Metaforecast late 2022 update: GraphQL API, Charts, better infrastructure behind the scenes.
==============
**tl;dr**:[Metaforecast](https://metaforecast.org/) is a search engine and an associated repository for forecasting questions. Since our[last update](https://metaforecast.substack.com/p/metaforecast-update-better-search), we have added a GraphQL API, charts, and dashboards. We have also reworked our infrastructure to make it more stable.
Our most significant new addition is our GraphQL API. It allows other people to build on top of our efforts. It can be accessed on[metaforecast.org/api/graphql](https://metaforecast.org/api/graphql), and looks similar to the EA Forum's[own graphql api](https://forum.effectivealtruism.org/graphiql).<p><imgsrc="https://i.imgur.com/xHRBMNb.png"class='.img-medium-center'></p>
To get the first 1000 questions, you could use a query like:
```
{
questions(first: 1000) {
edges {
node {
id
title
url
description
options {
name
probability
}
qualityIndicators {
numForecasts
stars
}
timestamp
}
}
pageInfo {
endCursor
startCursor
}
}
}
```
You can find more examples, like code to download all questions, in our[/scripts](https://github.com/quantified-uncertainty/metaforecast/tree/master/scripts) folder, to which we welcome contributions.
## Charts and question pages.
Charts display a question's history. They look as follows:
Clicking on the expand button brings the user to a question page, which contains a chart, the full question description, and a range of quality indicators:
We are also providing an endpoint at_metaforecast.org/questions/embed/\[id\]_ to allow other pages to embed our charts. For instance, to embed a question whose id is_betfair-1.178163916_, the endpoint would be[here](https://metaforecast.org/questions/embed/betfair-1.178163916). One would use it in the following code:
You can find the necessary question id by clicking a toggle under "advanced options" on the frontpage, or simply by noticing the id in our URL when expanding the question.
With time, we aim to improve these pages, make them more interactive, etc. We also think it would be a good idea to embed Metaforecast questions and dashboards into the EA Forum, and we are trying to collaborate with the [Manifold team](https://github.com/ForumMagnum/ForumMagnum/pull/6015), who have[done this before](https://github.com/ForumMagnum/ForumMagnum/pull/4907), to make that happen.
## Dashboards
Dashboards are collections of questions. For instance,[here](https://metaforecast.org/dashboards/view/561472e0d2?numCols=2) is a dashboard on global markets and inflation, as embedded in[Global Guessing](https://globalguessing.com/russia-ukraine-forecasts/).
Like questions, you can either[view dashboards directly](http://metaforecast.org/dashboards/view/561472e0d2?numCols=2), or[embed](http://metaforecast.org/dashboards/embed/561472e0d2?numCols=2) them. You can also create them, at[https://metaforecast.org/dashboards](https://metaforecast.org/dashboards).
## Better infrastructure
We have also revamped our infrastructure. We moved to from JavaScript to Typescript, from MongoDB to Postgres, and simplified our backend.
## We are open to collaborations
We are very much open to collaborations. If you want to integrate Metaforecast into your project and need help do not hesitate to reach out, e.g., on our[Github](https://github.com/quantified-uncertainty/metaforecast/issues).
Metaforecast is also open source, and we welcome contributions. You can see some to-dos[here](https://github.com/quantified-uncertainty/metaforecast#to-do). Developing is going more slowly now because it's mostly driven by Nuño working in his spare time, so contributions would be counterfactual.
Metaforecast is hosted by the [Quantified Uncertainty Research Institute](https://quantifieduncertainty.org/), and has received funding from[Astral Codex Ten](https://astralcodexten.substack.com/p/acx-grants-results). It has received significant contributions from[Vyacheslav Matyuhin](https://berekuk.ru/), who was responsible for the upgrade to Typescript and GraphQL. Thanks to Clay Graubard of[Global Guessing](https://globalguessing.com/) for their comments and dashboards, to Insight Prediction for help smoothing out their API, to Nathan Young for general comments, to others for their comments and suggestions.
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