feat: public open collective dataset (#2319)

* add: `open-collective` dataset overview

* add: `javi` as an author

* add: open collective transactions dataset `blog`

* add: analytics hub link

apps/docs/blog/2024-10-08-open-collective-transactions-datasets/index.md

@@ -0,0 +1,106 @@
+---
+slug: open-collective-transactions-datasets
+title: "Introducing new Open Collective transactions datasets"
+authors: [jabolol]
+tags: [data-science, open-collective]
+image: ./total_amount_donated_oc.png
+---
+
+[Open Collective](https://opencollective.com) is a platform that enables groups
+to collect and disburse funds transparently. It is used by many open-source
+projects, communities, and other groups to fund their activities. Notable
+projects include [`Open Web Docs`](https://openwebdocs.org) (maintainers of
+[MDN Web Docs](https://developer.mozilla.org/en-US/)),
+[`Babel`](https://babel.dev), and [`Webpack`](https://webpack.js.org).
+
+At Open Source Observer, we have been working on collecting and processing Open
+Collective data to make it available for analysis. This includes **all
+transactions** made on the platform, such as donations, expenses, and transfers.
+Datasets are updated weekly.
+
+<!-- truncate -->
+
+## Datasets
+
+Transactions are the core of Open Collective data. They represent the flow of
+funds between entities on the platform. We currently provide two datasets for
+Open Collective transactions: `expenses` and `deposits`. These datasets contain
+all transactions of the respective type.
+
+Both datasets follow the same schema. This schema contains important fields such
+the transaction's id, group, type and amount. For the full reference, see the
+BigQuery schema.
+
+## Use cases
+
+The Open Collective transactions datasets can be used for a variety of
+applications. Here are some examples:
+
+### Donor contribution patterns
+
+One use case is to analyze overall donor contribution patterns. This involves
+examining the frequency of donations, the amounts donated, and the growth of
+donations over time.
+
+For example, the plot below illustrates the frequency of different donation
+amounts. We can see that the most common donation is around **$1,500**, with
+approximately **600,000** donations at this level. This indicates that people
+tend to donate around $1,500 more frequently than other amounts, suggesting that
+establishing a donation tier at this level would be a good idea.
+
+![Frequency of donation quantities](./donation_amount_vs_contribution_frequency.png)
+
+### Analyzing Donation Trends and Retention
+
+Another use case is to analyze donation trends and retention. This involves
+examining how donations have changed over time and how many donors have
+continued to donate over time.
+
+This plot illustrates the total donations made to the
+[`Pandas`](https://pandas.pydata.org) project over time. Notably, donations
+reached an all-time high in April 2022 but have since declined. As of September
+2024, there has been a slight rebound in donations; however, they remain at less
+than one-eighth of their peak average.
+
+![Pandas donations](./total_amount_donated_pandas.png)
+
+On the other hand, the plot below shows the total amount donated to the
+[`Babel`](https://babeljs.io) project over time. One interesting observation is
+that donations spiked in the beginning of 2021. This spike was likely due to the
+project's widespread usage during the global pandemic, as many developers turned
+to open-source tools to build applications.
+
+![Babel donations](./total_amount_donated_babel.png)
+
+## Getting started
+
+To get started with the Open Collective transactions datasets, you can access
+them directly in BigQuery. The datasets are available in the
+`opensource-observer` project. For instance, getting the total amount of
+donations per month in USD can be done with the following query:
+
+```sql
+SELECT
+  DATE_TRUNC(DATE(created_at), MONTH) AS donation_month,
+  SUM(CAST(JSON_VALUE(amount, "$.value") AS FLOAT64)) AS total_amount
+FROM
+  `opensource-observer.open_collective.deposits`
+WHERE
+  JSON_VALUE(amount, "$.currency") = "USD"
+  AND DATE(created_at) >= DATE("2020-01-01")
+GROUP BY
+  donation_month
+ORDER BY
+  donation_month;
+```
+
+This data can then be visualized to gain insights into donation patterns and
+trends. We can see that donations in Open Collective have massively increased in
+the last year, with almost **8M USD** donated in the last months.
+
+![Total donations per month](./total_amount_donated_oc.png)
+
+These are just some examples of the insights that can be gained from the Open
+Collective transactions datasets. We hope that these datasets will be useful for
+researchers, data scientists, and anyone interested in understanding the flow of
+funds in the open-source ecosystem.

apps/docs/blog/authors.yml

@@ -15,3 +15,9 @@ ravenac95:
   title: Engineer
   url: https://github.com/ravenac95
   image_url: https://github.com/ravenac95.png
+
+jabolol:
+  name: Javier Ríos
+  title: Engineer
+  url: https://github.com/jabolol
+  image_url: https://github.com/jabolol.png

apps/docs/docs/integrate/overview/index.mdx

@@ -15,6 +15,7 @@ import GitcoinLogo from "./gitcoin.png";
 import OpenrankLogo from "./openrank.png";
 import ArbitrumLogo from "./arbitrum.png";
 import EasLogo from "./eas.png";
+import OcLogo from "./open-collective.png";
 
 First, you need to set up your BigQuery account. You can do this by going to the
 [Get Started](../../get-started/index.mdx)
@@ -570,6 +571,41 @@ where
 
 **Remember to replace 'YOUR_PROJECT_NAME' with the name of your project in the query.**
 
+### Open Collective Data
+
+<img src={OcLogo} width="200" />
+
+<Button
+  size={"compact"}
+  color={"blue"}
+  target={"_blank"}
+  link={
+    "https://console.cloud.google.com/bigquery/analytics-hub/exchanges/projects/87806073973/locations/us/dataExchanges/open_source_observer_190181416ae/listings/open_collective_1926d37f24d" 
+  }
+  children={"Subscribe on BigQuery"}
+/>{" "}
+
+- [Reference documentation](https://models.opensource.observer/#!/source_list/open_collective)
+- [Updated weekly](https://dagster.opensource.observer/assets/open_collective)
+
+[Open Collective](https://opencollective.com/) is a platform for transparent finances and governance for open source projects.
+
+The Open Collective datasets contains all transactions realized on the platform since its inception. Separate datasets are available for **expenses** and **deposits**.
+
+For example, you can get the total amount of donations in `USD` made to the [**pandas**](https://pandas.pydata.org) project:
+
+```sql
+select
+  SUM(CAST(JSON_VALUE(amount, "$.value") as FLOAT64)) as total_amount,
+from
+  YOUR_PROJECT_NAME.open_collective.deposits
+where
+  JSON_VALUE(amount, "$.currency") = "USD"
+  and JSON_VALUE(to_account, "$.id") = "ov349mrw-gz75lpy9-975qa08d-jeybknox"
+```
+
+**Remember to replace 'YOUR_PROJECT_NAME' with the name of your project in the query.**
+
 ## Subscribe to a dataset
 
 ### 1. Data exchange listings