We want to use IATI data to create a network visualisation of the connections between funders, international NGOs and local NGOs. For us, this is about spotting where organisations are clustering rather than collaborating within a specific context or country as well as seeing how they link up. A very basic example is here: https://www.google.com/fusiontables/DataSource?docid=1VfPqITAxt2rzZTBRXlcr0YlaDfIToX1us0atuss8 (Chart 1 tab). This is data on organisations working on international development in Nepal. The viz shows the relationship between the funding organisations and the implementing organisations, weighted by total disbursements. We wanted to see if there were any patterns, for example, organisations receiving funding (orange node) from more than one funder (blue node).
I just wondered if you had any advice about things to be careful of, when creating a network visualisation. We can cut the data in very different ways, which mean the story we tell will also be different. And the quality of the data will also affect this - for example, there are funders who do not name implementing organisations - you can see this by the big orange blob connected to many funders. This network viz also shows that where organisations have different names in the data (DFID and Department for International Development), they appear as different nodes. If there any other ‘gotchas’ that we should watch for based on your experience, it would be really useful to know this. Thank you IATI Community!
I find that with “IATI-wide queries” across all available data, there is quite a bit of curation to do:
I’ve done a query on all activities from NGOs (types 21,22,23) with recipient-country Nepal: it’s a big graph, and there are some errors on my end to resolve, but it’s the sort of output that helps me feedback to organisations on their data quality.
https://www.drostan.org/wp-content/uploads/2016/02/nepal.svg
For instance, use “Find” and look for “ActionAid United Kingdom”, you’ll see:
Hope this is helpful, although perhaps not hopeful
Rolf Kleef Just looked at your SVG link and my brain exploded. But also really useful, thanks for sharing.
Thanks Steven, really helpful. We’ll be using OIPA to pull the data so hopefully that will get around the datastore/csv issue. We’re looking at Gephi for initial analysis of the data at the moment as it’s a bit more in-depth than Fusion. Data quality I think is going to be a bit of an issue too, where the data is missing. For this reason, I’ve using the data in the transactions (incoming funds and disbursements) and provider and receiver orgs as the relationships are clearer than in participating orgs.