Wiki: Swiss GWR Address Data Import Guide

We had a good discussion at the November meetup, but I feel even more
frustrated than then, when I realized my hours of collecting address
data is gone, erased.

The section about Data Cleanup has to vanish from the import proposal in
my opinion. For mappers investing their time this is just so so painful,
everything gone just to save a bit of time for an importer.

Why are you still importing new stuff instead of fixing your unaccepted
imports. That was also topic that evening and that is precisely why we
we should immediately revert such imports. No one ever comes back and
does the work.

Even though I greatly appreciate @spalinger 's effort to complete the address mapping, I am also in favor of stopping/reverting these imports until a common consensus has been reached.

The word frustration also applies to me, because many hours of careful work have, in my eyes, been made worse.

How do you all see it? Can I revert the changesets that I think have made the situation worse than before?

Sorry @spalinger , I know you only meant well. I hope that we don’t discourage you from continuing to invest your time in OSM with this kind of negative feedback.

And to the people at the fondue meetup: did you have discussed the way we want to handle duplicate addresses (for example on all POIs or multiple entrances) if we tag the address on a node? This data redundancy is for me the main driver to tag addresses if possible to the building outline.

I’m truly sorry to hear this. The last thing I want is for dedicated mappers like yourself to feel disheartened or frustrated because of my imports. Your work has significantly improved the quality of OSM, particularly in Cham, and that’s something to be celebrated.

From our discussions, I didn’t get the impression that my imports, including those in Cham, were unwelcome—especially as you had mentioned you wouldn’t revert the changeset at the time. Following the November meetup, I took your feedback seriously and reviewed the import carefully. I did remove imported addresses that corresponded to removed buildings. I had hoped this addressed the concerns raised.

Furthermore, I noticed that Cham’s older buildings lacked accurate geometer records for addresses. To address this, I reported over 40 cases of incorrectly positioned entrances to madd in a single email. In total, I have sent 12 emails to madd regarding various issues to help improve the GWR and ensure their data can better support mapping efforts in the future.

I’ve stopped importing in areas with active mappers (defined as areas with 50% or more address coverage) since receiving the first critical feedback (Grüningen). If the community believes my imports are unwelcome, I’m happy to stop entirely. Until there is a clear consensus, I will not proceed with any new imports.

Of course, I don’t want to cause frustration or discourage active mappers like you. It would still be helpful for the community if you could point out the specific changes or aspects that have made the situation worse, so everyone can better understand the concerns.

No, this wasn’t discussed.

Allow me to emphasise this again: please provide any specific examples of problematic imports you come across so that I can address and correct my previous changesets. With over 93,000 (net) imported addresses, some errors are unavoidable. However, I believe this process has resolved a multitude more issues than it has created.

To assist, I’ve compiled a list (diff) of all municipalities where I’ve performed imports. While the list may include one or two municipalities I didn’t personally import—due to similar import styles—the average improvement in address coverage is 79%, with a median improvement of 90%. In most cases, I focused on municipalities with less than 10% matching address coverage. Some areas may have risen only to around 50% coverage, as I filtered out subordinate addresses during the import process.

Diff:

Diff Total Switzerland -105002 12596 105794 -15400 121194 99042 8 15659 -150580 -7231 -10148 -40 -5147 -2120 -2199 -22360
Diff Total Imports below -3418 1021 93804 -22227 116031 99320 79.07 1083 -102122 -5822 -7656 -34 -1616 -1574 -1448 -12004
Municipality Canton GWR GWR ancillary OSM Total OSM Buildings OSM Nodes Matching % Matching ▾ Matching ancillary Missing Different or missing postcode Different or missing city Distance more than 50 m addr:street instead of addr:place addr:street/ addr:place missing Non-GWR Warnings total
Arbaz VS -1 -2 906 -5 911 907 100 1 -908 -4 -4 -2 -6
Bedigliora TI -174 -30 398 -3 401 398 100 -438
Damphreux-Lugnez JU -7 6 301 -2 303 294 100 7 -301 -2 -2 -2 -2
Inden VS -4 3 234 -1 235 227 100 3 -231 3 3
Courtedoux JU -6 6 461 -1 462 455 100 6 -461
Embd VS -1 1 503 -1 504 503 100 1 -504 -1 -1
Rossa GR -1 1 352 1 351 354 100 -355 -1 -1 -2 -3
Saubraz VD 134 134 134 100 -134
Buseno GR -2 2 217 217 217 100 -219
Castaneda GR -2 1 232 232 234 100 -236 -1 -2 -3
Saint-Martin (VS) VS -25 22 1540 -23 1563 1528 99 22 -1553 -2 -2 -13 -16
Visperterminen VS -3 2 1702 -17 1719 1701 99 2 -1704 -1 -2 -1 -1 -4
Saint-Barthélemy (VD) VD 216 -11 227 224 99 -224 -2 -8 -10
Movelier JU -19 19 367 -4 371 348 99 19 -367 -1 -1
Vernayaz VS -20 18 604 -3 607 590 99 19 -610 -1 -4 -5
Törbel VS -3 3 933 -2 935 924 99 3 -927 1 1
Ballens VD 175 -1 176 176 99 -176 -1 -1 -2
Villars-sous-Yens VD 179 -1 180 178 99 -178
Fideris GR -3 3 534 1 533 539 99 -542 -3 -3 -1 -6 -9
Grandfontaine JU -9 9 342 2 340 333 99 10 -342 -1 -1
Oppens VD 69 69 69 99 -69
Treytorrens (Payerne) VD -1 1 75 75 75 99 -76 -1 -1
Missy VD -1 1 130 130 130 99 -131
Dittingen BL -8 8 441 441 442 99 -450 -1 -1
Staldenried VS 728 728 727 99 -727 1 1
Brislach BL -19 19 874 874 872 99 -891 -5 -5 -2 -7
Salgesch VS -4 1 913 -9 922 906 98 5 -910 -5 -1 1 1 -4
Chevilly VD 101 -7 108 105 98 -105 -4 -4
Bettens VD 154 -1 155 154 98 -154
Ergisch VS -11 418 418 407 98 -417 1 8 9
Stalden (VS) VS -9 9 784 -25 809 773 97 9 -782 2 2 -2 -2
Cœuve JU -4 2 399 -19 418 403 97 2 -407 -1 -7 -8
Varen VS -2 1 576 -15 591 580 97 -582 -15 -15 -4 -18
Bure JU -10 10 450 -14 464 440 97 10 -450 -9 -9 -1 -10
Hüntwangen ZH -5 418 -11 429 409 97 1 -414 -8 -8 -2 3 -6
Anniviers VS -29 26 5544 -9 5553 5416 97 26 -5445 -41 -125 -4 -1 -5 -130
Wichtrach BE -60 60 205 -8 213 1275 97 60 -1335 1 -127 16 -111
Lalden VS -10 172 -5 177 173 97 -181 -2 -1 -3
Oberems VS -150 217 217 214 97 -253 3 3
Courtételle JU -16 16 1088 -42 1130 1074 96 15 -1090 -1 -15 -3 -5 -24
Saas-Balen VS -1 1 512 -28 540 514 96 -515 -2 -2
Eisten VS -3 3 362 -19 381 359 96 2 -362 1 1
Veysonnaz VS -6 -1 302 -11 313 304 96 -310 -9 -9 -6 -1 -16
Gerzensee BE -4 2 84 -4 88 563 96 41 -567 -161 1 -160
Agno TI -293 -98 972 456 516 960 96 3 -1007 -1 -1 2
Zwischbergen VS -1 1 129 -191 320 305 95 -306 -13 -176 -188
Val Terbi JU -32 30 2070 -61 2131 2003 95 29 -2033 2 2 22 -1 -5 -4 -10
Bettmeralp VS -2 1109 -37 1146 1084 95 -1086 -32 -32 -1 -28 -3 -63
Bovernier VS 477 -25 502 477 95 -477
Eggerberg VS -78 156 -11 167 155 95 -171 1 2 3
Mex (VD) VD 202 18 184 202 95 -202 -2 -2
Boncourt JU -13 13 801 -47 848 788 94 10 -801 -6 -7 -3 -3 -12
Turtmann-Unterems VS -1 1 1005 -35 1040 982 94 1 -983 6 6 6 5
Châtillon (JU) JU -5 5 217 -15 232 211 94 5 -216 -2 -2
Auboranges FR -2 2 150 -1 151 150 94 -152
Courgenay JU -49 46 1038 -79 1117 996 93 42 -1045 -20 -21 -3 -2 -24
Sattel SZ -5 5 907 -48 955 901 93 3 -906 -8 -8 -1 -1 -7 -6 -23
Jaberg BE -4 4 35 -6 41 153 93 18 -157 -66 3 -63
Herbligen BE -11 11 39 -2 41 269 93 7 -280 -4 -4 -84 -89
Leukerbad VS -8 7 1115 -98 1213 1121 92 6 -1129 -28 -28 -24 -46 -97
Wolfhalden AR -1 1 702 -62 764 698 92 -699 -32 -30 -1 -2 -35
Boécourt JU -30 30 472 -45 517 444 92 29 -474 -39 -39 -6 -1 -1 -41
La Grande-Béroche NE -29 14 2356 -211 2567 2398 91 13 -2426 -15 -39 9 -1 -41 -6 -89
Develier JU -15 9 657 -54 711 645 91 10 -660 -1 -1 -17 -2 -20
Luzein GR -13 13 1117 -141 1258 1140 90 -6 -1152 -25 -25 -4 -21 -3 -47
Alle JU -57 57 1014 -104 1118 956 90 56 -1013 -83 -82 -2 -11 -5 -98
Oberweningen ZH -2 2 432 -31 463 413 90 2 -415 -5 -31 5 -26
Wasterkingen ZH -1 185 -20 205 184 90 -185 -12 -12 -12
Cornol JU -12 11 508 -68 576 499 89 8 -511 -10 -10 -1 -11
Vendlincourt JU -8 7 440 -54 494 431 89 7 -439 -51 -51 -1 -52
Basse-Allaine JU -15 15 754 -104 858 743 88 15 -758 -101 -101 -12 -1 -4 -108
Haute-Sorne JU -74 74 2921 -365 3286 2848 87 74 -2922 -211 -198 13 -147 -10 -30 -305
Courroux JU -19 18 1170 -184 1354 1163 87 16 -1182 -30 -34 -9 -3 -8 -53
Bürchen VS -26 26 1100 -177 1277 1075 87 21 -1101 -3 -3 -1 -1 -5
Aesch BL -39 39 2777 -100 2877 2740 87 31 -2779 -197 -372 -3 -57 -5 -19 -388
Sevelen SG -2 2 1319 -157 1476 1308 86 -3 -1310 -68 -77 -8 -4 -80
Saint-Brais JU -2 2 113 -91 204 174 86 1 -176 -26 -26 -1 -11 -33 -1 -63
Niederglatt ZH -3 3 696 -245 941 759 84 3 -762 -106 -140 -3 -50 11 -179
Val de Bagnes VS -38 9 5381 -453 5834 5238 83 19 -5272 17 -34 63 -1 -25 -73 -146
Walchwil ZG -9 -3 901 -148 1049 862 83 -871 -141 -150 -4 -9 -1 28 -127
Guttet-Feschel VS -1 1 470 470 469 83 1 -470
Unteriberg SZ -24 3 775 -146 921 755 81 7 -779 1 1 -3 -1 -5
Uetendorf BE -49 49 216 -14 230 1673 80 51 -1722 -4 -170 1 -174
Münsingen BE -113 113 207 -7 214 2612 79 355 -2724 30 20 9 -41 -458 8 -505
Lupsingen BL -12 12 541 -2 543 540 79 -552 -1 -1 -1 -2
Höri ZH -2 1 455 -113 568 454 78 -456 -3 -14 -2 -9 -24
Illgau SZ -131 26 -45 71 25 76 1 -156 -4 -7 -11
Crésuz FR -3 3 254 254 255 75 -258 -1 -1
Val-de-Travers NE -113 50 2418 -645 3063 2248 73 59 -2356 -5 -13 27 -174 -22 -28 -239
Oberägeri ZG -71 -3 897 -336 1233 885 73 2 -956 -73 -103 -3 -8 1 -111
Glattfelden ZH -7 6 857 -331 1188 879 73 1 -886 -136 -240 -3 -41 -283
Steinhausen ZG -4 2 1111 -280 1391 1086 73 1 -1090 -194 -196 -3 -12 -22 -15 -236
Alpthal SZ 204 -68 272 203 73 -203 -2 -49 -1 -50
Oberiberg SZ -8 -1 363 -141 504 362 72 -4 -370 -54 -54 -1 -51
Schöfflisdorf ZH -6 6 360 -35 395 344 72 3 -350 -12 -31 -2 -1 10 -23
Nenzlingen BL -4 4 181 1 180 180 71 -184 -2 -1 -2
Stadel ZH -4 4 461 -200 661 464 70 -6 -468 -38 -85 -4 -87
Bossonnens FR -7 7 357 -1 358 357 70 -364 -3 -3 -2 -3
Zermatt VS -81 34 1241 -359 1600 1212 69 29 -1277 -256 -313 -3 -24 -14 -346
Dielsdorf ZH -6 6 725 -289 1014 694 68 6 -700 -93 -154 -3 -1 -6 -165
Rothenthurm SZ -6 5 480 -279 759 519 68 3 -525 -85 -79 -3 -10 -14 -2 -105
Chapelle (Glâne) FR 92 92 98 64 -98 -6 -6
Courchapoix JU -2 2 183 -1 184 182 62 -184
Hünenberg ZG -3 2 988 -561 1549 940 59 2 -943 -267 -281 -2 -80 -5 5 -332
Niederhasli ZH -28 28 1666 -333 1999 1592 59 7 -1620 -142 -257 -6 -1 -265
Massonnens FR -4 4 168 1 167 168 59 -172
Wil (ZH) ZH 317 -265 582 323 56 -6 -323 -34 -59 -11 -3 -62
Lully (FR) FR -10 10 313 4 309 311 55 -321 -1 -3 -1 -1 1 -3
Ellikon an der Thur ZH 169 -141 310 168 53 -168 -89 -89 -1 -5 -10 -104
Bulle FR -48 48 2477 -1 2478 2526 52 13 -2574 -244 -262 -2 -17 -27 -39 -346
Gibloux FR -35 35 1817 8 1809 1797 51 7 -1834 15 -54 14 -3 -19 -77
Le Mouret FR -13 12 904 904 908 51 1 -921 -1 -8 -2 -5 -15
Eglisau ZH -2 2 644 -544 1188 653 50 -10 -655 -224 -270 -4 -15 -23 -301
Einsiedeln SZ -77 -18 1986 -1744 3730 1836 49 4 -1911 -101 -142 -27 -49 -6 -99 -318
Courtepin FR -569 -128 1156 -6 1162 1163 49 5 -1707 -11 -11 -1 -8 -14 -37
Sâles FR -10 10 439 5 434 439 49 -449 -4 -5 -5
Bachs ZH -9 9 153 -104 257 190 48 2 -199 -1 -1 -20 -42 -63
Ménières FR -3 3 135 135 135 48 -138 -4 -4 -4
Zug ZG -26 4 1694 -1831 3525 1817 47 1 -1843 -1263 -1308 -11 -125 -25 -28 -1456
Nuvilly FR -5 5 152 152 159 46 -164 -1 -6 -7
Schleinikon ZH -5 5 147 -89 236 163 45 -168 -1 -9 -1 -13 -2 -25
Grüningen ZH -3 3 29 -902 931 401 44 -61 -404 -15 -9 -2 -29 -317 -352
Neuheim ZG -18 -5 195 -240 435 215 43 -17 -233 -17 -17 -3 -22 -3 -30
Steinmaur ZH -18 15 326 -411 737 304 42 13 -322 -17 -179 -6 -9 -189
Baar ZG -87 3 1229 -1426 2655 1096 38 -12 -1183 -285 -298 -8 -44 -5 2 -333
Rüschlikon ZH -51 38 454 -806 1260 453 37 38 -502 -5 -6 -6 -1 -60 -73
Menzingen ZG -116 -10 167 -563 730 205 35 -10 -320 -27 -82 -2 -18 -11 -7 -107
Cham ZG -25 8 514 -736 1250 602 29 8 -627 -349 -509 -10 -185 -8 -60 -706
Risch-Rotkreuz ZG -7 -1 316 -972 1288 314 24 -318 -201 -216 -5 -209 -9 -53 -459
Rheinau ZH -10 10 219 -414 633 204 24 1 -214 -28 -38 -1 -48 -13 -75
Horgen ZH -41 41 768 -2669 3437 961 21 -96 -1003 -206 -217 -5 -35 -20 -93 -354
Unterägeri ZG -2 1 274 -950 1224 303 18 -4 -305 -26 -44 -7 -26 -5 -50 -131
Bütschwil-Ganterschwil SG -5 2 236 -15 251 262 18 3 -267 -11 -220 -10 -95 -32 -345
Saint-Martin (FR) FR -2 2 95 63 32 93 18 1 -95 1 1

I would really like to see the “disembodied” addresses gone. That the
address is either a tag on the building outline or a node which is part
of the outline. Like this was done in Bern. But at least, for addresses
that were mapped before, that the state is restored to what it was before.

I see little opinions on the topic of the unconnected addresses. If this
is really acceptable to the rest of the community for new addresses, so
be it. I have a strong opinion against it. But that still just counts once.

2 Likes

I wasn’t even aware that this option was on the table. As somebody who has to process the address data, I agree: please don’t do that.

The address should go on the building outline or on an entrance node on that outline. In the exceptional case that an address applies to a full property (think “water park” for example) you can also use the plot outline or an entrance node on the plot outline.

A revert of the changeset looks fair as it has removed information that was present before.

1 Like

I tried to get a discussion started on the multi-address / POI in building situation here Wiki: Swiss GWR Address Data Import Guide - #10 by SimonPoole but didn’t get any response.

I’m still of the opinion that this is really the only case for which modelling style is relevant and that we need to agree on. For the single address, no POIs situation it largely doesn’t matter at all, but that is what people are getting all upset about. We have whole countries in OSM that use “address node in building outline” throughout and it hasn’t led to the downfall of western civilisation.

That doesn’t mean that I’m in favour of overwriting existing data, quite the opposite, it is the main reason that I create the “missing address” files with addresses that are either completely missing or are very incomplete on Address Counts per Municipality for Switzerland. By definition using these should have minimal to no impact on existing data regardless of modelling style.

Hi everyone,

Thank you for continuing to engage in this discussion. I appreciate the time and effort from everyone who has shared their perspectives so far. I want to clarify a few things, address some of the key concerns, and propose a way to move forward.


1. Clarification on Address Conversion and Data Deletion

Some comments suggest that I “deleted data” during my edits. I’d like to explain this again in more detail:

  • When I converted addresses from building outlines to unconnected nodes, the data was not deleted. It remains in the database but in a different form—at a more precise location (e.g., the building’s entrance).
  • OpenStreetMap does not support directly “converting” an address from a building outline to a node. This means removing the address from the outline was a necessary step in the process, if more accurate address data is wanted. However, all information was preserved.
  • If there are specific cases where you feel my edits caused the loss of valuable information or introduced inconsistencies, please let me know, and I’ll review those changes.

2. Offering to Revert My Changesets

Revert my changesets if you feel this is necessary.


3. Why Are Unconnected Address Nodes Considered “Bad”?

A recurring theme in recent comments is a preference for addresses on building outlines over unconnected nodes. While I respect differing opinions, I’d like to understand the specific concerns
What specific issues do unconnected address nodes cause, aside from address duplication for POIs ?

From my perspective:

  • Unconnected nodes at building entrances store the same information as addresses on outlines (e.g., addr:street, addr:housenumber, etc.), but add greater precision.
  • They work equally well—or even better—in tools and workflows, particularly for navigation.
  • They are particularly useful when building geometries are incomplete or misaligned, as they make spotting and correcting such issues easier.
  • Statistically, most addresses in OSM worldwide are on nodes (84 million), compared to those on buildings (79 million). While Switzerland differs slightly (1.39 million on buildings vs. 0.52 million on nodes), this indicates that unconnected nodes are a widely accepted practice globally.

I encourage anyone who sees unconnected nodes as problematic to provide clear reasons or examples of practical issues they have caused.


4. Visual Example

Below are before-and-after comparisons from specific areas (Hünenberg, Zug, and Cham) to illustrate the edits:
HünenbergZugCham

As shown:

  • The address data remains intact but is now positioned at more precise locations.
  • Errors were corrected (e.g., “Dorfgässli 10” instead of “0”), and missing addresses were added.
  • In some cases (e.g., Cham), the edits reveal an inaccuracy in building data, making it easier to address.

5. Questions for Voting

To resolve this discussion fairly and reach a consensus, I propose the following questions for community voting:

  1. Are unconnected address nodes acceptable in Switzerland?
  2. Should addresses generally be placed on building outlines (ways) where possible?
  3. Is it acceptable to move addresses from building outlines to unconnected nodes at entrances?
  4. Should changesets that moved addresses from building outlines to unconnected nodes be reverted?
  5. Should POIs in multi-address buildings have addresses?
  6. Should POIs generally have addresses?

If you have additional suggestions for questions or refinements, please share them.
Regardless of the outcome, if you wish to revert any of my changesets (e.g., in areas you focus on), please feel free to do so. My goal is not to discourage or frustrate any mappers, but rather to improve address coverage.


Thank you for your engagement and feedback.

Best regards

1 Like

For the edits I checked in Cham, you moved an address that was at the entrance to some unconnected node somewhere in the middle of the building, e.g. Node History: 4784514688 | OpenStreetMap So I don’t understand what you are saying. Your edits do not move the addresses towards the entrance, they move them away from it.

If you want to have addresses on entrances, that’s perfectly fine but please read the wiki on how to map entrances: the node needs an entrance=* tag and must be placed on the outline of the area it is entrance to.

I’m referring to actual entrances, not the entrance=yes tag. According to the wiki it is not perfectly fine to assign addresses to nodes tagged with Tag:entrance=yes.

Do you map building footprints or roof outlines as building=*? This distinction was briefly addressed earlier in this thread. Typically, the entrance is not located directly under the roof outline, which is also why the address nodes are not placed on roof outline nodes.
If the building outline were imported from the AV, I wouldn’t object to placing the entrance node on the outline—provided this mapping style has certain advantages.


  • Red: OSM
  • Imported address: Blue-marked red dot
  • entrance=yes: Red dot
  • Background: AV

In the location you referenced, the manual mapping of addresses to entrance=yes nodes by @datendelphin contains three (or possibly four, if you include the recessed entrance) errors in entrance positions, highlighted in yellow.

One error, marked by the blue arrow, existed in my import and appears to have been corrected in the GWR data (imported data is from 2024-10-29), as the updated position is now represented by the green dot.

You seem to be referring to correctness of absolute positioning of the entrances when talking about correctness. That’s somewhat problematic. OSM is a project that was founded on the idea of manual mapping. That comes by its nature with some imprecision in the positioning. That’s perfectly fine as long as the data is topologically correct, i.e. as long as the different features are placed correctly in relation to each other. When mixing another dataset into OSM, it is important to ensure that relative positioning remains intact.

We also usually operate under the principle that local knowledge trumps imported data. That means that when you find a discrepancy between your import data and what was mapped manually, it is your responsibility to cross-check that the error is in the manually surveyed data before overwriting the data.

The wiki page seems to be inconsistent. It may say "The house number should be added at another node in the building or at the building itself. " but it also says "Useful combinations: addr:*`. With 30% of entrances having an address, it is fairly safe to ignore the first sentence.

3 Likes

I’ve fixed the wiki entry. As you say obvious nonsense.

In the location you referenced, the manual mapping of addresses to entrance=yes nodes by @datendelphin contains three (or possibly four, if you include the recessed entrance) errors in entrance positions, highlighted in yellow.

Yes, at Moosstrasse 2 I seem to have totally failed. I just went there and had a look again. I actually mapped the auxiliary entrance, because the house number is attached there. The main entrance is not well visible from the street, but of course there is a broad path to it which I should have recognized. I wish this embarrassment wasn’t so public.
More seriously, the nice thing to do in such a case would have been to ask me to check again. The state now is in my opinion totally unhelpful. The address node is in the right vicinity, but the entrance is in the wrong place. An ideal implementation would take entrance nodes into account and point the user to the wrong side of the building. And in actual life nobody would notice any of it because no one looks at the navigation to find the entrance in that particular case.

With my deep shame out of the way, I find it hard to continue this discussion. You repeat your arguments in a fundamental fashion, oblivious to any other perspective. The arguments you ask for have been mentioned here and also verbally. There is no more merit in weighing pros and cons when all arguments get swept away by you by some arbitrary precision and clearness standard.

Just pointing out one dissonance in your argumentation, almost the same that Sarah already did. You made this comparison before and after. The right most pane of that struck me as “blatant fabrication” because I vividly remember doing the addresses of the residential buildings there for an introduction to OSM presentation. So let me share a different view of that, from achavi:

image achavi - Augmented OSM Change Viewer  [attic]
Even though in your comparison it looks like there were no addresses, this seems more like a bug in that particular renderer. Because there were addresses. And have a look at the four buildings with green outlines in a row from middle top to bottom right. They had entrances at the side. Which is actually correct. Here the data from GWR is missing that detail. How would you know without being there? No idea. Each discrepancy can go in both directions. But by overwriting the existing data, we are deprived of one independent data set.

Clarification on Address Conversion and Data Deletion

The most valuable asset OSM has is its mappers that actually go to a place, because that generates truly unique (or independent) data. And the only thing we volunteers get in return is a good feeling. As I experienced myself, moving the data from an outline to a node, or moving it from a node and entering it with a new node, disconnects my work, the “history” from the current state on the map. This is psychological, but very powerful. At the risk of being selfish, we need to take care of those community members, and I weigh that a lot higher than an arbitrary precision argument. Grudgingly embracing Simons observation:

We have whole countries in OSM that use “address node in building outline” throughout and it hasn’t led to the downfall of western civilisation.

That also means such imprecisions that you pointed out are of no consequence either.
So my view for a compromise is: We can import free floating missing addresses. But do not touch already mapped ones. No matter what low opinion you have of basic mappers. We don’t even need to agree if that is irrational or well founded, the damage to the community is just too great.

And as a final remark: hard balling with arguments is quite taxing. This reply cost me 3 hours, and it is still too flippant, too emotional, too attacking unfortunately

1 Like

I sincerely apologize for the inconvenience. I will revert the changesets for Cham and the other municipalities you were involved in mapping.

If anyone else requests a revert for a municipality, I will take care of it.

I reverted the changes in Cham, Hünenberg, Risch-Rotkreuz, and Steinhausen, while Piz_Pachific handled Grüningen.


I’ve updated the Wiki with the following changes:

  • Preserve/do not delete address data on nodes tagged with entrance=*.
  • Make the removal of address data on ways or nodes along building edges optional.
  • I’ve incorporated some points from the discussion, including potential drawbacks, into this optional step on the wiki.

The guide recommends “selecting the full dataset O.”
It would be a lot safer and easier to select the “Missing” dataset. The full dataset will be useful to look at to resolve some problems, like a Building with multiple addresses but only one mapped.