> For the complete documentation index, see [llms.txt](https://docs.redivis.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.redivis.com/guides/discover-and-access-data/discover-datasets.md).
# Discover datasets
Datasets are the core entity on Redivis, and finding the dataset(s) you want to work with is generally one of your first steps.
## 1. Find a dataset
You can discover datasets in many contexts.
If you are part of an institution or an organization you can browse for datasets they've uploaded on the **Datasets** tab of their home pages.
You can also look for datasets directly on the Redivis [Explore](https://redivis.com/explore) page. This will show all datasets on Redivis that you have overview access to. If you expect to see a dataset here that isn't appearing you might need to log into your account, or ask the dataset owner to share the dataset with you.
## 2. Search for data
When searching for data on an organization page, institution page, or the Redivis explore page you can use multiple filters along with search terms to find what you'd like. All searches take a comprehensive look at information from the dataset documentation as well as variable metadata, including value labels.
You can also use the filters to find specific information you're looking for. If you know the name of the variable or year of the data you're interested in, narrow your search here.
## 3. Preview tables
Each dataset that appears here matches all search and filter configurations. You can click on the dataset tile to see more information, including a preview of all of the tables this dataset contains.
Click on any of these tables to dig into it further. As long as you have metadata access you can see the variable information and summary statistics.
Once you find a dataset you want to explore further, click on the title to go to the dataset page.
## 4. Explore the dataset page
This dataset page has all of the information you'll need to familiarize yourself with the data and get started working with it further. Add this dataset to your dataset library to easily find it later on by clicking the button alongside the dataset title.
**Overview**
This tab has a short summary of the dataset along with different sections filled out by the administrators such as the Methodology, Documentation, and Provenance information. This Provenance section will also have citation information and a DOI if one has been created. You can also see your current access level on the right side of the page.
**Tables**
This tab contains all of the dataset's tabular data. You can see each table alongside information about its contents. Click on each one to dig deeper into the data.
**Files**
This tab contains all of the dataset's unstructured data. You can preview each file by clicking on it.
**Usage**
This tab has information about how other people have used this dataset on Redivis. You can see the most popular variables across all tables to get a sense for which ones might be a good starting place to understanding the structure of the data.
## Next steps
#### Apply for access to restricted data
If you don't have data access to this dataset you'll need to apply for access before you can work with it further
*Learn more in the* [*Apply to access restricted data*](/guides/discover-and-access-data/apply-to-access-restricted-data.md) *guide.*
#### Start working with your data
Add this dataset to a workflow to transform and analyze it leveraging lightning fast tools from your browser.
*Learn more in the* [*Work with data in a workflow*](/guides/analyze-data-in-a-workflow.md) *guide.*
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# Agent Instructions
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## 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, and the optional `goal` query parameter:
```
GET https://docs.redivis.com/guides/discover-and-access-data/discover-datasets.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.
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.