This allows MNOs to test delivery to multiple non-adjacent cells without
risk of sending a broadcast on the public network. This will also support
testing of multiple polygon geometries in a single message.
Test polygons are all non-UK (northern Finland).
Signed-off-by: Richard Baker <richard.baker@digital.cabinet-office.gov.uk>
I emailed the Geography team at the ONS:
> Hi geography team,
>
> I work on GOV.UK Notify, which is a service run by Government Digital Service (part of the Cabinet Office). I was given your email address by [redacted] who’s been helping answer some of my questions on the cross-government Slack.
>
> We’re using some of the boundary datasets from the Open Geography Portal, and mostly they’ve been excellent.
>
> In the abstract, the problem we’re trying to solve is, given a point outside an area, what is the minimum distance to a point within that area. So, for example, if a crow was somewhere in Cardiff, what’s the shortest distance it would have to fly to reach somewhere in the Bristol local authority district?
>
> We’ve noticed some problems with the data that means our calculations would be wrong. We’ve noticed this around Torquay, Norwich and Bristol. Here are some screenshots of Bristol, from the generalised and full resolution boundaries:
>
> The artefacts I’ve highlighted are closer to Cardiff than any actual part of the land area of Bristol. They are either:
> - in the sea
> - land that’s part of North Somerset
>
> I suspect that this is being caused by the process of clipping the actual region of Bristol (which, unusually, extends into the water) to the mean high water line.
>
> I’ve worked around this by filtering out any polygons that are smaller than ~7,500m². It’s a bit hacky because parts of the Scilly Isles start disappearing. That’s not a problem for what I’m working on, but it would be nice to not need the hack.
>
> So my questions would be:
>
> - Is there a better way to remove these artefacts than filtering by area?
> - Is there a plan to remove these artefacts from the data in future releases?
>
> Thanks in advance,
> Chris
They emailed back to say:
> Hi Chris
>
> Thank you for your enquiry.
>
> We have completed the amendments to the LAD MAY 2020 BFC and BGC boundaries as mentioned so you should be able to download them from the portal now.
>
> Hope this helps.
>
> Kind regards
> [redacted]
This commit brings in the files they’ve updated. We still have to do
some filtering (but now at a higher resolution) because they haven’t
fixed Norwich yet. I’ll email them separately about that.
We need to give people a better feel for the consequences of
broadcasting an alert. We’ve seen in research that some users will
assume it is subscription based, or opt-in, rather than going to every
phone in the area.
I reckon that the most effective way to communicate this is to put some
numbers next to the areas, to give people an idea of how many people
will get alerted.
We can estimate how many phones are in an area by:
- taking the population of all electoral wards in that area
- multiplying it by the percentage of people who own an internet
connected phone[1]
The Office for National Statistics publish both these datasets.
The number of people who own an intenet connected phone varies a lot by
age. Since the population data for each ward is broken down by age we
can factor this in. Simplified, the calculation looks like this:
- take the _Abbey_ ward of _Barking and Dagenham_
- in this ward there are 26 people aged 80
- 40% of people over 65 have an internet-connected phone
- therefore 10 of these 80-year-olds would be likely to receive a
broadcast
- (repeat for all other ages)
These numbers won’t be exact, but should be enough to give people a feel
for the severity of what they’re about to do. We can see if they acheive
this aim in user research.
1. This is a proxy for the number of people who are likely to have a 4G
capable phone, because only 4G capable phones will be receiving
broadcasts to begin with
maps lower tier local authorities to upper tier local authorities -
translation for humans: Maps districts to the counties that they are in.
For counties, a row looks like:
`255,E07000105,Ashford,E10000016,Kent`
(E07000105=Ashford, E10000016=Kent)
For unitary districts it maps that district to itself, eg:
`49,E06000052,Cornwall,E06000052,Cornwall`
where both codes are the same
