> For the complete documentation index, see [llms.txt](https://whitepaper.openvision.network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.openvision.network/openvision-declaration/overview.md).

# Overview

OpenVision connects Data Providers with AI researchers and through a collective egocentric data ownership governed by $VISION tokens.

* By hosting a decentralized data availability layer, **AI researchers** can tap into the repository of existing high-quality data collected by OpenVision’s dedicated hardware and access a community of enthusiastic Data Providers. $VISION token is both used to secure decentralized data storage and to reward timely data availability.
* **Data Providers**, either with our crafted mobile apps or OpenVision’ dedicated hardware, can respond to data requests posted by AI researchers by capturing high-quality visual data apposite to such requests.
* **Data Validators**, who are required to pledge a bond in $VISION to perform their duty, will vet uploads before clearing them to enter our canonical repository built upon our decentralized data availability solution.

<figure><img src="/files/FccJCr07AlsjMg2sifF5" alt=""><figcaption><p>OpenVision Governance DAO is owned by all $VISION token holders</p></figcaption></figure>

While AI researchers who post the request will have early and a time-limited exclusive access to the data harvested, the ownership of OpenVision’s decentralized data repository belongs to all $VISION token holders.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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://whitepaper.openvision.network/openvision-declaration/overview.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.