> For the complete documentation index, see [llms.txt](https://docs.pdap.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.pdap.io/meta/community-calls/february-1-2023.md).

# February 1, 2023

## Updates from PDAP

Josh is still primarily working on grant application and collaboration with groups local to Pittsburgh using or generating data.

Jacob is working on long-term software projects related to more permanent Data Sources.

### Known projects in need of help

* Research on Southeast Arkansas ([thread in #data-exchange](https://discord.com/channels/828274060034965575/1063264064719044688))
  * scheduling a working session when we know more
  * we may have a connection in AK
* San Francisco court scraper [issue here](https://github.com/biglocalnews/court-scraper/issues/179) (Jacob's been doing research and groundwork; ready to hand off or finish)
* Research on Detroit Police Department (discussing new information today)
  * OPD would give the requestor the ability to request complaint and calls for service data, providing it as a Pandas dataframe
* Machine learning identification of URLs
  * More notes about this project in recent community call notes
  * Scheduling a working session next week
  * Stocking wrote a crawler which PDAP can fork + keep in our repo to regex ID URLs → JSON labels; craeft offered to host stuff on a personal box for us to access/use


---

# 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://docs.pdap.io/meta/community-calls/february-1-2023.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.