I’m David Kane, and I joined CAST in January as a Data Scientist working on Beehive Giving, the fundraising tool that’s incubated by CAST. Before joining CAST I was a researcher at NCVO, working on trends and data about the charity sector.
Part of getting to grips with Beehive has been about making sure that we’re getting the most out of our source data. Beehive is unique: we use open data published by funders themselves to the 360Giving open standard, to build recommendations for charities on who to apply to. So far the platform has successfully matched over 9,000 UK charities to funding opportunities. It saves both nonprofits and grantmakers the time of having to manually check eligibility, boosting applicants’ chances of success.
We’re always looking for ways to improve the insights Beehive provides, and deliver more value to our users. One way to do this is by combining different open datasets so that we can reveal additional information and interesting comparisons.
As part of this I’ve written a short report looking at the data published by a new 360Giving publisher: the Cabinet Office, which has published data about its “Community First” fund. I’ve put together a blog post for 360Giving about the analysis, and how the 360Giving data standard makes linking datasets together easy.
As part of working in the open I’ve made the code available too, on github. You can see the python notebooks I’ve used to go through the process of cleaning, analysing and linking the data.
This kind of analysis is a flavour of what powers Beehive, and it shows how powerful the combination of linked open datasets can be.
If you’re a fundraiser, let us know how you’d use Beehive and what more you’d like to do with it. You can email us at email@example.com — all feedback is extremely valuable and will help us shape a better, more useful product.