsu4zi2uawdn5gfexdqwvu4vq",
   "displayName":"Sep6_PDF",
   "labelsSet":[
     {
          "name":"L1"
     },
     {
          "name":"L"
     },
     {
          "name":"23423"
     }
   ],
   "annotationFormat":"MULTI_LABEL",
   "datasetSourceDetails":{
      "namespace":"idgszs0xipmn",
      "bucket":"Demo-bucket"
   },
   "datasetFormatDetails":{"formatType":"DOCUMENT"},
   "recordFiles":[
      {
         "namespace":"idgszs0xipmn",
         "bucket":"COVID_Dataset",
         "path":"Snapshotsrecords_1632479104889.jsonl"
      }
   ]
}

Example of an Exported Image Dataset JSON File

An example of an exported image dataset JSON file.

{
     "id": "ocid1...",
     "compartmentId": "",
     "timeCreated":2020-12-15...,
     "displayName":...,
     "description":...,
     "labelsSet": [
          {"name":"germanshepherd"},
          {"name":"americanshepherd"},
          {"name":"australianshepherd"},
          {"name":"irishwolfhound"}
     ]
     "annotationFormat": "IMAGE_OBJECT_SELECTION",
     "datasetSourceDetails": {
          "sourceType": "OBJECT_STORAGE",
          "namespace": "i235o3idk",
          "bucket": "mytrainingdata",
          "prefix": "puppyproject/"
     }
     "datasetFormatDetails": {
          "formatType": "IMAGE" # image requires less metadata than delimited for example
     }
     "recordsFiles: {
          [
              {
              "namespace": "i235o3idk"
              "bucket": "mylabels"
              "path": "puppyproject/records1.json"
              }
          ]
     }
     "definedTags": {}
     "freeformTags": {}   
}
Example of an Exported Text Dataset JSON File

An example of an exported text dataset JSON file.

{
   "id":"ocid1.datalabelingdatasetdev.oc1.iad.amaaaaaazaehrjyamqjx733dhxd25zxcro2nftrewq7ltj34ua2cfapzsmjq",
   "compartmentId":"ocid1.compartment.oc1..aaaaaaaagzh2kii2frktoc7bcvfydpzkxr7dbn6nf6jcyrxwgzen4pi5y4zq",
   "displayName":"NER DEMO DATASET UNLABELLED",
   "description":"NER DEMO DATASET UNLABELLED",
   "labelsSet":[
      {
         "name":"Person"
      },
      {
         "name":"Organization"
      },
      {
         "name":"Event"
      },
      {
         "name":"Place"
      }
   ],
   "annotationFormat":"ENTITY_EXTRACTION",
   "datasetSourceDetails":{
      "namespace":"idrcdhfxwqwa",
      "bucket":"news-articles"
   },
   "datasetFormatDetails":{
       
   },
   "recordFiles":[
      {
         "namespace":"idrcdhfxwqwa",
         "bucket":"snapshots",
         "path":"forReview/records_1621847577526.jsonl"
      }
   ]
}

Example of an Exported Document Record JSON File

An example of an exported document record JSON file.

{
   "id":"ocid1.datalabelingrecord.oc1.iad.amaaaaaaniob46iaqgpzhscdpdcgohg5ocp3obwmjjgju6m73bmyrt4aovhq",
   "timeCreated":"2021-09-06 03:40:02",
   "sourceDetails":{
      "sourceType":"OBJECT_STORAGE",
      "path":"SampleDocs-sample-pdf-file copy 98.pdf"
   },
   "annotations":[
      {
         "id":"ocid1.datalabelingannotation.oc1.iad.amaaaaaaniob46iatjg3p6hlszxrgmsj4y76b5tndddaedm6ardkoxbtt6mq",
         "timeCreated":"2021-09-06 03:42:43",
         "createdBy":"ocid1.user.oc1..aaaaaaaa6ynps4htdea6fqoerfhkedp3lih2ktureqhw3hmfojde6ukf3mpa",
         "entities":[
            {
               "entityType":"GENERIC","labels":[
                  {
                     "label_name":"23423"
                  }
               ]
            }
         ]
      }
   ]
}{
   "id":"ocid1.datalabelingrecord.oc1.iad.amaaaaaaniob46iasb5klulgaj4djn3acsgsd3cekx3ix46ftxjdip4tu23a",
   "timeCreated":"2021-09-06 03:40:02",
   "sourceDetails":{
      "sourceType":"OBJECT_STORAGE",
      "path":"SampleDocs-sample-pdf-file copy 99.pdf"
   },
   "annotations":[
      {
         "id":"ocid1.datalabelingannotation.oc1.iad.amaaaaaaniob46iav45mlpcleqjt7cnmhyogopszi2rfnilwjhd4xyxa7irq",
         "timeCreated":"2021-09-06 03:42:47",
         "createdBy":"ocid1.user.oc1..aaaaaaaa6ynps4htdea6fqoerfhkedp3lih2ktureqhw3hmfojde6ukf3mpa",
         "entities":[
            {
               "entityType":"GENERIC","labels":[
                  {
                     "label_name":"L1"
                  }
               ]
            }
         ]
      }
   ]
}{
   "id":"ocid1.datalabelingrecord.oc1.iad.amaaaaaaniob46iaxhixolkqryomyu6i4jrrmzwcckw2tmgva47suylu5rzq",
   "timeCreated":"2021-09-06 03:40:02",
   "sourceDetails":{
      "sourceType":"OBJECT_STORAGE",
      "path":"SampleDocs-sample-pdf-file copy 97.pdf"
   }
}{
   "id":"ocid1.datalabelingrecord.oc1.iad.amaaaaaaniob46iagymrjuem42kvzilxjd5hdrr3djznrl7aajvvcr6zc6sq",
   "timeCreated":"2021-09-06 03:40:02",
   "sourceDetails":{
      "sourceType":"OBJECT_STORAGE",
      "path":"SampleDocs-sample-pdf-file copy 96.pdf"
   }
}{
   "id":"ocid1.datalabelingrecord.oc1.iad.amaaaaaaniob46iaclpccpxn5hgmplesv3mt3g6hxkfaepzv6fuy7b6he3ca",
   "timeCreated":"2021-09-06 03:40:02",
   "sourceDetails":{
      "sourceType":"OBJECT_STORAGE",
      "path":"SampleDocs-sample-pdf-file copy 2.pdf"
   }
}
Example of an Exported Image Record JSON File

An example of an exported image record JSON file.

{
    "id": "ocid1...",
    "timeCreated": 2020-12-15...,
    "sourceDetails": {
         "sourceType": "OBJECT_STORAGE",
         "path": "filename2.jpg"
    }
    "annotations": [
        {
            "id": "ocid1....",
            "timeCreated": ...,
            "createdBy": ...,
            "entities: [
                {
                    "entityType": "IMAGEOBJECTSELECTION",
                    "labels": [
                        {"name": "germanshepherd"}
                    ],
                    "boundingPolygon": {
                        normalizedVertices: [
                            {"x":0.2, "y":0.2},
                            {"x":0.3, "y":0.2},
                            {"x":0.3, "y":0.3},
                            {"x":0.2, "y":0.3}
                        ]
                    }
                },
                {
                    "entityType": "BOUNDING_BOX",
                    "labels": [
                        {"name": "irishwolfhound"}
                    ],
                    "boundingPolygon": {
                        normalizedVertices: [
                            {"x":0.4, "y":0.4},
                            {"x":0.5, "y":0.4},
                            {"x":0.5, "y":0.5},
                            {"x":0.4, "y":0.5}
                        ]
                    }
                }
            ]
        }
    ],
    "freeformTags": {
        "set": "validation" # optional, user defined convention used for reproducibility
    }
}
Example of an Exported Text Record JSON File

An example of an exported text record JSON file.

{
   "id":"ocid1.record.oc1.iad.UxxfPBMZVYfwZHZnjCPUGkhMwpWoTPMOnxDnrgXbBxwLKkrdeGwewdViOoUJ",
   "timeCreated":"2021-06-21 09:06:01",
   "sourceDetails":{
      "sourceType":"OBJECT_STORAGE",
      "path":"article_3.txt"
   },
   "annotations":[
      {
         "id":"ocid1.datalabelingannotation.oc1.iad.amaaaaaazaehrjyadghacojq3nmo2mtcbcmlo4rgslmpzxeboujhduft5nta",
         "timeCreated":"2021-46-21 09:46:45",
         "createdBy":"ocid1.user.oc1..aaaaaaaazjupiis2cu54smlzemiujpqxriz6i4wp3euuqrzffdugib73epbq",
         "entities":[
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Event"
                  }
               ],
               "textSpan":{
                  "offset":141,
                  "length":12
               }
            },
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Organization"
                  }
               ],
               "textSpan":{
                  "offset":204,
                  "length":20
               }
            },
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Person"
                  }
               ],
               "textSpan":{
                  "offset":254,
                  "length":15
               }
            },
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Organization"
                  }
               ],
               "textSpan":{
                  "offset":402,
                  "length":3
               }
            },
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Place"
                  }
               ],
               "textSpan":{
                  "offset":638,
                  "length":11
               }
            }
         ]
      }
   ]
}{
   "id":"ocid1.record.oc1.iad.AakCoDHvJpnZofzIYfRCfpZnFUqNmfiWNIuNysbXCSRZeTVqdwKGvYjJpMvh",
   "timeCreated":"2021-06-21 09:06:01",
   "sourceDetails":{
      "sourceType":"OBJECT_STORAGE",
      "path":"article_1.txt"
   },
   "annotations":[
      {
         "id":"ocid1.datalabelingannotation.oc1.iad.amaaaaaazaehrjyafoed6oimxqxeyey6osjo3jp52vsyd75i5zspfvcfdz3q",
         "timeCreated":"2021-30-21 03:30:10",
         "createdBy":"ocid1.user.oc1..aaaaaaaazjupiis2cu54smlzemiujpqxriz6i4wp3euuqrzffdugib73epbq",
         "entities":[
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Person"
                  }
               ],
               "textSpan":{
                  "offset":36,
                  "length":8
               }
            },
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Person"
                  }
               ],
               "textSpan":{
                  "offset":147,
                  "length":23
               }
            },
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Organization"
                  }
               ],
               "textSpan":{
                  "offset":196,
                  "length":3
               }
            },
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Event"
                  }
               ],
               "textSpan":{
                  "offset":311,
                  "length":22
               }
            },
            {
               "entityType":"TEXTSELECTION",
               "labels":[
                  {
                     "label_name":"Place"
                  }
               ],
               "textSpan":{
                  "offset":512,
                  "length":49
               }
            }
         ]
      }
   ]
}
Example of an Exported CSV Text Dataset JSON File

An example of an exported CSV (text) dataset JSON file.

{
	"id": "ocid1.datalabelingdatasetint.oc1.phx.amaaaaaaniob46iaxarhafiu42tbdm2d2nkxlkxwhnc76ohnwvpsdfccqw5q",
	"compartmentId": "ocid1.compartment.oc1..aaaaaaaaundh4v2w4spnyt4hgy367qf54jonakpz6gh573bspmgzfoj2auga",
	"displayName": "Text Classification CSV dataset",
	"labelsSet": [{
		"name": "positive"
	}, {
		"name": "neutral"
	}, {
		"name": "negative"
	}],
	"annotationFormat": "SINGLE_LABEL",
	"datasetSourceDetails": {
		"namespace": "idgszs0xipmn",
		"bucket": "TEST",
		"prefix": "languageteam/Text_Classification_Context_Oracle_advt.csv"
	},
	"datasetFormatDetails": {
		"formatType": "TEXT",
		"textFileTypeMetadata": {
			"formatType": "DELIMITED",
			"delimitedFileTypeMetaData": {
				"columnIndex": 5,
				"columnName": "CONTENT",
				"columnDelimiter": ","
			}
		}
	}
} {
	"id": "ocid1.datalabelingrecord.oc1.phx.amaaaaaaniob46iajx42mojwkktind744i3t2q3di6tdhwysw2wy4d42tseq",
	"timeCreated": "2022-06-05 04:39:18",
	"sourceDetails": {
		"sourceType": "OBJECT_STORAGE",
		"path": "/546"
	},
	"annotations": [{
		"id": "ocid1.datalabelingannotation.oc1.phx.amaaaaaaniob46iadsu6zpch4lvozx7ci3as5st23jqxjpjdcryp4jworala",
		"timeCreated": "2022-06-05 05:40:48",
		"createdBy": "ocid1.user.oc1..aaaaaaaaavjgmgh67ndbznlhnuxhzswfbwcpd5tlvugskeeqt7noudcu7xha",
		"entities": [{
			"entityType": "GENERIC",
			"labels": [{
				"label_name": "neutral"
			}]
		}]
	}]
} {
	"id": "ocid1.datalabelingrecord.oc1.phx.amaaaaaaniob46ia7otgs2rb3kuh464sisfbjxxbbkb65sbg2icst3gquw3q",
	"timeCreated": "2022-06-05 04:39:18",
	"sourceDetails": {
		"sourceType": "OBJECT_STORAGE",
		"path": "/303"
	},
	"annotations": [{
		"id": "ocid1.datalabelingannotation.oc1.phx.amaaaaaaniob46iatfuceqzjb5nnh7quk5wupvwe74bfpn5oka57cz6gqv4a",
		"timeCreated": "2022-06-05 05:41:30",
		"createdBy": "ocid1.user.oc1..aaaaaaaaavjgmgh67ndbznlhnuxhzswfbwcpd5tlvugskeeqt7noudcu7xha",
		"entities": [{
			"entityType": "GENERIC",
			"labels": [{
				"label_name": "neutral"
			}]
		}]
	}]
} {
	"id": "ocid1.datalabelingrecord.oc1.phx.amaaaaaaniob46iab55fqcxlfb3xszlpp7qnpsthjdhzzb7nki65xqdvgceq",
	"timeCreated": "2022-06-05 04:39:18",
	"sourceDetails": {
		"sourceType": "OBJECT_STORAGE",
		"path": "/547"
	},
	"annotations": [{
		"id": "ocid1.datalabelingannotation.oc1.phx.amaaaaaaniob46iamosgunt72lci3g3mzyyx2sskjdje4e5zspts7mbnsl5q",
		"timeCreated": "2022-06-05 05:41:36",
		"createdBy": "ocid1.user.oc1..aaaaaaaaavjgmgh67ndbznlhnuxhzswfbwcpd5tlvugskeeqt7noudcu7xha",
		"entities": [{
			"entityType": "GENERIC",
			"labels": [{
				"label_name": "neutral"
			}]
		}]
	}]
} {
	"id": "ocid1.datalabelingrecord.oc1.phx.amaaaaaaniob46ia45ave4zhtisvu2k7d6tbciskcge4ecm2imb6bvdqe4da",
	"timeCreated": "2022-06-05 04:39:21",
	"sourceDetails": {
		"sourceType": "OBJECT_STORAGE",
		"path": "/564"
	},
	"annotations": [{
		"id": "ocid1.datalabelingannotation.oc1.phx.amaaaaaaniob46iauqo6tlqil7vijetsayt6vsmpohxum5vmj6cde3wbfxua",
		"timeCreated": "2022-06-05 05:40:44",
		"createdBy": "ocid1.user.oc1..aaaaaaaaavjgmgh67ndbznlhnuxhzswfbwcpd5tlvugskeeqt7noudcu7xha",
		"entities": [{
			"entityType": "GENERIC",
			"labels": [{
				"label_name": "positive"
			}]
		}]
	}]
} {
	"id": "ocid1.datalabelingrecord.oc1.phx.amaaaaaaniob46iasymkpbstgjwmae7ar5ikgp5mtth2izcaaaruatpl45ma",
	"timeCreated": "2022-06-05 04:39:18",
	"sourceDetails": {
		"sourceType": "OBJECT_STORAGE",
		"path": "/545"
	},
	"annotations": [{
		"id": "ocid1.datalabelingannotation.oc1.phx.amaaaaaaniob46iatu6k7afdwirdtvv6bofrquc65m4ruet4hlfmhgzhqjxa",
		"timeCreated": "2022-06-05 05:41:02",
		"createdBy": "ocid1.user.oc1..aaaaaaaaavjgmgh67ndbznlhnuxhzswfbwcpd5tlvugskeeqt7noudcu7xha",
		"entities": [{
			"entityType": "GENERIC",
			"labels": [{
				"label_name": "positive"
			}]
		}]
	}]
} {
	"id": "ocid1.datalabelingrecord.oc1.phx.amaaaaaaniob46ia6n4whohdhn257pmot7zlncawockthadosdhrp5so2nna",
	"timeCreated": "2022-06-05 04:39:18",
	"sourceDetails": {
		"sourceType": "OBJECT_STORAGE",
		"path": "/304"
	},
	"annotations": [{
		"id": "ocid1.datalabelingannotation.oc1.phx.amaaaaaaniob46iaslgb6s6h5ffce5mcgeidndp3vydcxzjya7yrbaj6pw5a",
		"timeCreated": "2022-06-05 05:40:57",
		"createdBy": "ocid1.user.oc1..aaaaaaaaavjgmgh67ndbznlhnuxhzswfbwcpd5tlvugskeeqt7noudcu7xha",
		"entities": [{
			"entityType": "GENERIC",
			"labels": [{
				"label_name": "negative"
			}]
		}]
	}]
} {
	"id": "ocid1.datalabelingrecord.oc1.phx.amaaaaaaniob46iamgsncrjarzujr6duaedmsjyrp67yi7dpe2uoi6h54c5a",
	"timeCreated": "2022-06-05 04:39:18",
	"sourceDetails": {
		"sourceType": "OBJECT_STORAGE",
		"path": "/548"
	},
	"annotations": [{
		"id": "ocid1.datalabelingannotation.oc1.phx.amaaaaaaniob46iabt3hwyc7mkaanez7q24k7vlfds3lisa6hdu53hntq2qq",
		"timeCreated": "2022-06-05 05:42:55",
		"createdBy": "ocid1.user.oc1..aaaaaaaaavjgmgh67ndbznlhnuxhzswfbwcpd5tlvugskeeqt7noudcu7xha",
		"entities": [{
			"entityType": "GENERIC",
			"labels": [{
				"label_name": "positive"
			}]
		}]
	}]
} {
	"id": "ocid1.datalabelingrecord.oc1.phx.amaaaaaaniob46iactsl4j7v633d2y2t67lkxawv2nyemz7wwarppjpxeofq",
	"timeCreated": "2022-06-05 04:39:18",
	"sourceDetails": {
		"sourceType": "OBJECT_STORAGE",
		"path": "/305"
	},
	"annotations": [{
		"id": "ocid1.datalabelingannotation.oc1.phx.amaaaaaaniob46ia7xxg4ukky3ur56zzwaodvwrks4vqgvoug2z2moif274a",
		"timeCreated": "2022-06-05 05:41:44",
		"createdBy": "ocid1.user.oc1..aaaaaaaaavjgmgh67ndbznlhnuxhzswfbwcpd5tlvugskeeqt7noudcu7xha",
		"entities": [{
			"entityType": "GENERIC",
			"labels": [{
				"label_name": "negative"
			}]
		}]

Moving the Dataset to another Compartment

You can move the dataset from one compartment to another.

  1. In the dataset details page, click More Actions.
  2. Click Move Resource.
  3. Select a new compartment from the list, Choose New Compartment.
  4. Click Move Resource.

Dataset Tags

You can tag datasets in Data Labeling to make them easier to find.

When Creating a Dataset, you can add tags to help you identify and classify your datasets. Two tags are always created by default when a dataset is created. They are:
  • CreatedBy, which gives the user id of who created the dataset.
  • CreatedOn, which gives the date timestamp of when the dataset was created.
As is explained in Adding Tags to a Dataset, you can also add them to a dataset once it is created.

You can see the tags on a dataset by clicking the Tags tab on the dataset details page.

Editing Dataset Tags

Follow these steps to edit the tags on a dataset in Data Labeling.

  1. From the dataset details page, click the Tags tab.
  2. Click the Edit icon next to the tag you want to edit.
    The Edit Tag pop up windows displays.
  3. (Optional) Change the tag value and click Save.
  4. (Optional) Delete the tag by clicking Remove Tag.

Supported File Formats

Data Labeling supports various file formats and content types.

  • For documents, JPEG, JPG, PNG, PDF, TIF, and TIFF files are supported.
  • For images, JPEG, JPG, and PNG files are supported.
  • For text, CSV, TEXT, and TXT files are supported.
    Note

    English is the only language supported for text files.

Maximum File Sizes and Content Types

Supported File Sizes and Content Types
File Type Content Type Maximum File Size
CSV text/csv 5 MB
JPEG, JPG image/jpeg 6 MB
PDF application/pdf 50 MB
PNG image/png 6 MB
TEXT, TXT text/plain 2 MB
TIF, TIFF image/tiff 50 MB

Dataset in Needs Attention State

If an action on a Dataset leaves it with a state of Needs Attention, try the following.

  • Attempt the action again. All buttons on the dataset details page are enabled.
  • Find out if there is a problem that needs resolving by Viewing Work Requests related to the action attempted. Any error messages, or content in the log files, should help you.
If a dataset is in this state, a message alerting the user to it displays at the top of the screen.