An Introduction to Aid Data

Curriculum

6 Sections
35 Lessons
Lifetime

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Introduction to aid data
Welcome to the world of aid data! In this first module, we’ll be starting from first principles: what do we actually mean when we say ‘aid’, and why is looking at aid data important?
5
A guide to IATI data
One major source of aid data is made available through the International Aid Transparency Initiative (IATI). There are a few different ways that you can access raw IATI data, so here’s a quick run through of what you can get, and where it is, including IATI data itself as well as data about IATI data (metadata).
6
Cleaning IATI data with OpenRefine
So once you've got the raw IATI data, what next? Often it might need 'cleaning' - here, we'll use a sample IATI dataset to learn how to use a powerful cleaning tool, OpenRefine.
5
An introduction to OECD-DAC data
Another major source of data available about international development data, is the OECD. Here, we run through a few ways that they make this data available, and where to find what you're looking for.
8
Inspiration module: how is aid data used in the media?
We've seen a few ways of where to find aid data, how to clean it and use it - but how is this applied in the real world? Here are a couple of examples of 'reverse engineering' aid data that we might come across in the media - maybe it will give you some ideas!
6
Jargon busting the world of aid
This module is intended as a reference point while you're going through the other modules. In each case, the relevance of the term to working specifically with data is highlighted to try and make it clear what you should be looking out for when you come across the term in your work.
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Strengths of the OECD-DAC data

Comprehensive: The data included here is fully comprehensive for what is defined as “Official Development Assistance”, and reporting to the database is mandatory for all 29 DAC member countries.

Less risk of double counting: Within the dataset itself, you don’t have to worry about double counting – ie. the same activity or event being counted more than once. This is a weakness of other aid datasets.

Validated/good quality: The data has been validated through the Development Cooperation Directorate, and via Peer Reviews (more information here)

Comparability: there are standard criteria (codes for sectors, types of aid, terms and conditions) – which are used universally, making the data comparable between donors, and over time

Historic: the data goes back as far as 1960 (in some cases; it’s not all complete)

Measuring against targets: the data is useful for measuring against commitment levels (eg. are donor countries meeting the 0.7% of GNI target?) – and, to a degree, sectoral targets, and geographical targets.

Things to understand before diving into the data

Weaknesses of the OECD-DAC data

An Introduction to Aid Data

Curriculum

Strengths of the OECD-DAC data

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