---
title: "Filter Items"
slug: "filter-items"
tags: ["Schema Search"]
updated: 2026-08-05T08:28:41Z
published: 2026-08-05T08:28:41Z
canonical: "docs.dataloop.ai/filter-items"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dataloop.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Filter Items

## Overview

The **DDOE Dataset Browser** is a powerful interface that enables users to efficiently search, filter, and refine datasets to identify required items with ease. It provides multiple levels of search functionality, ranging from simple searches to advanced queries, ensuring flexibility for diverse user needs.

The Dataset Browser is a versatile tool that supports:

- Filtering by item, annotation, and task properties.
- Natural language semantic search via CLIP.
- Multi-level search approaches (Basic, Advanced, and DQL).
- Task-specific filtering for assignment management.

---

## Filter Modes

The Dataset Browser supports three primary search modes: **Basic Search**, **Advanced Search**, and **DQL Query Editor Search**.

Also supports, Saved Filters search, Semantic Search, etc.

1. **Basic Search**
2. **Advanced Search**
3. **DQL**
4. **Semantic Search**
5. [Collections](https://docs.dataloop.ai/docs/organize-your-data#collections)
6. [ML Subsets](https://docs.dataloop.ai/docs/organize-your-data#ml-subsets)
7. [Tasks and Statuses](https://docs.dataloop.ai/docs/filter-your-data#tasks-statuses)
8. [Saved Filters (if available)](https://docs.dataloop.ai/docs/filter-your-data#saved-filters)

---

## Basic Search

The **Basic Search** feature enables quick filtering and discovery of items using predefined parameters. It helps you easily locate items by applying simple conditions such as labels, attributes, status, users, and more.

Available pre-defined search filters are:

- **Annotated**: allows to search annotated items or not annotated items.
- **Attributes**: allows to search annotated items with attributes.
- **Labels**: allows to search annotated items with specific labels.

Clicking on the ![](https://cdn.document360.io/53f32fe9-1937-4652-8526-90c1bc78d3f8/Images/Documentation/db_add_more.png) allows you to **Add more** search types into the query.

| Search Criterias | Description |
| --- | --- |
| **Search by Labels** | Find items by selecting a specific label from the list. |
| **Search by Attributes** | Select an attribute from the list to locate items with specific attribute values linked to a label. |
| **Search by Item Status** | Filter items based on their status (e.g., annotated, not annotated, described). |
| **Search by Team** | View items according to the users who worked on them. |
| **Search by Item Uploaded Date** | Retrieve items uploaded on a specific date or within a date range. |
| **Search by File Name** | Search items using their exact file name or partial matches. |
| **Search by File Extension** | Filter items by file type (e.g., `.jpg`, `.png`, `.json`). |
| **Search by Item Size** | Locate items by defining size conditions (e.g., minimum or maximum in KB, MB, or GB). |
| **Search by Item Metadata** | Search using custom metadata values associated with items, such as Meta Key Type - `System` or `Custom` , Data Type, etc. |
| **Search by Item Media Type** | Filter items based on their media type, such as `image` , `video`, `image/jpeg`, `video/webm`, etc.). |
| **Search by Annotation Type** | Retrieve items based on annotation types (box, point, polygon, etc.). |
| **Search by Annotation Metadata & QA** | Search using custom metadata values associated with items, such as Meta Key Type - `System` or `Custom` , Data Type, etc, or quality assurance results. |

You can clear a single filter by pressing **X** or the **Clear** button inside the filter config dialog, or all filters by pressing **Clear**.

---

## Advanced Search

Filters are integral components of the Dataset Browser, providing users with the capability to refine and narrow down the displayed items based on specific criteria. These filters offer a powerful tool for managing and exploring large datasets efficiently.

Advanced Search uses a **search schema** that allows users to query items and annotations data with higher granularity:

- Search Items using structured schema fields.
- Explore diverse use cases of search schemas within the Dataset Browser.
- View available schemas directly in the interface for guidance.

Search Items by Item's DataSearch Items by Annotation's DataSearch Items by Task's Data

### Search Items by Item Data

1. In the Data Browser, click on the **Items** field.
2. Select or enter the required search query.
3. Click **Search** to view the search result.

#### Search by Annotation Status

By Annotation Status -> Annotated or Not.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
annotated = true
```

or

```bash
annotated = false
```

1. Click **Search** to view the search result.

---

#### Search by Annotation's Count

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
annotationsCount = 5
```

1. Click **Search** to view the search result.

---

#### Search by Collection List

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
collection = 'Collection A'
```

1. Click **Search** to view the search result.

---

#### Search by Creation Date

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
createdAt = (03/12/2023)
```

1. Click **Search** to view the search result.

---

#### Search by Creator Email

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
creator = 'your@email-ID'
```

1. Click **Search** to view the search result.

---

#### Search by File Name

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
name = '63dbdd10be95cbe35df0a78b.jpg'
```

1. Click **Search** to view the search result.

---

#### Search by Dataset ID

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
datasetId = '65950d1d5c356a5e51f6727e'
```

1. Click **Search** to view the search result.

---

#### Search by Description Status

Description Status is Available or Not

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
described = true
```

or

```bash
described = false  
```

1. Click **Search** to view the search result.

---

#### Search by Description Text

1. In the Data Browser, click on the **Item** field.
2. Select or enter the query as follows:

```bash
description = 'description-text'
```

Whole description

Ensure to enter the full description to receive the result.

1. Click **Search** to view the search result.

---

#### Search by Folder Directory

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
dir = '/sub-folder name'
```

or

```bash
dir IN '/sub-folder name/sub-folder name'  
```

1. Click **Search** to view the search result.

---

#### Search by File Path

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
filePath = '/folder name/sub-folder name/fileName.jpg'
```

1. Click **Search** to view the search result.

---

#### Search by Height

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
itemHeight = 234
```

*Use the* ***height value*** *(for example, "height": 234) from the item metadata.*

1. Click **Search** to view the search result.

---

#### Search by Width

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
ItemWidth = 234
```

*Use the* ***width value*** *(for example, "width": 234) from the item metadata.*

1. Click **Search** to view the search result.

---

#### Search by Item ID

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
ItemID = '65798f8f81b02fbafe34fcad'
```

1. Click **Search** to view the search result.

---

#### Search by Discarded Items

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
ItemStatus = 'Discard'
```

1. Click **Search** to view the search result.

---

#### Search by Completed Items

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
ItemStatus = 'Complete'
```

1. Click **Search** to view the search result.

---

#### Search by Approved Items

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
ItemStatus = 'Approve'
```

1. Click **Search** to view the search result.

---

#### Search by JSON (Media Type)

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
MediaType = 'application/json'
```

1. Click **Search** to view the search result. It displays the all the JSON files.

---

#### Search by PCD (Media Type) Files

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
MediaType = 'application/pcd'
```

1. Click **Search** to view the search result. It displays the all the PCD files.

---

#### Search by Audio Files

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
MediaType = 'audio/*'
```

1. Click **Search** to view the search result. It displays the all the audio files.

---

#### Search by Image Files

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
MediaType = 'image/*'
```

1. Click **Search** to view the search result. It displays the all the image files.

---

#### Search by Text Files

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
MediaType = 'text/*'
```

1. Click **Search** to view the search result. It displays the all the text files.

---

#### Search by Video Files

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
MediaType = 'video/*'
```

1. Click **Search** to view the search result. It displays the all the video files.

---

#### Search by Frames Per Second

Search Video Files by Frames Per Second (Metadata - fps) in the Dataset.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.fps = 25
```

*Use the* ***fps value*** *(for example, "fps": 25) from the item metadata.*

1. Click **Search** to view the search result.

---

#### Search by System Metadata's Mimetype

Search Items by System Metadata's Mimetype in the Dataset.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.mimetype = 'image/jpeg'
```

*Use the* ***mimetype value*** *(for example,* `"mimetype": "image/jpeg"`*,* `"mimetype": "text/html"`*, or* `"mimetype": "audio/mp3"` *) from the item metadata.*

1. Click **Search** to view the search result.

---

#### Search by File Size Using Metadata

Search Items by File Size from the Item Metadata.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.size = 'value'
```

1. Click **Search** to view the search result.

---

#### Search by Frames Per Second Using Metadata

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.fps = 15
```

*Use the* ***fps value*** *(for example,* `"fps": 15`*) from the item metadata system.*

1. Click **Search** to view the search result.

---

#### Search by Duration Using Metadata

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.duration = 30.8
```

*Use the* ***duration value*** *(for example,* `"duration": 30.8`*) from the item metadata system.*

1. Click **Search** to view the search result.

---

#### Search by Width Using Metadata

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.width = 320
```

*Use the* ***Width value*** *(for example,* `"width": 320`*) from the item metadata system.*

1. Click **Search** to view the search result.

---

#### Search by Height Using Metadata

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.height = 240
```

*Use the* ***Height value*** *(for example,* `"height": 240`*) from the item metadata system.*

1. Click **Search** to view the search result.

---

#### Search by Dataset Tags Using Metadata

Search Items by the Dataset Tags (Train, Validation, or Test) from the Item Metadata.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.tags.train = true
```

*Use the* ***Tags value*** *from the item metadata system.* for example,

```bash
    "tags":
        "train": true
```

Or

```bash
   "tags":
       "validation": true
```

Or

```bash
    "tags":
        "test": true
```

*Use the* ***Tags value*** *from the item metadata system.*

1. Click **Search** to view the search result.

---

#### Search by Reference ID Using Metadata

Search Items by the Reference ID from the Item Metadata.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.refs.id = 649c421b9084a344b862289b
```

*Use the* ***refs ID value*** *(for example,* `"id": "649c421b9084a344b862289b"`*) from the item metadata system.*

1. Click **Search** to view the search result.

---

#### Search by Reference Type Using Metadata

Search Items by the Reference Type from the Item Metadata.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.refs.type = 'assignment'
```

*Use the* ***Type value*** *(for example,* `"type": "assignment"`*) from the item metadata system.*

1. Click **Search** to view the search result.

---

#### Search by Encoding Using Metadata

Search Items by the Encoding from the Item Metadata.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.encoding = 7bit
```

*Use the* ***Encoding value*** *(for example,* `"encoding": "7bit"`*) from the item metadata system.*

1. Click **Search** to view the search result.

---

#### Search by Original Name Using Metadata

Search Items by the Original Name from the Item Metadata.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
metadata.system.originalname = video-tutorial-v1.mp4
```

*Use the* ***originalname value*** *(for example, `"originalname": "video-tutorial-v1.mp4") from the item metadata system.*

1. Click **Search** to view the search result.

---

#### Search by Model Test Set Items

Search Items are Designated for a Model Test Set.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
ModelTestSet = true
```

or,

```bash
ModelTestSet = false
```

1. Click **Search** to view the search result.

---

#### Search by Model Train Set Items

Search Items are Designated for a Model Train Set.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
ModelTrainSet = true
```

or,

```bash
ModelTrainSet = false
```

1. Click **Search** to view the search result.

---

#### Search by Model Validation Set Items

Search Items are Designated for a Model Validation Set.

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
ModelValidationSet = true
```

or,

```bash
ModelValidationSet = true
```

1. Click **Search** to view the search result.

---

#### Search by Updated Date

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
updatedAt = (10/04/2024)
```

1. Click **Search** to view the search result.

---

#### Search by User Who Updated

1. In the Data Browser, click on the **Items** field.
2. Select or enter the query as follows:

```bash
updatedBy = 'name@dataloop.ai'
```

1. Click **Search** to view the search result.

### Search Items by Annotation Data

1. In the Data Browser, click on the **Annotation** field.
2. Select or enter the required search query.
3. Click **Search** to view the search result.

![](https://cdn.document360.io/53f32fe9-1937-4652-8526-90c1bc78d3f8/Images/Documentation/advanced_search_by_annotations.png)

#### Annotation ID

Search Annotations by Annotation ID.

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
annotationId = '6638e5f4fb9b79bc00d04288'
```

*Copy the* ***annotationId*** *value from opening a labeled item -> select an annotation from the right-side panel -> click on the 'i' (info) icon -> copy annotation ID.*

1. Click **Search** to view the search result.

---

#### Confidence Value

Search Annotations by Label's Confidence Value.

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
Confidence = '402.33'
```

1. Click **Search** to view the search result.

---

#### Creation Date

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
createdAt = (03/12/2023)
```

1. Click **Search** to view the search result.

---

#### Annotation Creator

Search Annotations by Annotation Creator.

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
creator = 'creator's email ID'
```

1. Click **Search** to view the search result.

---

#### Dataset ID

Search Annotations by Dataset ID.

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
datasetId = '65950d1d5c356a5e51f6727e'
```

1. Click **Search** to view the search result.

---

#### Attribute’s Name

Search Annotations by Attribute’s Name.

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
attributeName.<name of the attribute> = '<attribute value>'
```

For example,

- Attribute Name = **How is it**. By default, it displays all available attributes.
- Attribute Value = **Good** or **Bad**. By default, it displays all available attribute values.

then, the query will be `attributeName.How_is_it = 'Good'`

1. Click **Search** to view the search result.

---

#### Attribute ID

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
attributeName.<ID of the attribute> = '<attribute value>'
```

For example,

- Attribute ID = **1**. By default, it displays all available attribute ID.
- Attribute Value = **Good** or **Bad**. By default, it displays all available attribute values.

then, the query will be `attributeId.1 = 'Good'`

*You can copy the* ***attributeId*** *value from the Recipe -> Labels & Attributes -> Right-side section (Create Section)*

1. Click **Search** to view the search result.

---

#### Item ID

Search Annotations by the Item ID.

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
itemId = '65798f8f81b02fbafe34fcad'
```

1. Click **Search** to view the search result.

---

#### Label Name

Search Annotations by the Label Name. Displays all available labels.

> [!NOTE]
> Displays all available labels
> 
> When a dataset is linked to one recipe, and a task is created using items from that dataset with a different recipe, the label filters in the Dataset Browser will display labels from both the dataset’s recipe and the task’s recipe.

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query example as follows:

```bash
label = 'Cat'
```

1. Click **Search** to view the search result.

---

#### Model Name

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
modelName = 'yolov3'
```

*You can copy the* ***model name*** *value from the JSON file of the item.*

1. Click **Search** to view the search result.

---

#### Parent Annotation (Parent ID)

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
parentId = '1234'
```

1. Click **Search** to view the search result.

---

#### Source of the Annotation

Search Annotations by the Source of the Annotation.

1. In the Data Browser, click on the **Annotations** field to find where the annotation is created.
2. Select or enter the query as follows:

```bash
type = 'ui'
```

or

```bash
type = 'sdk'
```

1. Click **Search** to view the search result.

---

#### Label's Attribute

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
metadata.system.attributes.1 = 'Yes'
```

Attributes

The attributes are defined according to the customizations made in the recipe.

1. Click **Search** to view the search result.

---

#### Annotation Type

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
type = 'cube'
```

1. Click **Search** to view the search result.

---

#### Update Date

1. In the Data Browser, click on the **Annotations** field.
2. Select or enter the query as follows:

```bash
updatedAt = (03/12/2023)
```

1. Click **Search** to view the search result.

### Search Items by Task Data

1. In the Data Browser, add the **Tasks** filter.
2. In the Tasks' field, select task's `ID` or `Name` criteria from the list.
3. Enter the value and click **Search** to view the search result.

Auto-complete for task name search

Receive real-time auto-complete suggestions as you type a task name. Suggestions are dynamically refreshed and sourced from the first 100 matching tasks. To improve system performance, the number of tasks displayed in the dataset browser is limited:

- Lazy loading: Tasks are loaded in batches of 100 as you scroll through the task filter component.
- Maximum limit: Up to 1,000 tasks are loaded, prioritized by last updated time.

#### Task's ID

1. In the Data Browser, add the **Tasks** filter.
2. In the Tasks' field, select the **TaskID** from the list.
3. Enter the value as follows.

```bash
TaskID= 'task's ID'
```

1. Click **Search** to view the search result.

---

#### Task's Name

1. In the Data Browser, add the **Tasks** filter.
2. In the Tasks' field, select the **TaskName** from the list.
3. Select or enter query as follows:

```bash
TaskName = 'task's Name'
```

1. Click **Search** to view the search result.

---

### Search Query Variables

Search Items

To learn various search options using the schema search, see the [Search Items](https://docs.dataloop.ai/docs/search-items#overview) article.

| Filter Data Type | Filter Variable | Description | Conditions | Data Types |
| --- | --- | --- | --- | --- |
| Items | `annotated` | Filter items based on whether they are annotated or not. | `=`, `!=` | Boolean values (`true` or `false`) |
| Items | `annotationsCount` | Filter items based on the number of annotations. | `=`, `!=`, `&gt;`, `&gt;=`, `&lt;`, `&lt;=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Items | `collection` | Filter items based on the collection folder name | `=`, `!=` | String |
| Items | `createdAt` | Filter items based on the date and time of their creation. | `=`, `!=`, `&gt;=`, `&lt;=`, `&lt;`, `&gt;` | dd/mm/yyyy |
| Items | `creator` | Filter items based on the creator of the item. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Items | `datasetid` | Filter items based on the dataset ID. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Items | `described` | Filter items based on the presence or absence of a description. | `=`, `!=` | Boolean values (`true` or `false`) |
| Items | `description` | Filter items by searching for those that contain a specific part of the description text. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Items | `dir` | Filter items based on their folder location within the dataset. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Items | `filePath` | Filter items by the file location. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Items | `ItemHeight` | Filter items based on the height value of each item. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Items | `ItemId` | The unique ID of the item. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Items | `ItemStatus` | Filter items based on the item's annotation status | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String (Discard, Complete, and Approve) |
| Items | `ItemWidth` | Filter items according to the width value of each item. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Items | `MediaType` | The filter allows searching based on their media types, such as video or image. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Items | `metadata` | Filter items based on metadata information (for example, `metadata.system` and `metadata.description`) contained in the [items' JSON](https://docs.dataloop.ai/docs/item-json-format) file. | `=`, `!=`, `&gt;=`, `&lt;=`, `&lt;`, `&gt;`, `IN`, `NOT-IN` | String |
| Items | `ModelTestSet` | Filter items that are designated for testing the model. | `=`, `!=` | Boolean values (`true` or `false`) |
| Items | `ModelTrainSet` | Filter items that are designated for training the model. | `=`, `!=` | Boolean values (`true` or `false`) |
| Items | `ModelValidationSet` | Filter items that are designated for validating the model. | `=`, `!=` | Boolean values (`true` or `false`) |
| Items | `name` | Filter items based on their name. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Items | `updatedAt` | Filter items based on the item's last updated date. | `=`, `!=`, `&gt;`, `&gt;=`, `&lt;`, `&lt;=`, `EXIST`, `DOESNT-EXIST` | String |
| Items | `updatedBy` | Filter items based on the email ID of the user who last updated the item. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Annotations | `annotationId` | Filter annotation based on the annotation ID. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Annotations | `attributeId` | Filter annotation based on the attribute ID. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Annotations | `attributeName` | Filter annotation based on the attribute name. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Annotations | `confidence` | Filter annotations based on its confidence level. The Confidence is the measure of certainty or accuracy in the labels assigned to data, typically expressed as a percentage. Higher confidence scores indicate greater reliability of the annotations. | `=`, `!=`, `&gt;`, `&gt;=`, `&lt;`, `&lt;=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Annotations | `createdAt` | Filter annotations based on the date and time of their creation. | `=`, `!=`, `&gt;=`, `&lt;=`, `&lt;`, `&gt;` | dd/mm/yyyy |
| Annotations | `creator` | Filter annotations by the user's email ID who created the annotation. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Annotations | `datasetId` | Filter annotations based on the dataset ID. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Annotations | `id` | Filter annotations based on the annotation ID. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Annotations | `itemId` | Filter annotations based on the item ID. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Annotations | `label` | Filter annotations based on the labels. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Annotations | `metadata` | Filter items based on annotation metadata information, such as `metadata.system.taskId` (annotation's task ID data) and `metadata.system.status` (annotation's like, approved, completed, etc.s). For more information, see the [annotation metadata](https://docs.dataloop.ai/docs/annotation-json-format). | `=`, `!=`, `IN`, `NOT-IN` | String |
| Annotations | `modelName` | Filter annotations based on the model names. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Annotations | `parentId` | Filter the data using the ID of the parent annotation. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Annotations | `source` | Filter the data using the by where the annotation was created: UI/SDK. | `=`, `!=`, `IN`, `NOT-IN` | String |
| Annotations | `type` | Filter the data using the [types of annotations](https://docs.dataloop.ai/docs/tools-overview). | `=`, `!=`, `IN`, `NOT-IN` | String |
| Annotations | `updatedAt` | Filter annotations based on the last updated date. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Annotations | `updatedBy` | Filter annotations based on the email ID of the user who last updated the item. | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Tasks | `TaskID` | Filter the data using the Tasks' ID | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |
| Tasks | `TaskName` | Filter the data using the Tasks' Name | `=`, `!=`, `IN`, `NOT-IN`, `EXIST`, `DOESNT-EXIST` | String |

---

## DQL Search

The **DDOE Query Language (DQL)** provides a powerful and flexible way to search, filter, and retrieve items within a dataset. Unlike **Basic Search**, which uses predefined filters, DQL enables users to build **custom, fine-grained queries** that can combine multiple conditions and operators.

### **DQL Syntax Highlights**

DQL queries are written in a structured JSON-like format. Some of the common elements include:

- **Field Operators:**
  - `=`, `!=` (equals / not equals)
  - `&gt;`, `&lt;`, `&gt;=`, `&lt;=` (range comparisons)
  - `in`, `not in` (match against lists)
- **Logical Operators:**
  - `$and`, `$or`, `$not` (combine multiple conditions)
- **Wildcard & Regex Support:**
  - Search partial text patterns or match flexible strings.

[Learn more](https://docs.dataloop.ai/docs/dql-getting-started)

### Use the DQL Query Editor to Search

In addition to data search using the basic UI, it is possible to filter data using the [Dataloop Query Language](https://docs.dataloop.ai/docs/api-dql).

1. In the Dataset Browser, click on the **DQL** tab.
2. Click on the **DQL Editor** icon. The DQL Search window is displayed.
3. Edit the query as required, or select a saved query from the list.
4. Once edited, click **Search** to run the search query, or click **Save As** to save it.

Delete DQL Search Query

Click on the **Delete Query** to delete the query.

---

### Copy the DQL Filter Query

1. In the Dataset Browser, click on the **DQL** tab.
2. Click on the **Copy Filter** icon. A confirmation message is displayed, and the query will be copied in DQL format.

### Expand the DQL Filter Query

1. In the Dataset Browser, click on the **DQL** tab.
2. Click on the **Expand** icon. The query field will be expanded.

---

### Filters Operands

The following operators are applied within and between filters, unless otherwise specified when manually modifying a DQL query.

#### Cross Filter Operand

A relationship between multiple filters in a single query is based on the **AND** operand. For example, filtering by status `Annotated` `AND` the user `john@doe.ai` `AND` the annotation type: `Box`, will return items that are annotated, have `Box` annotation, and `have john@doe.ai` as an annotator in one or more of the annotations.

#### Inter-Filter Operand

The operand relationship between multiple values in a specific filter is based on the **OR** operator. For example, filtering by labels with the values **Person** and **Dog**, the filter will return all items with annotations of either of these labels, not necessarily both at the same time.

---

## Move Between Search Filter Modes

DDOE provides three filter modes for searching data:

- **Basic**: Simple filter-based searches
- **Advanced**: More detailed filtering options
- **DQL**: Query-based filtering using DQL syntax

You can switch between these modes using the filter mode toggle.

**Important Notes**

- Switching filter modes does **not** run a search automatically.
- Any changes that have not been applied are discarded when switching modes.
- If a query cannot be converted to another mode, that mode is disabled.

### Supported Mode Transitions

| **Always Allowed** | **Conditional Transitions** **(**The following transitions are only available if the current query can be represented in the target mode) |
| --- | --- |
| **Basic → Advanced** | **DQL → Advanced** |
| **Basic → DQL** | **DQL → Basic** |
| **Advanced → DQL** | **Advanced → Basic** |

### When Switching to Basic Mode Is Not Allowed

You cannot switch to Basic mode if the query contains:

- Wildcards (for example, `Dog*`)
- Complex logic or nested conditions
- Unsupported operators such as:
  - `!=`
  - `EXCEPT`
  - `INTERSECT`
- Invalid queries

**Supported**, example:

```json
Label = 'Dog' AND Annotated = true

Label IN ['Dog', 'Cat']
```

**Not supported**, example:

```json
Label = 'Dog' OR Annotated = true
Label != 'Cat'
```

### When Switching to Advanced Mode Is Not Allowed

You cannot switch from DQL to Advanced mode if the query contains:

- `EXCEPT` or `INTERSECT` operators
- Complex nested logic
- Invalid DQL syntax
- Queries that cannot be represented using Advanced filters

### Loading Saved or URL Filters

When DDOE loads filters from Static filters, URLs, Saved task filters; it automatically selects the most suitable mode:

1. **Basic Mode**
2. **Advanced Mode** (if Basic is not supported)
3. **DQL Mode** (if Advanced is not supported)

### DQL Queries in Advanced Mode

If an Advanced task filter uses a **Match** operator, DDOE keeps you in the current mode.

When a DQL query is active in Advanced mode, the Items filter section is locked and displays the following message: `DQL Query is active, edit the query using the DQL editor.`

---

## Semantic Search - CLIP Based

NLP (Natural Language Processing) with CLIP (Contrastive Language-Image Pre-Training) refers to the integration of language understanding capabilities with visual recognition. CLIP is a neural network model that leverages NLP techniques to process and understand text while simultaneously analyzing and comprehending images. This enables the model to interpret and align textual descriptions with corresponding visual content effectively.

You can input any descriptive text, and the model will retrieve images or data entries that best match the query, significantly enhancing the user experience by making the search process more intuitive and flexible. Additionally, you can use it alongside other search fields such as Annotations and Items to further refine and improve your search results.

***Prerequisites****: Install a CLIP Model.*

1. In the Data Browser, click on the **Semantic Search**.
2. Select the **NLP (CLIP)** from the list. A new field NLP (CLIP) is added.
3. Enter the required text in the **NLP (CLIP)** field. For example, "Image with red cars".
4. Click **Search** to view the search result.

---

## Searchable and Unsearchable Metadata

- **Searchable metadata** refers to key-value pairs stored under `metadata.user` that are **indexed by DDOE**. [Learn more](https://docs.dataloop.ai/docs/organize-your-data#searchable-metadata).
- **Unsearchable metadat**a in DDOE refers to custom key-value pairs stored under alternative subpaths like `metadata.user.unsearchable`, which are not indexed by the platform. [Learn more](https://docs.dataloop.ai/docs/organize-your-data#unsearchable-metadata).

---

## Filter by Collections

The Collections feature in DDOE's Data Browser helps organize data by allowing you to group specific sets of items based on task needs (e.g., annotation, review, training) into a collection folder. You can create up to **10** collection folders.

![](https://cdn.document360.io/53f32fe9-1937-4652-8526-90c1bc78d3f8/Images/Documentation/db_filter_collections.png)

1. Open the **Dataset Browser**: Go to the Data → Datasets → Your Dataset → **Data Browser**.
2. Select the **Collections** from the top-bar. The available items are displayed in folder wise.
3. Select a collection from the list. Once selected, only items included in that collection will be displayed.

#### **Filter Items without Collections**

Click on the **Items without collections**

[Learn more](https://docs.dataloop.ai/docs/organize-your-data#collections) about Collections.

---

## Filter by ML Subsets

The **ML Subsets** view in DDOE’s Data Browser is a dedicated feature that streamlines machine learning workflows by helping you organize and manage datasets more efficiently. It enables you to classify and filter items according to their ML subset assignments—such as **train**, **validation**, and **test**—which are essential stages in the ML lifecycle for model development and evaluation.

![](https://cdn.document360.io/53f32fe9-1937-4652-8526-90c1bc78d3f8/Images/Documentation/db_filter_ml-subsets.png)

1. Open the **Dataset Browser**: Go to the Data → Datasets → Your Dataset → **Data Browser**.
2. Select the **ML Subsets** from the top-bar. The available items are displayed in folder wise.
3. Select a subset. For example, Train, etc. and click outside of the ML Subsets pop-up. The items are added to the train subset will be filtered and displayed.

![](https://cdn.document360.io/53f32fe9-1937-4652-8526-90c1bc78d3f8/Images/Documentation/db_ml_subsets_open.png)

A search query for the train subsets will be also added and visible on the Items search field.

![](https://cdn.document360.io/53f32fe9-1937-4652-8526-90c1bc78d3f8/Images/Documentation/db_ml_subsets_search_query.png)

**If there are no items added to ML Subsets**, click [Split Into Subsets](/docs/filter-items#split-items-into-subsets).

[Learn more](https://docs.dataloop.ai/docs/organize-your-data#ml-subsets) about ML Subsets.

---

## Filter by Tasks & Statuses

The Tasks & Statuses filter in DDOE's Data Browser allows you to filter and search for items based on task-related attributes, such as task status or lack of assignments. This feature offers advanced filtering options, enabling better data management.

![](https://cdn.document360.io/53f32fe9-1937-4652-8526-90c1bc78d3f8/Images/Documentation/db_filter_tasks.png)

**Prerequisites**: [Create a Task](https://docs.dataloop.ai/docs/task-types#create-a-labeling-task).

**Filters Items by Tasks & Statuses**

1. Open the **Dataset Browser**: Go to the Data → Datasets → Your Dataset → **Data Browser**.
2. Select the **Tasks & Statuses** from the top.
3. Select the following options to filter items:
  1. **Items in task**:
    1. **Search tasks**: Select a task to filter items included as part of this task.
    2. **Filtering by Status**:
      1. Use the **Timestamp** to select a time period to view the items. Use the **filter** to view items based on the following task status options.
      2. Items with Status **[= (equals)]**: Filter items that have one of the following assigned task status: **Complete** or **Discard**
      3. Items with Status [**!= ( not equals)**]: Filter items that do not have one of the following assigned task status: **Complete** or **Discard**.
      4. Items without Status: Filter items that do not have a status. The DQL (Data Query Language) query will update accordingly.
  2. **Items Not in task**: Filter items that are not part of any tasks.

### Item Status

An item earns the status **annotated** if it receives any form of annotation, such as a classification, a note, or any other tool-generated annotation, regardless of whether this occurs in the dataset browser or during a task. However, being **annotated** doesn't necessarily mean an item is **completed**.

- This situation may arise if the item is annotated via the dataset browser, where annotations can be saved without assigning a status, or if it's annotated during a task without the complete button being engaged. Perhaps because the annotator plans to return to it later.
- **Completed** status is assigned to an item when an annotator finalizes their work on it by clicking the **complete** button during a task.
- An **approved** status is granted after an item undergoes a QA task and the QA tester decides to approve it by clicking the respective button.
- An item is deemed **not annotated** if it lacks any annotations. Interestingly, an item can be marked as **completed** and yet be considered **not annotated** if the **complete** button was clicked without any actual annotation work being done on it.

---

## Saved Filters

The DDOE platform allows you to customize and save search queries within data querying or search systems, designed to streamline and optimize user interactions with large datasets.

![](https://cdn.document360.io/53f32fe9-1937-4652-8526-90c1bc78d3f8/Images/Documentation/db_filter_saved_filters.png)

### Save Search Queries

DDOE platform offers the ability to save specific search filter criteria, allowing for efficient and consistent future searches.

1. Open the **Dataset Browser**: Go to the Data → Datasets → Your Dataset → **Data Browser**.,
2. Create a search query.
3. Click on **Saved Filters.**
4. Select **Save Filter**. A dialogue window is displayed.
5. Enter a name for the new filter query.
6. Click **Save**. A confirmation message is displayed.

### Filter Items Using Saved Queries

DDOE platform offers the ability to reuse specific search filter criteria.

1. In the Dataset Browser, click on the **Saved Filters.**
2. Select **Saved Filters** and choose the saved filter from the list. Clicking on the saved filter allows the search query to run and displays the result.

> [!NOTE]
> View Saved Filters
> 
> Up to **three saved filters** are displayed in the top menu, above of the search bar. Clicking on any of these filters will automatically run the corresponding query in the **Smart Search** field, instantly applying the saved conditions to your dataset.

### Delete Saved Search Queries

DDOE platform offers the ability to reuse specific search filter criteria.

1. In the Dataset Browser, click on the **⋮ Three Dots**.
2. Select the **Saved Filters**.
3. Find the query to be deleted and click on the **Delete** icon when you hover over.
4. Click **Delete Query**. A confirmation message is displayed.