# Datasets

All your raw data - including images, point clouds and videos are managed through datasets. You can add tags to each file in your dataset to organize it into different subsets.

To create a dataset, select what type of data you would like to upload, and where you would like to upload it.&#x20;

<figure><img src="/files/Gh7m5gmVrAOMWV4fRjxd" alt=""><figcaption></figcaption></figure>

You can upload data to your datasets multiple times. [**Check out this guide**](/management/datasets/uploading-data.md) **to see the different ways in which you can add your data to Mindkosh.**

Once uploaded, you can see it in a list and filter by tags.

<figure><img src="/files/5AMAoyA1HIsq9Sh2y11s" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
To start labeling this uploaded data, you need to create a task and attach a dataset to it. [Check out this guide](/management/tasks.md#creating-a-new-task) to see how you can create a task.
{% endhint %}

&#x20;

### Using tags

Tags are a great way to organize your data on Mindkosh. For e.g. if you have multi-modal data, you can tag the data from each sensor with a specific tag to easily identify it.

{% hint style="success" %}
You can add multiple tags to each file
{% endhint %}

Another way to tags is to segment your data in meaningful ways. For e.g. imagine that you are uploading data captured on specific days. You could tag the data from each day with a specific tag, to easily identify the files captured on a particular day. These tags can then be used to label data from specific days in separate tasks.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.mindkosh.com/management/datasets.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
