--- title: "Schema creation and management" slug: "aitems-schema" tags: ["AiTEMS", "schema"] updated: 2026-09-17T09:33:47Z published: 2026-09-17T09:33:47Z canonical: "guide.ncloud-docs.com/aitems-schema" stale: true --- > ## Documentation Index > Fetch the complete documentation index at: https://guide.ncloud-docs.com/llms.txt > Use this file to discover all available pages before exploring further. # Schema creation and management Available in Classic and VPC The Schema creation and management section describes how to create and delete schemas, as well as how to duplicate an existing schema to create a new one. ## Creating a schema To create a schema: Note You can also create a schema when creating a dataset. For details, see [Creating a dataset](/docs/en/aitems-dataset#%EB%8D%B0%EC%9D%B4%ED%84%B0%EC%85%8B%EC%83%9D%EC%84%B1). 1. Navigate to **Menu** > **All Services** > **AI Services** > **AiTEMS** in the NAVER Cloud Platform console. 2. Click the **Schema** menu. 3. Click the **[Create schema]** button. 4. When the Create schema interface appears, select the dataset type. - The Basic schema information section appears. 5. Enter the schema name and description. - The schema name is used as the management key for the schema. It must begin with an English letter and can contain English letters, numbers, _, and -. Enter 3 to 20 characters. 6. Enter the field information for the schema and click the **[Add]** button. - Required fields are set automatically and cannot be modified or deleted. The required fields are listed below. | Dataset Type | Required Fields (Not NULL) | Reserved Words | | --- | --- | --- | | user | USER_ID (string) | - | | item | ITEM_ID (string) | CATEGORY (String) CREATION_TIMESTAMP (long) | | interaction | USER_ID (string) ITEM_ID (string) TIMESTAMP (long) | EVENT_TYPE(String) EVENT_VALUE(null) | - **Field name**: Enter the field name exactly as it appears in the dataset file. - **Field type**: Select the data type to input (**string**/**float**/**long**/**double**/**int**/**boolean**/**null**) - **Categorical field**: Set to **Y** when entering data with predefined categories. - You can drag and drop ![i-aitems_order](https://cdn.document360.io/6998976f-9d95-4df8-b847-d375892b92c2/Images/Documentation/i-aitems_order.png?sv=2026-02-06&spr=https&st=2026-11-14T04%3A50%3A32Z&se=2026-11-14T05%3A50%3A32Z&sr=c&sp=r&sig=G1Oa3SokZxRPoJar5EpchIb%2FnPEbqK7W%2Fx7XzZCcIJw%3D) to change the order of the fields. 7. Click **[Create]** button. - The schema is created and added to the list. ## Duplicating a schema You can duplicate an existing schema to create a new one. Note When duplicating an existing schema, you cannot change the dataset type. To duplicate a schema: 1. Navigate to **Menu** > **All Services** > **AI Services** > **AiTEMS** in the NAVER Cloud Platform console. 2. Click the **Schema** menu. 3. In the schema list, click the schema you want to duplicate. 4. Click the **[Duplicate schema]** button. 5. When the Duplicate schema popup appears, edit the schema name. 6. Configure the schema fields. - For more details about configuring field information, see [Creating a schema](/docs/en/aitems-schema#%EC%8A%A4%ED%82%A4%EB%A7%88%EC%83%9D%EC%84%B1). 7. Click the **[Duplicate]** button. 8. In the notification popup, click **[OK]** button. - The duplicated schema appears in the list. ## Deleting a schema To delete a schema: Note You cannot delete a schema that is connected to a dataset. [Delete the relevant dataset](/docs/en/aitems-dataset#%EB%8D%B0%EC%9D%B4%ED%84%B0%EC%85%8B%EC%82%AD%EC%A0%9C) or [change the schema](/docs/en/aitems-dataset#%EB%8D%B0%EC%9D%B4%ED%84%B0%EC%85%8B%EC%88%98%EC%A0%95) connected to that dataset before deleting the schema. 1. Navigate to **Menu** > **All Services** > **AI Services** > **AiTEMS** in the NAVER Cloud Platform console. 2. Click the **Schema** menu. 3. In the schema list, click the schema you want to delete. 4. Click the **[Delete schema]** button. 5. When the schema popup appears, enter the name of the schema you want to delete and click **[Delete]** button. - The schema is deleted and removed from the list.