Local Digital Fund Networks
In an effort to beef up on network analysis skills, we’re hoping to map the UK government ecosystem into a network to see what we can learn from it. The MHCLG’s Local Digital Fund aims to “help local authorities break their dependence on inflexible technology, adopt the best digital ways of working, and ultimately offer excellent local services for less”. The initial stage of applicants helps to identify potential projects with shared ideas to help councils partner up on bids.
We have been building a data set including all the UK local government entities, central government organisations and companies involved in digital projects linked with these. This has been compiled from various different sources including a list of local authorities and details about them (taken from registers and gss codes) and the list of government organisations at gov.uk.
The initial application digital fund data was made available at https://localdigital.gov.uk/fund/projects-submitted/
We took these applications, mined them for relational data and turned this into a network using our new government data set. The relationships are based on applicants to projects and partners to projects. We are aware that these relationships are going to be constantly changing and evolving as the projects move on and want to keep the network up to date with more data from MHCLG.
The data was messy and took a lot of cleaning before we were able to create relationships. Government departments do not have a code that commonly identifies them so we created our own. This is a stand alone issue that Ben from Satori briefly mentions here. When we pull in data like this, we would love to be able to process it automatically. If the project data had linked to registers with these organisations in, or if the initial application form could link to these registers, it would make processing the data much easier. This is something for future projects to consider.
An initial representation of the network can be found here with nodes coloured by type (organisation or project) and sized by degree (how many other nodes they link to). We can already see a few councils with links to many projects, either as an applicant or a partner. We’re going to keep adding attributes to the network to get a better picture of how this relationships work and any outcomes from them.
We’re currently building a multi purpose network visualisation tool so anyone can filter the data themselves and we can add in all the attributes from the data set. Please keep in touch and let us know what useful things you would like to know from this data or if you have other data that you think would benefit from being visualised as a network.
https://thesatorilab.com/contact-us/
Our digital fund relational data is available here
