Before importing your custom metadata to Encord, we recommend that you import a metadata schema. Encord uses metadata schemas to validate custom metadata uploaded to Encord and to instruct Index and Active how to display your metadata.
To handle your custom metadata schema across multiple teams within the same organization, we recommend using namespacing for metadata keys in the schema. This ensures that different teams can define and manage their own metadata schema without conflicts. For example, team A could use video.description, while team B could use audio.description. Another example could be TeamName.MetadataKey. This approach maintains clarity and avoids key collisions across departments.

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Benefits of Using a Metadata Schema

Using a metadata schema provides several benefits:
  • Validation: Ensures that all custom metadata conforms to predefined data types, reducing errors during data registration and processing.
  • Consistency: Maintains uniformity in data types across different datasets and projects, which simplifies data management and analysis.
  • Filtering and Sorting: Enhances the ability to filter and sort data efficiently in the Encord platform, enabling more accurate and quick data retrieval.

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Metadata Schema Table

Metadata Schema keys support letters (a-z, A-Z), numbers (0-9), and blank spaces ( ), hyphens (-), underscores (_), and periods (.). Metadata schema keys are case sensitive.
If you are unsure about the type to assign to a metadata key, we recommend using varchar as a versatile default.
Use .add_scalar() to add a scalar key to your metadata schema.
Scalar KeyDescriptionDisplay Benefits
booleanBinary data type with values “true” or “false”.Filtering by binary values
datetimeISO 8601 formatted date and time.Filtering by time and date
numberNumeric data type supporting float values.Filtering by numeric values
uuidUUIDv4 formatted unique identifier for a data unit.Filtering by customer specified unique identifier
varcharTextual data type. Formally string. string can be used as an alias for varchar, but we STRONGLY RECOMMEND that you use varchar.Filtering by string.
textText data with unlimited length (example: transcripts for audio). Formally long_string. long_string can be used as an alias for text, but we STRONGLY RECOMMEND that you use text.Storing and filtering large amounts of text.
Use add_enum and add_enum_options to add an enum and enum options to your metadata schema.
KeyDescriptionDisplay Benefits
enumEnumerated type with predefined set of values.Facilitates categorical filtering and data validation
Use add_embedding to add an embedding to your metadata schema.
KeyDescriptionDisplay Benefits
embedding1 to 4096 for Index. 1 to 2000 for Active.Filtering by embeddings, similarity search, 2D scatter plot visualization (Coming Soon)
Incorrectly specifying a data type in the schema can cause errors when filtering your data in Index or Active. If you encounter errors while filtering, verify your schema is correct. If your schema has errors, correct the errors, re-import the schema, and then re-sync your Active Project.

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Import Your Metadata Schema to Encord


# Import dependencies
from encord import EncordUserClient
from encord.metadata_schema import MetadataSchema

SSH_PATH = "<file-path-to-ssh-private-key>"

# Authenticate with Encord using the path to your private key
user_client: EncordUserClient = EncordUserClient.create_with_ssh_private_key(
    ssh_private_key_path=SSH_PATH
)

# Create the schema
metadata_schema = user_client.metadata_schema()

# Add various metadata fields
metadata_schema.add_scalar("metadata_1", data_type="boolean")
metadata_schema.add_scalar("metadata_2", data_type="datetime")
metadata_schema.add_scalar("metadata_3", data_type="number")
metadata_schema.add_scalar("metadata_4", data_type="uuid")
metadata_schema.add_scalar("metadata_5", data_type="varchar")
metadata_schema.add_scalar("metadata_6", data_type="text")

# Add an enum field
metadata_schema.add_enum("my-enum", values=["enum-value-01", "enum-value-02", "enum-value-03"])

# Add embedding fields
metadata_schema.add_embedding('my-test-active-embedding', size=512)
metadata_schema.add_embedding('my-test-index-embedding', size=<values-from-1-to-4096>)

# Save the schema
metadata_schema.save()

# Print the schema for verification
print(metadata_schema)

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Verify Your Schema

After importing your schema to Encord we recommend that you verify that the import is successful. Run the following code to verify your metadata schema imported and that the schema is correct. 

# Import dependencies
from encord import EncordUserClient
from encord.metadata_schema import MetadataSchema

SSH_PATH = "<file-path-to-ssh-private-key>"

# Authenticate with Encord using the path to your private key
user_client: EncordUserClient = EncordUserClient.create_with_ssh_private_key(
    ssh_private_key_path=SSH_PATH
)

# Create the schema
metadata_schema = user_client.metadata_schema()

# Print the schema for verification
print(metadata_schema)

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Edit Schema Keys

You can change the data type of schema keys using the .set_scalar() method. The example below shows how to update the data type for multiple metadata fields.
Restore Schema Key
# Import dependencies
from encord import EncordUserClient
from encord.metadata_schema import MetadataSchema

SSH_PATH = "/Users/chris-encord/ssh-private-key.txt"

# Authenticate with Encord using the path to your private key
user_client: EncordUserClient = EncordUserClient.create_with_ssh_private_key(
    ssh_private_key_path=SSH_PATH
)

# Get your metadata schema
metadata_schema = user_client.metadata_schema()

# Edit various metadata fields
metadata_schema.set_scalar("metadata_1", data_type="number")
metadata_schema.set_scalar("metadata_2", data_type="boolean")
metadata_schema.set_scalar("metadata_3", data_type="boolean")

# Print the schema for verification
print(metadata_schema)

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Delete Schema Keys

Schema key options cannot be deleted. Instead, we recommend creating new schema key options to meet your needs and phasing out any that are no longer required.
You can delete schema keys using the .delete() method. There are two types of deletion: hard delete and soft delete. A hard delete permanently removes the key, making it impossible to restore. A soft delete allows you to restore the key later using the .restore_key() method. The following examples show hard delete and soft deletion of a schema key called Fruit. 
# Import dependencies
from encord import EncordUserClient
from encord.metadata_schema import MetadataSchema

SSH_PATH = "/Users/chris-encord/ssh-private-key.txt"

# Authenticate with Encord using the path to your private key
user_client: EncordUserClient = EncordUserClient.create_with_ssh_private_key(
    ssh_private_key_path=SSH_PATH
)

# Get your metadata schema
metadata_schema = user_client.metadata_schema()

metadata_schema.delete_key(k: "Fruit", hard: False)

# Print the schema for verification
print(metadata_schema)

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Restore Schema Keys

Keys that have been soft deleted can be restored using the .restore_key() method. The following example restores a schema key called Fruit.
Restore Schema Key
# Import dependencies
from encord import EncordUserClient
from encord.metadata_schema import MetadataSchema

SSH_PATH = "/Users/chris-encord/ssh-private-key.txt"

# Authenticate with Encord using the path to your private key
user_client: EncordUserClient = EncordUserClient.create_with_ssh_private_key(
    ssh_private_key_path=SSH_PATH
)

# Get your metadata schema
metadata_schema = user_client.metadata_schema()

metadata_schema.restore_key(k: "Fruit")

# Print the schema for verification
print(metadata_schema)