A look at Coops UK Cooperative Economy Open Dataset 2015

Asking “How can we easily match organisations ?”

During the P6Data hack day, I got to talking with Michelle and Paul from Coops UK, the UK co-operative network. They’ve released a UK Cooperative economy dataset, which is an excellent start to their open data publication journey.

After a critical look at the dataset and guide (guys! they have documentation!), alongside the use cases that came out of P6 Data: “How the heck do we share data more smoothly?”, we came to some conclusions:

1. We really need a data exchange standard that’s lightweight and we don’t want to reinvent the wheel (we’ll come to that later).
2. We really need to know: Who’s the registrar and what’s the organisation type? This will help match organisations from one list to organisations from another.

How? Read on.

So Coops UK provide the registrar’s number for most of their members (except schools and a few other edge cases like unincorporated organisations, more on that later too). On the downside, it’s a single column all smooshed up together. On the upside, a simple (!) set of rules means we can work back and find out the organisation type *and* the registrar. Happy days! [See table below]

So what does this do for us? Ultimately, by knowing the registrar, we can:

Exchange information with other organisations: we can all match on something better than name.

For example, instead of trying to match Littleton and Badsey Growers Ltd and Littleton and Badsey Growers Limited or even Littleton & Badsey Growers, you can match Companies House’s Company Number 04518100. Much simpler

Check the registered number is right: At least with modern regulators like Companies House who provide a unique location (URI) for every company, here’s Littleton & Badsey Growers.

We can do that right in Excel, Open Refine or your preferred spreadsheet/wrangling programme. We can ask our friendly developers to add this feature to customer relationship management systems like SalesForce or plan.io. This means one less task when your organisation tries to reconcile a list from another organisation.

Here’s an example in Open Refine where I’ve worked out the registrar, the organisation type and the link to that organisation at the FCA’s mutual registry (the FCA URI).

Get even more relevant information: Given more time, we could pull out particular things we’re interested in, for example, what’s their current  status as a mutual or is a company incorporated and since when?

All this from a small extension to the existing dataset, which you can find here: Co-Operative Economy Extended Dataset derived from Coops UK Co-Operative Economy Open Data, released under the Open Data Commons Attribution License (ODC-by v1.0).

Corrections, updates and stories about what you’ve done with this dataset are welcome.

Working out the registrar – a simple guide (based on best guess)

A huge thank you to our collaborators and hosts: