Visualised #2: Grants awarded by the National Lottery Heritage Fund
The National Lottery Heritage Fund is the largest dedicated funder of heritage in the UK. They support a mind-bogglingly broad range of projects through grants of between £3,000 and £5m (and above via the Heritage Horizon Awards).
It’s actually pretty hard to put together a short, representative list of the types of things they’ve funded over the years.
In April 2019 the Heritage Fund released data about the grants awarded between 2013 and 2019. This was released as Open Data, meaning that it can be “freely used, shared and built-on by anyone, anywhere, for any purpose”.
The post announcing this release highlighted a few interesting tidbits from the data and said:
You can discover more interesting facts and figures by investigating our data for yourself
So to help with that, we’ve taken it upon ourselves to create a simple data explorer. To see the full size version click on the image or here: NLHF Grants Awarded (April 2013 to March 2019).
Some data visualisations are trying to tell you a story and perhaps drive you towards a conclusion. This isn’t one of those. We call this type of visualisation an ‘explorer’.
It’s a tool that can be used to dig through a mountain of data relatively quickly. This sort of thing is very useful when we’re working with a new client and want to get to grips with their data as quickly as possible.
As well as the filters for region, programme, and financial year, you’ll find that the tables, bar chart and map are also clickable, allowing you to investigate specific items.
Behind the scenes
The data comes from the Heritage Fund’s Open Data page. It was added to a Google Sheet that was then connected to Google Data Studio. We haven’t had to do much in terms of cleaning up or aggregate the data - we’ve presented it as it is.
Work on this explorer was done by Alix, with feedback and suggestions from Tess and Chris.
Want more visualisations?
This post is the second in our Visualised series where we’re taking cultural sector data and making it more accessible through visualisations.
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