> For the complete documentation index, see [llms.txt](https://hurwitzlab.gitbook.io/imicrobe/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://hurwitzlab.gitbook.io/imicrobe/community/camera-datasets.md).

# CAMERA

**Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis (CAMERA)**. One of the first efforts to make environmental ‘omics datasets available in a common cyberinfrastructure was through the Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis (CAMERA). This project integrated ‘omics data and rich environmental metadata in a common framework to query data and run analyses. In Fall 2014, the CAMERA project ended making these important data sets and analysis pipelines inaccessible, some of which did not exist elsewhere. To continue the broad use of these data sets, the data from the CAMERA data distribution center (DDC) and website were mirrored in iMicrobe including: reads, peptides, CDS, contigs, assemblies, annotations, and related project, sample and environmental data. These data were then harmonized across projects using standardized terminology and ontology across projects (github), to enable a rapid search interface for data sets in the CyVerse Data Store. The CAMERA dataset consists of \~120 projects with \~1TB of data. <br>


---

# 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://hurwitzlab.gitbook.io/imicrobe/community/camera-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.