# Introduction

PetaBencana.id is a free and transparent platform for emergency response and disaster management in megacities in South and Southeast Asia. The platform harnesses the heightened use of social media during emergency events to gather, sort, and display confirmed hazard information in real-time.

The platform adopts a “people are the best sensors” paradigm, where confirmed reports are collected directly from the users at street level in a manner that removes expensive and time-consuming data processing. This framework creates accurate, real-time data which is immediately made available for users and first responders.

PetaBencana.id gathers, sorts, and visualizes data using specially developed Situational Intelligence Open Source Software (Siti OSS), to transform the noise of social and digital media into critical information for residents, communities, and government agencies.

## Petabencana Data API

Petabencana is backed by a data [API](https://en.wikipedia.org/wiki/Application_programming_interface) exposing a number of public and private endpoints. The documentation that follows allows developers to get up and running. The project is fully open source and the code is available in the [PetaBencana GitHub](https://github.com/petabencana/). The architectural diagram is available in different formats:

* [PDF](https://github.com/petabencana/petabencana-docs/tree/d8b3cac5b3bc2a65abd49d874bf9c5798e93eb97/petabencana.pdf)
* [Visio XML](https://github.com/petabencana/petabencana-docs/tree/d8b3cac5b3bc2a65abd49d874bf9c5798e93eb97/petabencana.vdx)
* [OmniGraffle](https://github.com/petabencana/petabencana-docs/tree/d8b3cac5b3bc2a65abd49d874bf9c5798e93eb97/petabencana.graffle.zip)


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# Agent Instructions: 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.petabencana.id/master-1/readme.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.