pinardag/eu-structural-funds

The EU structural funds datasets on regional and national level (in progress).

EU Cohesion and Structural Funds

Introduction

Structural and Cohesion Funds are financial tools set up to implement the regional policy of the European Union. They aim to reduce regional disparities in income, wealth and opportunities. The overal budget for the 2007-2013 period was €347 billion according to wikipedia.

This repository is a data pipeline. It channels information about the beneficiaries of the funds into the Open-Spending datastore. The goal is to provide a unified dataset that is easy to visualize and query, so that citizens and journalists can follow the money on a local and global scale.

This project is a collaborative effort between Open-Knowledge Germany, Open-Knowledge International and a number of journalists and developers. This repository builds on research and sourcing work that was previously organised inside a google spreadsheet.

What's in here?

The repository contains the following:

• data/: all the data goes in here
• resources/: project documentation and ancillary data
• fields.official.yaml: the list of fields we expect in the raw data
• geocodes.nuts.yaml: the nomenclature for naming countries and regions
• datapackage.template.raw.json: the template for raw datasets
• datapackage.template.fiscal.json: the template for fiscal datasets
• codelist.yaml: describes category fields common to all datasets

Philosophy

We believe that data pipelining is a fine blend of manual and automated processing. We believe in the almighty power of Frictionless-Data to glue the two together. We believe over-engineering is a sin, albeit a really enjoyable one (note to self).

How do I contribute?

Before you decide what to do, please:

• Check out data pipeline
• Read the contribution guidelines
• Register on Slack
• Check-out the list of issues

There are many ways to contribute, depending on your skills. You can:

• Source, document and download datasets
• Send FOAI requests for missing datasets
• Describe, translate and clean-up datasets
• Write python spiders to scrape datasets
• Write python ETL scripts to automize processes
• Raise issues about bugs in the code or the data

Please adhere to the following workflow (note to self):

• Fork the repository
• Create a new branch
• Make your contribution
• Send a pull request.

Thanks!