As I mentioned in Parts 1 and 2, over the last couple of months I set out to systematically update Points of Interest in four adjoining barrios in the city of Málaga.

A few businesses really did open, close, or change hands over that short period. But the vast majority of the changes in the data reflect the OSM data “catching up” with reality: adding points that had never been mapped in OSM, or updating POIs that had changed in some way since they were last touched by an OSM mapper.

Adding leisure POIs

Closely examining changes over a period is a good way of revealing faulty assumptions. I noticed that three shop locations had disappeared from my data, even though I was sure there were still businesses at those addresses. They are all gyms now, and gyms are tagged as “leisure” - a tag I had completely ignored. I’ve now added leisure POIs. As with “amenity” tags, I excluded some high-volume tags such as “garden” and “swimming pool”. I now have 392 POIs in my current dataset, not 376 as I mentioned in previous diary entries.

Changes over the period

	POI count	count distinct feature tags
mid Aug 2024	267	96
+ newly created	141	34
- removed	(16)	(9)
late Oct 2024	392	121
% change	+47%	+26%

I mentioned in a previous post that I thought that POIs were reasonably well mapped in this neighbourhood. The numbers suggest that about two thirds of POIs were mapped two months ago. That seems respectable, but not great. There has not been any major expansion of retail space in this area recently. Some of the new additions are locations that were vacant or derelict when the area was first mapped in detail, but the majority have existed for a long time and were simply never mapped in OSM.

Most of the removed POIs are now mapped as with a “disused:” life cycle tag (and thus excluded from my data). These are premises that could still be used for retail, but are currently vacant. In a few cases the original POI has been deleted completely, where the building has been demolished or the retail space has been absorbed by a neighbouring shop.

Many of the POIs added and removed had unique tags, so the number of tags changes roughly in line with the number of POIs. But it increases at a slower rate, as we would expect - the more POIs we map, the more likely a new POI will be of a type already in the data.

Evolution of the POIs in the original dataset

Ignoring the newly added points, this is what happened the 267 POIs already mapped in mid August:

	number of points	as %
no major change	209	78%
removed	16	6%
changed POI type	28	10%
changed name	14	5%
total	267	100%

The changes of POI type are mainly genuine changes of use, often to something very different: a greengrocer to a coworking centre, a clothes shop to a beauty salon for pets, an electronics shop to a laundry. The name changes usually reflect a change in ownership or a a significant rebranding. Only a small share of both types of change is due to improved tagging of a POI that did not change in reality.

Almost 80% of mapped POIs were already up to date when I started checking (ignoring minor changes such as contact details or spelling errors). Again, this seems fairly respectable in isolation. But combined with the POIs that were missing completely, only 53% of POIs were mapped correctly. That’s a lot less than I expected when I started all this.

Changes by POI group

Were some types of POIs better mapped than others?

feature group	count new	count old	change	% change
amenity - food+drinks	56	49	7	+14%
amenity - general	48	33	15	+45%
craft - general	14	3	11	+367%
healthcare - general	26	17	9	+53%
leisure - general	16	13	3	+23%
office - general	42	17	25	+147%
shop - clothes	15	17	-2	-12%
shop - food	52	45	7	+16%
shop - for the body	51	24	27	+113%
shop - general	61	42	19	+45%
tourism - general	11	7	4	+57%
total	392	267	125	+47%

Most eateries (restaurants, cafes, bars) were already on the map, as well as most food shops (supermarkets, greengrocers, bakeries and so on).

Of the main groups, “for the body” stands out as undermapped. I have already talked about the high proportion of shops in the area that are hairdressers or beauty salons. The majority had not been mapped previously: the number increased from 15 to 38. In fact “shop=hairdresser” is now the most common single tag, well ahead of “amenity=restaurant” which was the leader until two months ago.

It’s also clear that offices and crafts were undermapped. The increase in these categories was spread across a wide range of POI types. I did notice an increase in business related to the sale and management of property (including vacation rentals), but that only accounts for at most 10 extra POIs. I could have mapped even more offices, but as I mentioned in a previous post, I generally didn’t add businesses identified only by a plaque in a doorway.

So, it seems that over the years, local mappers (including me) have tended to focus more on some categories of POI than others. That might be due to the nature of the POIs themselves: offices are often not very interesting, hairdressers tend to open and close rather frequently, mappers tend to add cafes where they eat themselves, and so on. But it might also have something to do with…

Location, location, location

Looking at the map, it’s clear that a lot of the new POIs are in the northwest corner of the area of interest. Apparently neither I nor other mappers ever paid enough attention to this group of streets. Until I started my systematic survey, I had thought of these streets as almost entirely residential. In fact they contain quite a few small retail businesses. To some extent the same applies to other side streets. It probably doesn’t help that I do most of my surveying at night, when many of these shops are completely shuttered and attract very little attention. Shops on the main streets tend to be a little more obvious even when they are closed.

This pattern inevitably influences the results I described above. It seems quite possible that hairdressers, crafts, and offices were undermapped not so much because of anything intrinsic to these businesses, but because they are more likely to be located away from the busiest streets.

In my next diary entry, I’ll look at how the POIs in this area evolved over a much longer period.