> For the complete documentation index, see [llms.txt](https://docs.lagrangedao.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lagrangedao.org/datasets/data-card.md).

# Data Card

A datacard serves as a detailed overview and documentation for a dataset. Creating a `readme.md` file in the dataset's root directory is a good practice to provide necessary information about the dataset to users. You can use the sample datacard as a template and customize it based on your dataset's specific details.

Here's a sample [datacard](https://github.com/lagrangedao/datasets) structure for a `readme.md` file:

## Dataset Title

### Table of Contents

* Description
* Content
* Usage
* Licenses and Attribution
* Citation
* Contact

### Description

A brief description of the dataset, its purpose, and the problem it aims to address.

### Content

* A detailed explanation of the dataset's content, including:
  * Data sources
  * Features/variables/columns and their descriptions
  * Data format (CSV, JSON, etc.)
  * Size of the dataset
  * Temporal and spatial coverage (if applicable)

### Usage

* Potential use cases of the dataset
* Any preprocessing steps or data cleaning performed
* Any known limitations or biases in the dataset
* Guidelines for using the dataset responsibly and ethically

### Licenses and Attribution

* Information about the dataset's license
* Required attributions or acknowledgments
* Any third-party content, data, or code used in the dataset

### Citation

Provide a suggested citation format for users who reference the dataset in their research or work.

### Contact

* Contact information for the dataset's creators or maintainers
* Any relevant links, such as the project website, related publications, or social media profiles

When you create the `readme.md` file with this structure, it will serve as the datacard for your dataset, providing users with all the necessary information they need to understand and utilize the dataset effectively.