Thanks for your suggestions, Dave F. I’ve created a number of issues in the
GitHub repository (see links below). I won’t have time to improve the code for
a while, but at least we will be able to keep track of suggestions. I am of
course open to pull requests if anyone wants to have a go at improving it.
> The latest total for this district is 1767, so appears a bit more than a week
> behind.
> Could the update date be added on the page so there's a guide to their
> accuracy?
There is a date/time at the bottom of each district page, which reflects when
that HTML page was generated. The update script gets the FHRS data using their
API and downloads OSM data from GeoFabrik before processing the data and
creating the HTML pages and JSON files which feed the slippy maps. The whole
process takes an hour and a half ish.
The GeoFabrik data is probably a bit behind, but this seems the most convenient
way to obtain large amounts of OSM data without having to filter the entire
planet file.
https://github.com/gregrs-uk/python-fhrs-osm/issues/4
<https://github.com/gregrs-uk/python-fhrs-osm/issues/4>
> Could a 'Relevant OSM nodes/ways without fhrs:id' statistic be added?
Probably, although the goal of the tool is really to improve the OSM address
(and particularly postcode) data, hence the ‘Relevant OSM nodes/ways without
fhrs:id or postcode’ statistic instead. (There are generally quite a number of
establishments with a postcode but no fhrs:id, although in Bath and NE Somerset
I see there are loads of establishments with an fhrs:id but no postcode.)
https://github.com/gregrs-uk/python-fhrs-osm/issues/5
<https://github.com/gregrs-uk/python-fhrs-osm/issues/5>
> A Download (as Geojson?) of the mismatched/missing lists would be very
> helpful.
JSON files are already created to feed the slippy maps, so could you try
[http://gregrs.dev.openstreetmap.org/fhrs/json/overview-270.json
<http://gregrs.dev.openstreetmap.org/fhrs/json/overview-270.json>] for example?
What were you hoping to use the downloaded files for? Let me know if the linked
one already does what you’d like and I can add links to the HTML pages.
> Does it check relations?
No, just nodes and ways at the moment.
https://github.com/gregrs-uk/python-fhrs-osm/issues/6
<https://github.com/gregrs-uk/python-fhrs-osm/issues/6>
> I'm a bit confused. It says:
> 'Relevant OSM nodes/ways without fhrs:id or postcode' = 173
> but then says:
> 'Percentage of relevant OSM nodes/ways with FHRS match or postcode' = 6.3%
> Am I misunderstanding something?
I’ve been through the code that generates the stats again to check what’s going
on.
‘Relevant OSM nodes/ways without fhrs:id or postcode’ – seems to be OSM
nodes/ways which have neither an fhrs:id that matches one in the FHRS database
nor an addr:postcode.
‘Percentage of relevant OSM nodes/ways with FHRS match or postcode’ – this
includes OSM nodes/ways which have an fhrs:id and postcode that both match the
FHRS database, and those with a postcode but no fhrs:id. This doesn’t include
those with a non-matching fhrs:id, or those for which the postcodes don’t agree
(including cases where the OSM postcode is not set). This is probably what is
misleading because the large number of establishments in Bath with a valid
fhrs:id but no postcode will not be included. It’s meant as a measure of
‘completeness’ really, with the goal to tag establishments with a postcode and
possibly an fhrs:id. I think the label probably needs changing though.
https://github.com/gregrs-uk/python-fhrs-osm/issues/5
<https://github.com/gregrs-uk/python-fhrs-osm/issues/5> again
Thanks,
Greg.
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