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Thursday, 12. November 2026

OpenStreetMap User's Diaries

Dakota/Lakota Writing Systems and Orthography

The Dakota/Lakota language has been a written language for only the most recent chapters of its history. Writing systems for the language were first devised by 19th-century missionaries who sought to promote literacy as a part of encouraging Dakota people to convert to Christianity. These missionaries, especially Stephen Riggs, developed an alphabet based on the Latin Alphabet to represent the s

The Dakota/Lakota language has been a written language for only the most recent chapters of its history. Writing systems for the language were first devised by 19th-century missionaries who sought to promote literacy as a part of encouraging Dakota people to convert to Christianity. These missionaries, especially Stephen Riggs, developed an alphabet based on the Latin Alphabet to represent the sounds present in the language. All widely used methods for writing the language today are based on Riggs’ system with some degree of variation.

There is no single writing system accepted by the vast majority of speaker communities. A variety of systems - or orthographies - exist with varying degrees of popularity, and invididual speakers and teachers often have strong preferences one way or another. Areas of debate include:

  • May an orthography make use of special characters (ŋ, ǧ, ḳ, ú) or should writing be done only with characters that can be written with a standard English keyboard?
  • The language contains vowels (a, i, u) that may be nasalized or not, depending on context; should the orthography note the difference?
  • The language contains consonants (z, c, p, t, k, s) that may be aspirated for a harder sound or unaspirated; should the orthography note the difference?
  • The language contains consonants (g, h) that may be guttural or not; should the orthography note when this happens?
  • Some words are distinguished from other words only by which syllable is emphasized when the word is spoken e.g. “máġa” is a field while “maġá” is a goose. Should the orthography note which syllable is emphasized or not?

Whatever orthography is best for the learning journey of any given speaker, I believe that for a reference resource like OpenStreetMap it is best to use a writing system that fully explains how to correctly pronounce the words that make up place names. Speakers and learners who learn names from this resource can always choose to copy or remember information without pronunciation marks that they think are unnecessary. However, it is much harder to infer more information when given less; the starting position ought to be the maximum amount of information that we can give.

For this reason, I write Dakota (:dak) place names in the UMN Orthography developed by Carrie Schommer et al. at the University of Minnesota. This orthography is used by Dakota communities in Minnesota and language programs in Sisseton Wahpeton and Wípazoka Wakpa. This orthography fully communicates all possible pronunciation details that exist in the Dakota dialect. As is typical for this orthography, I note syllable emphasis only in the minority of situations when it is not on the second syllable. The way OSM displays means sometimes I have to use ṗ for aspirated-p consonants instead of the more commonly used p̣.

I write Lakota (:lkt) place names in the Standard Lakota Orthography used by the New Lakota Dictionary, Lakota Grammar Handbook, and related resources. This orthography fully communicates all possible pronunciation details that exist in the Lakota dialect. As is typical for this orthography, I note syllable emphasis on every multi-syllable word.

I am aware that there are speakers, teachers and communities that have preferences for orthographies other than these and come down on other sides of the questions above. The method that helps you learn is never the wrong choice, and once you’ve really internalized any one writing system you’re 95% of the way to understanding any of the others. It is my hope that the information I’ve recorded here will be helpful to you, even if you choose to represent it some other way in your own writing.


Basic Overview of the Dakota/Lakota Language

Dakota (instead called Lakota by speakers of that dialect) is the indigenous language of the Oc̣eṭi Ṡakowiƞ (Seven Council Fires) people of North America, consisting of the Bdewaḳaƞṭuƞwaƞ, Waḣpeḳute, Waḣpeṭuƞwaƞ, Sisiṭuƞwaƞ, Ihaƞkṭuƞwaƞ, Ihaƞkṭuƞwaƞna and Ṭiṭuƞwaƞ communities. Most members of these communities will describe themselves as Dakota (or Lakota for the Ṭiṭuƞwaƞ) people.

Dakota (instead called Lakota by speakers of that dialect) is the indigenous language of the Oc̣eṭi Ṡakowiƞ (Seven Council Fires) people of North America, consisting of the Bdewaḳaƞṭuƞwaƞ, Waḣpeḳute, Waḣpeṭuƞwaƞ, Sisiṭuƞwaƞ, Ihaƞkṭuƞwaƞ, Ihaƞkṭuƞwaƞna and Ṭiṭuƞwaƞ communities. Most members of these communities will describe themselves as Dakota (or Lakota for the Ṭiṭuƞwaƞ) people.

Dakota and Lakota communities can be found in Minnesota, North Dakota, South Dakota, Nebraska, Montana, Manitoba and Saskatchewan. All of these places have a rich geography of names devised by Oc̣eṭi Ṡakowiƞ people in the Dakota/Lakota language, including rivers, lakes, towns, islands, hills and more. People have traveled since the dawn of human history and some areas once had Dakota/Lakota communities that presently do not, and so other areas (such as Wisconsin, Iowa, Wyoming and Ontario) also have locations with names in the language.

Historically, there have been far, far more Dakota and Lakota place names than those that survive for us to learn about them in the present. Colonization has inflicted enormous trauma and language loss on these and other Native communities through allegedly-voluntary but actually forced exile from their lands, wars of conquest, traumatic boarding school assimilation, and more. However, many people who are members of (or in close contact with) these communities have put in heroic efforts in defense of the language. These language protectors have striven to continue learning, speaking and teaching the language, and to record many aspects of the language for future generations - including place names.

The language is cherished by the communities to which it belongs, though in the present only a minority of community members speak it with any degree of fluency. It is a richly detailed language in which large amounts of information are elegantly conveyed by verbs, especially verbs of motion and place. The language is related to (though not fully mutually intelligible with) a range of other languages of North America.

Oc̣eṭi Ṡakowiƞ culture is marked by great devotion and reverence toward the land and all that lives on it, and there have been many small- or large-scale efforts by people in or adjacent to these communities to record and publish place names in the language. However, many of these efforts have been expressed as books that are now out of print, articles behind academic paywalls, papers in archives, or websites with fragile hosting. Many such projects also only describe a small geographic area.

Modern data platforms like OpenStreetMap represent a great opportunity to store, share and present this knowledge. My goal on OSM is to pull together as many genuine Dakota/Lakota place names as I can find from the sources that exist and represent them on the map. I aim to do so in a way that accurately communicates how they are pronounced for the benefit of other learners and speakers, and that can be an aid to understanding their meaning.


Dakota/Lakota Dialects

My mapping on OpenStreetMap includes names in both Dakota and Lakota, with ISO codes dak and lkt respectively. This is an unusual approach compared to a lot of other multilingual mapping, so it’s worth explaining in more detail.

Dakota and Lakota are two different dialects of the same language (and are two possible names for that language). They are mutually intelligible, and a fluent sp

My mapping on OpenStreetMap includes names in both Dakota and Lakota, with ISO codes dak and lkt respectively. This is an unusual approach compared to a lot of other multilingual mapping, so it’s worth explaining in more detail.

Dakota and Lakota are two different dialects of the same language (and are two possible names for that language). They are mutually intelligible, and a fluent speaker of one can understand a fluent speaker of the other without difficulty. An analogy might be made to the Spanish spoken in Mexico vs the Spanish spoken in Spain - a speaker of the other dialect will seem to have a strong accent, unusual pronunciation, and some different word choices, but they are still clearly speaking your language. Both dialects are endangered, but there are substantially more Lakota speakers than Dakota speakers and this has been true for a long time.

Dakota and Lakota share the vast majority of their vocabulary. Most words that differ between these dialects differ in predictable, formulaic ways that do not represent any difference in meaning (e.g. Oṭuƞwe vs Otȟúŋwahe or Bde vs Ble). The most meaningful differences in Lakota vs Dakota speech emerge in conversational flow, which rarely matters for place names. Additionally, names of places in Dakota/Lakota are rarely Proper Nouns as English speakers understand them (words that are only used as names e.g. London, Florida, Catherine, Jesse). Rather, place names in the language - like the names of people in the language - are constructed from normal words.

Thus, while my sources all speak one or the other of Dakota or Lakota, when I add a place name in one dialect from a source I try to also add it in the other dialect - as long as the place name consists entirely of words that are “identical” between the dialects. These words may differ subtly in pronunciation, but are identical in meaning. This matches the approach to dialect differences that I’ve generally heard from speakers in practice - people stay in their dialect when describing the names of places, even if the place is populated by speakers of the other dialect.

There are situations where I will refrain from doing this mirroring between dialects:

  • When I have sources in both dialects and they say different things, I will enter truly different values for the two dialects. For example, see South Dakota’s Paha Waḳaƞ/Pȟežúta Pahá (Medicine Butte).
  • When I have a credible source for a name but it really is presented as a Proper Noun (rare) or at least I don’t feel that I understand what it means well enough to find counterpart words in the other dialect. For example, see the city of Ablíla (Aberdeen) in South Dakota - I have only a Lakota source, can’t break down the structure of the word further, and can’t find a Dakota source for the name of the city.
  • When I understand the name well enough, but the name is composed of words that truly don’t have parallels in the other dialect e.g. Isaƞ vs Míla. For example, see southern Minnesota’s Ṡuƞkṭokca Wakpadaƞ (Wolf Creek); this creek has only a Dakota name because only Dakota speakers say “Ṡuƞkṭokca” (wolf) and the Lakota word for wolf is too different to credibly present it as a counterpart.

People familiar with discourse on the Dakota/Lakota language may ask here “isn’t there a third dialect that we should be discussing?” and indeed you’ll often hear the language described as the “Dakota, Lakota and Nakota dialects”. For completeness’ sake, it’s worth mentioning that the Dakota dialect is further subdivided into Eastern (Isaƞyaṭi or Santee-Sisseton) and Western (Wic̣iyena) variants. Wic̣iyena Dakota is sometimes called “Nakota”. Some (myself included) believe that the term Nakota originated in an error, but in the present many authentic speakers of the language use the term sincerely to describe this dialect. Speakers of Wic̣iyena Dakota do not, however, call themselves Nakota - they still refer to themselves as Dakota people. The people who actually refer to themselves as Nakota are the Assiniboine of Montana and Canada, who speak a language that is related to Dakota/Lakota but not mutually intelligible; their language is outside the scope of my mapping efforts.

Wic̣iyena Dakota has more in common with Santee-Sisseton Dakota than Lakota, but occupies a sort of “middle ground” in pronunciation between the other dialects in ways that would be difficult to explain without a deep dive into linguistics terminology. Like Dakota vs Lakota, the ways Santee-Sisseton and Wic̣iyena Dakota differ are mostly subtle, predictable and formulaic pronunciation differences.

All OSM name:dak values I have added are in Santee-Sisseton Dakota, though locations west of Minnesota will skew toward Sisiṭuƞwaƞ-Waḣpeṭuƞwaƞ use of the diminutive -na instead of Isanyaṭi use of the diminutive -daƞ. There are some reasons for this choice:

  • Unlike Dakota vs Lakota, Santee-Sisseton vs Wic̣iyena Dakota do not have different ISO language codes; the OSM format forces me to choose one when assigning a primary name:dak value.
  • 19th-century Minnesota policies of forced expulsion and (frankly) genocide pushed Santee-Sisseton Dakota-speaking populations westward into traditionally Wic̣iyena-speaking areas. Very little migration has gone the other direction, so there are far fewer places where Wic̣iyena Dakota is the only dialect around.
  • There are much, much more abundant language resources for Santee-Sisseton Dakota than Wic̣iyena Dakota, ranging from historic missionary language texts to 21st-century Dakota-led language revitalization programs. This means I can check the meaning and origin of names in one in a way that I cannot for the other.
  • Santee-Sisseton Dakota is the dialect that I was taught in and thus the dialect that is most intuitive to me.

Whatever the dialect variations, the language I am mapping in is all one language. If the language is part of your heritage (or if it isn’t but you live in this part of the world), I’d encourage you to explore learning it in whatever dialect is spoken in or near your community.


A map of open OSM notes, sorted by what they need

There are about 450,000 open notes on OpenStreetMap. Each one is a message from someone who saw a problem on the map. But to know what a note needs, you have to open it and read it, one by one. That takes a lot of time.

So I trained a machine learning model to do this first read for us. I also made a simple website to show the results:

→ osm-notes.rub21.com

What does the mod

There are about 450,000 open notes on OpenStreetMap. Each one is a message from someone who saw a problem on the map. But to know what a note needs, you have to open it and read it, one by one. That takes a lot of time.

So I trained a machine learning model to do this first read for us. I also made a simple website to show the results:

→ https://osm-notes.rub21.com

What does the model do?

The model reads the first comment of each note and gives it two labels:

  • Category: what the mapper should do. For example: missing place, place closed or changed, wrong name, missing or wrong road, other wrong data, spam, empty, or not mappable (opinions, questions).
  • Theme: what the note is about. For example: food, shops, health, roads, transport.

How I built it

  1. The notes. Andrés (AngocA) built OSM-Notes-Ingestion. It loads all OSM notes into a database and keeps them up to date every minute. On top of it, I built a small pipeline that:
    • loads the full notes dump from the planet file,
    • takes the first comment of each note (the one that explains the problem),
    • detects the language of each note.
  2. Training data. This was the hardest part, and it took several rounds. The AI helped me a lot, but I reviewed many of its labels:
    • I sent about 10,000 notes to three popular AI models: Claude, GPT and Gemini. When all three agreed, I kept the label, and I also reviewed many of them.
    • When they did not agree, I read the note and chose the label myself. I labeled about 1,300 notes this way.
    • After the first training, I looked at the notes where the model failed. In many of them the label was wrong, not the model. So I fixed many labels and trained again, until the results were good enough.

    In the end, I had about 11,700 labeled notes in Spanish and English. I did not train with other languages. The model is multilingual, so I hope it can also work in other languages, but I have not measured it yet.

  3. The model. I fine-tuned XLM-RoBERTa large, a multilingual model, with these notes. Category macro-F1 is 0.78 and theme macro-F1 is 0.83.

The model is not perfect. It still makes mistakes, mostly with “other wrong data” and “not mappable”.

For ML people: model and results

  • Input: the model reads the full text of the first comment. I only remove things that do not help, like URLs, dates, hashtags and app versions. About 31% of the notes come from apps (StreetComplete, Organic Maps, MAPS.ME…). The rest come from the OSM website.
  • Models: I trained one model for category and one for theme. I compared three options: a simple TF-IDF + logistic regression baseline, mDeBERTa-v3 base, and XLM-RoBERTa large (XLM-R).
  • Split: 72% for training, 8% for validation (to pick the best checkpoint and stop early), and 20% for testing, stratified by class. I only used the test notes at the end. The main score is macro-F1, so rare classes like spam count as much as common ones.

Labeled notes per class (click a class to see it on the map):

Category Meaning Labeled notes
missing_place A place exists but is not on the map 3,706
wrong_road A road or path is missing or wrong 1,933
other_data Other wrong data: hours, address, type… 1,843
place_changed A place closed, moved or changed 1,367
wrong_name Wrong or missing name 994
not_mappable Opinions, questions, things not for OSM 785
spam Ads or unrelated links 200
empty Says nothing: “test”, “ok” 192
personal_data Personal data (moderators only) 148
Theme Labeled notes Theme Labeled notes
roads 3,712 shop 952
none 1,379 food 579
services 1,285 nature 524
leisure 1,279 transport 329
buildings 1,224 education 301
    health 194

The classes are not balanced. missing_place has 3,706 notes, but personal_data has only 148. I also labeled 590 notes as unsure, and I did not use them for category.

F1 by class for the three models

XLM-R large gave the best results: category macro-F1 0.78 and theme macro-F1 0.83. For category, it works a bit better in English (0.80) than in Spanish (0.74).

Category confusion matrix

The confidence score helps. If we keep only predictions with 90% confidence or more, category accuracy goes up from 82% to 90%, and we still keep 81% of the notes.

One thing to keep in mind: most test labels come from AI models. So these scores show how well the model agrees with the AI labels, not with people.

A website to see the results and close notes

  • Running the model without a GPU

I did not want to pay for a GPU server. So after training, I exported both models to ONNX with 8-bit weights. Now they are 4 times smaller and run on a normal CPU. They give the same answer as the GPU model for 96% of the test notes.

  • The website

The website is simple and looks a bit like OSMCha. You can list notes by category, theme and confidence, and filter by language and app. I hope this makes it easier to find notes you can fix and close. You can also export the notes as GeoJSON for MapRoulette.

You can log in with your OSM account. Then you can tell the model if a prediction is right or wrong (👍 or 👎), and help label notes.

Some notes have personal data, like “this is my house” or a phone number. I did not want to show them on a public map. So the public map only shows how many there are, and only OSM moderators can see them after they log in.

Next step

  • Use closed notes. The closing comment often says what the mapper did, like “added the shop” or “spam”. This gives a label confirmed by a real person. The model will still read only the first comment, but these labels can help me train and test it in more languages.

  • Use the work of Mateusz Konieczny - bot. He used an LLM to find notes that can be closed (spam, junk, personal data, duplicates) and closed many of them. These notes were checked by a person, so they are good training data, especially for rare classes like spam and personal_data.

Feedback welcome

I hope this helps people solve notes faster. I would love to hear from you:

  • Are these categories useful? Would you change any?
  • Does the map help in your area?
  • You can also help: log in and press 👍 or 👎 on a note, or label notes at https://osm-notes.rub21.com/label.

Note: this runs on my own small server, so the website may be slow sometimes.


Wandering Around 1.0: what's new in the OSM-powered browser game

A few weeks ago I wrote here about Wandering Around, a free browser game in which you can walk through any town or city on Earth, built on the fly from OpenStreetMap. Thanks to your comments and feedback, the game has now left beta: version 1.0 is live.

Play it here: wanderingaround.games (phone and desktop, no download, no account needed)

This post is about what changed on the O

A few weeks ago I wrote here about Wandering Around, a free browser game in which you can walk through any town or city on Earth, built on the fly from OpenStreetMap. Thanks to your comments and feedback, the game has now left beta: version 1.0 is live.

Play it here: https://wanderingaround.games (phone and desktop, no download, no account needed)

This post is about what changed on the OSM side since then.

Buildings that look like the real thing

  • Churches are built from their real outline. The game reads the shape of the building and finds the nave, the transepts and the choir, and each part gets its own roof that follows the shape. A square part that sticks out becomes the tower. A church mapped carefully as a cross shape now also looks like one at eye level.
  • Mosques get a dome on a drum, pointed windows and a minaret. They are recognised by religion=muslim, building=mosque or the name.
  • Cemeteries (landuse=cemetery) are laid out with gravel paths, rows of graves in neutral shapes, low hedges and trees.
  • Sidewalks now run along the whole street as one continuous strip. Short gaps are filled and corners join neatly.
  • Shop fronts, front doors and porches get their own place in the facade, so windows don’t end up behind a door.

Walking along OSM streets

When you tap somewhere on the map, your avatar now finds the way over the OSM road and path network: tiles stitched together, loose ends of footpaths connected, no private roads and no tunnels. Before, it walked in a straight line and got stuck against the first wall. If the straight line is free it still walks straight, so it doesn’t make strange detours across an open square.

Trains and ferries, everywhere

Asking Overpass for train routes from the browser became slow and unreliable in busy areas. So railway routes (route=train relations with their stops) are now extracted from the Geofabrik continent files with osmium and stored in tiles of 2 × 2 degrees. Opening a station takes one short request, anywhere in the world. Ferry routes come from Overture Maps in the same tiled way.

Wikipedia in the local language

Thanks to Frederik’s comment on my previous post: a monument now shows the Wikipedia article in the language of the place first (in Aarhus that is Danish), and falls back to the language of your device. The wikidata tag on the object is what makes this possible.

Museums and their shops

Every museum with a Wikidata link gets a little museum shop at the street, where you can buy prints of paintings from that museum’s own collection (from Wikidata, public domain works only) and souvenirs. A museum is recognised by tourism=museum, or, when that tag is missing, by Wikidata “instance of” (museum, art museum, gallery …). So adding wikidata to a museum building is directly visible in the game.

And more

Does your area look right? A church with an odd roof, a cemetery that isn’t recognised, or a station without trains usually means a tagging pattern I don’t handle yet. Please tell me in the comments, or use the feedback button in the game.

Thanks again to everyone who maps. Every building you trace ends up in someone’s walk.

Map data © OpenStreetMap contributors · tiles by OpenFreeMap · Wikidata · Wikipedia · Wikimedia Commons · Overture Maps

Wednesday, 11. November 2026

OpenStreetMap User's Diaries

Highway Classificaiton within the Greater Cairo Metropolitan Area

According to sources (such as this a general rule of thumb for roads within urban areas is 40 for busy traffic roads and 60 for main roads. I believe that the highway=’primary’ tag should generally align for these roads (usually long stretching across a district, 2-3 lanes) such as Ramsis St. For the less important roads they should be secondary of tertiary depending on importance, where tertiar

According to sources (such as this a general rule of thumb for roads within urban areas is 40 for busy traffic roads and 60 for main roads. I believe that the highway=’primary’ tag should generally align for these roads (usually long stretching across a district, 2-3 lanes) such as Ramsis St. For the less important roads they should be secondary of tertiary depending on importance, where tertiary is more likely to intersect more with busier residential areas and roads. This can help routing algorithms better impute speeds depending on the highway, helping in this region as road speeds are rarely defined for non-trunk roads.


OpenCage

Interview: Frank März on OpenFireMap

Frank talks about the history and evolution of OpenFireMap.

Today in our OpenStreetMap (OSM) interview series, we are speaking with Frank März about the story behind OpenFireMap. What started as an effort to replace an outdated, hand-drawn village map has grown into a free map showing fire stations, hydrants, water supply points and defibrillators across dozens of European countries. We spoke with Frank about the project, how AI helped him rebuild it, and his hopes for the future of community mapping.

1. Tell us a bit about who you are and how you first got involved with OpenStreetMap?

I’m Frank März (52) from a small village in Franconia, Germany. I work in network operations for a German mobile operator. I found OpenStreetMap around 2010 as a passionate marathon runner: I started by mapping all the routes and paths around where I live, later the buildings and everything else that was missing. Then I realized that our volunteer fire brigade, in a village of about 1,000 people, still had an ancient hand-drawn map hanging in the fire station. I wondered whether OpenStreetMap could be the basis for a new village and hydrant plan. That question took me from running routes to fire-service mapping.

OpenFireMap

2. What is OpenFireMap, how did the idea for the project come about, and what motivated you to create a dedicated map for fire services and emergency infrastructure?

OpenFireMap is a free web map that shows fire stations, hydrants, water supply points and defibrillators from OpenStreetMap. It started with that village plan question. I brought it up at the OSM meetup in Nuremberg and got a few people on board. I can barely program, so I didn’t build it, but I gave the impulse, proposed the design and later organized the domain. The first OpenFireMap then ran largely unchanged for about 12 years, operated by the admin of our meetup.

What changed was AI. I had moved to a different department at work and had to get to grips with GitHub, Docker and CI/CD, and OpenFireMap became my learning project for exactly that. In January 2026 I tried to set up a hydrant map purely with vibe coding, and it worked very well. After a few weeks I released a new version, on my own together with AI, and moved my domain over to it. I haven’t looked at a single line of code since. I use the 20-euro plans of Claude and OpenAI, and I’m amazed at what has become possible within a year.

3. What kind of information does OpenFireMap display, and where does the data come from? How does it build on the wider OpenStreetMap database?

OpenFireMap has no database of its own. It’s purely a visualization of OpenStreetMap data, and I’ve always liked that: if someone wants to add or correct something, they do it in OSM and it shows up on the map. For the fire service, the relevant objects are hydrants, suction points, fire ponds and water tanks, plus fire stations as a small extra. Recently I’ve added AEDs. I’m registered with the first-responder app “Region der Lebensretter”, so that topic matters to me, and I’m tinkering with a small side project: photograph an AED, and it’s either added to OSM or, if it’s already there, confirmed as still present.

To keep the map fast, I first set up pre-built vector tiles for Germany, Austria, Switzerland, Luxembourg and Liechtenstein. In a second step I extended that to 40 more European countries. Everywhere else, and for recent changes, the map asks Overpass live.

Overlay Display

4. Who uses OpenFireMap, and how can it help in practical situations? Have you come across any particularly interesting examples of how people use the map?

People use it in three ways. At a desk, you choose a place and export a PDF or PNG, for example a village plan; GPX and CSV came later. Our own fire station now has a village plan made this way on the wall. I’m currently working on a special export for printing that draws streets wider than they really are, so a printed map is easier to read. On the phone, you locate yourself and see the nearest hydrants. And some fire-service software, such as the Alarminator app, uses the data.

Feedback has led to real changes. The plant fire brigade of a car manufacturer in Baden-Württemberg had Württemberg shaft hydrants, and there was no symbol for them. I added one, and now the map has it.

There’s also a statistics page. Some regions are very thin; in my valley, with my two neighboring municipalities, I’d say we’ve mapped 99% of all hydrants, even along new roads that aren’t open yet. It’s not an official dispatch map, and the data should be checked locally before operational use.

5. What are the biggest challenges in maintaining OpenFireMap and keeping its data useful and up to date? How can the OpenStreetMap community contribute to the project?

Reliability. The map used to depend entirely on the Overpass API, and as that became less dependable, the map was useless whenever it was down. After a summer break, when I’d rather be outside, I picked it up again at the end of September and set out to fix that: pre-computed data served from Cloudflare, so the map appears within one or two seconds. Overpass is now only a backup. The data for Germany, Austria, Switzerland, Liechtenstein and Luxembourg is updated daily, the other countries weekly. Building it scared me at first, but it could all be vibe-coded.

Where I’d like help: Android. AI can only judge to a limited extent how things look on phones, and Android doesn’t look like the iPhone. If you use Android and are a bit of a design genius, feedback would be great.

For mapping, I’d like local fire brigades and their youth groups to turn it into an exercise: split the village into quadrants, walk them with phones, and a complete map exists two days later. hydrantenjaeger.de makes that fast: photograph a hydrant, add a few details, upload, and it’s in OSM about 20 seconds later. I’d love to see people use it. A short tutorial video that explains it quickly is on my to-do list, but I haven’t found the time yet. I’m not a big fan of long texts myself, so it will be a video rather than a manual.

Fire Hydrant icon

6. OpenStreetMap has come a long way since it began. Looking ahead, what do you hope the project will achieve over the next 10 years, and what role do you see OpenFireMap playing in that future?

OSM is a huge project. I love it when people look closely at their surroundings so that the map is really good where they live, and then all sorts of apps use it, even my own employer. It’s a great feeling to see a map and know that about 80% of what’s around me I mapped myself 10 or 12 years ago, and it’s still there.

My wish for the next ten years: that very many fire brigades map their own village and surroundings, so that all hydrants end up in the OpenStreetMap database. That would be really cool.

Where OpenFireMap will be in ten years isn’t that relevant. All of Europe is in already, and the whole world would be possible; the question is just where the server space is. It’s a purely private project, and I don’t want to make money from it. I want to give something back. If someone wants their country, I can set it up within a day. What would help me most is feedback from fire brigades and other users: what’s missing? With AI agents, building it takes one or two evenings, not weeks.

Everything is on GitHub, under the MIT license, so anyone can contribute, or copy it and build something of their own. And I’m a friend of simplicity. Many maps I see based on OSM are completely overloaded, and keeping it simple is my small contribution.


OpenFireMap is a great example of how OpenStreetMap data can be put to practical use, supporting local communities and emergency services. Frank hopes more fire brigades will get involved in mapping their surroundings, helping make essential emergency infrastructure visible and accessible to everyone. Thank you, Frank, for sharing your story and for your contributions to the OpenStreetMap community.

Happy mapping

Danielle

Please let us know if your community would like to be part of our interview series here on our blog. If you are or know of someone we should interview, please get in touch, we’re always looking to promote people doing interesting things with open geo data.


OpenStreetMap User's Diaries

My phone's 'Organic Maps equipped'

So maybe I’ll map in the big capital city today…

So maybe I’ll map in the big capital city today…


Geospatial Action Against Dengue: Empowering Communities Through Open Mapping and Waste Hotspot Identification in Eravur Pattu, Sri Lanka

Turning Geospatial Knowledge into Community Action

Maps are more than representations of places. They help us understand our surroundings, identify challenges and make informed decisions that can improve people’s lives. With this belief, I had the opportunity to organise and facilitate the Open Mapping Guru Workshop and Field Mapping Programme 2026, held on 5th–6th October 2026 at the Faculty o

Turning Geospatial Knowledge into Community Action

Maps are more than representations of places. They help us understand our surroundings, identify challenges and make informed decisions that can improve people’s lives. With this belief, I had the opportunity to organise and facilitate the Open Mapping Guru Workshop and Field Mapping Programme 2026, held on 5th–6th October 2026 at the Faculty of Arts and Culture, Eastern University of Sri Lanka. Under the theme “Geospatial Action Against Dengue: Mapping Waste Hotspots and Stagnant Water in Eravur Pattu,” this initiative brought together university students, academic staff and the Open Mapping community to explore how geospatial technologies can contribute to environmental monitoring and public health awareness. Supported and sponsored by Open Mapping Hub - Asia-Pacific and the Humanitarian OpenStreetMap Team (HOT), the programme was designed to go beyond traditional classroom learning. It provided students with an opportunity to learn, explore, collect real-world geographical information and understand how their mapping contributions could support their surrounding communities. As the Resource Person and Organiser, my main objective was to connect geospatial knowledge with practical community needs and encourage students to become active contributors to the global Open Mapping community.

Day 01: Taking Open Mapping Beyond the Classroom.

The first day focused on practical field mapping and community-based data collection, with about 21 university students participating. The programme commenced at the Department of Geography, where students were divided into five groups and assigned different mapping areas surrounding the university and nearby communities. Before heading into the field, I introduced the participants to several mobile mapping applications and explained how these tools could be used to collect accurate, location-based information. The applications included ChatMap for capturing geotagged photographs and location-based field information, EveryDoor for contributing to OpenStreetMap through field-based data collection, and Organic Maps for navigation and exploring geographical locations, Mapillary for collecting and exploring street-level imagery, and Field Papers for preparing field maps and supporting systematic data collection. Following the technical introduction, the student groups began their field activities, focusing on identifying and documenting waste accumulation sites that could create potential mosquito breeding environments. Although the original theme included identifying both waste hotspots and stagnant water locations, the severe drought conditions experienced in Batticaloa District during this period limited the availability of stagnant water observations. Therefore, the students concentrated mainly on identifying waste accumulation locations and their surrounding environmental conditions. Field Mapping & Data Collection Near Eastern University ,Sri Lanka One of the most valuable tools during this activity was ChatMap. It enabled students to capture actual field photographs together with geographical coordinates, allowing us to build a location-based dataset supported by visual evidence. Throughout the fieldwork, I coordinated the groups, monitored their progress and provided technical guidance through a dedicated WhatsApp group. Students returned to the university in the afternoon, where we discussed their field experiences, observations, challenges and feedback. This activity provided valuable practical exposure and demonstrated how local observations can be transformed into useful geospatial information.For me, this was an important learning experience because students were not simply learning how to use mapping applications; they were observing real environmental issues and understanding how geographical information could help document them.

Day 02: Empowering Students Through Open Mapping and Open Source GIS

The second day focused on technical knowledge sharing, practical demonstrations and introducing participants to the wider world of Open Mapping and Open Source GIS. Approximately 51 participants attended the workshop, including students who had participated in the previous day’s field mapping, undergraduates from the second, third and fourth academic years, and academic staff members. OpenMapping training to YouthMappers Chapter ,EUSL We were honoured by the presence and participation of Prof. Suresh, Dean of the Faculty of Arts; Mr. Kiruparaja, Head of the Department of Geography; and Dr. Suthakaran, Senior Lecturer, Department of Geography. Their participation and encouragement highlighted the importance of introducing emerging geospatial technologies into university education and creating opportunities for students to engage in practical, technology-driven initiatives. As the Resource Person, I conducted and facilitated technical sessions covering several important areas of Open Mapping and Open Source GIS. These included an introduction to Open Source GIS and Open Mapping, exploring OpenStreetMap and the iD Editor, installation and configuration of JOSM, practical applications of ChatMap, an introduction to uMap for creating interactive maps, exploring the HOT Tasking Manager and HOT Export Tool, and mapping using Mapillary street-level imagery. The sessions combined technical explanations with practical demonstrations to help participants understand how open geospatial tools can be used for geographical data collection, collaborative mapping, spatial visualisation and humanitarian activities. It was particularly encouraging to see students engaging with the tools, exploring their capabilities and recognising that mapping is not limited to professional GIS specialists. The programme concluded successfully with the distribution of participation certificates, celebrating the students’ involvement and their willingness to learn and contribute to the Open Mapping community.

150+ Waste Hotspots: Turning Field Observations into Geospatial Evidence

view the map: One of the most significant achievements of this initiative was the identification of 150 + waste hotspots through student-led field mapping activities. The identified locations covered areas around Eastern University and nearby communities, including Kommanthurai, Vantharumoolai and Changalady. The collected information included geographical coordinates and supporting field photographs, providing visual and spatial evidence of waste accumulation locations. These observations offer an important foundation for understanding the spatial distribution of waste accumulation sites in the surrounding communities. The mapping output demonstrates how university students can contribute to documenting real environmental challenges using accessible mobile applications and open geospatial technologies. Each mapped location represents an environmental observation that can contribute to a better understanding of local waste management challenges. Although identifying waste hotspots alone does not establish the presence of mosquito breeding sites or confirm dengue transmission risks, the collected information can help relevant authorities identify locations that may require environmental inspection, waste removal and further monitoring. This is where I believe Open Mapping creates meaningful value: it transforms local observations into organised geographical information that can support informed action.

Connecting University Mapping Activities with Local Community Needs

For me, the purpose of this programme was never limited to conducting a two-day workshop or teaching students how to use GIS applications. The broader objective was to establish a connection between university-based geospatial knowledge and real community needs. The identified waste hotspot dataset is intended to serve as a useful resource for environmental monitoring and local-level planning. As the next step, we aim to further organise, validate and prepare the collected geographical information for sharing with the Medical Officer of Health (MOH) and Eravur Pattu Municipal Council through the YouthMappers Chapter Executive Committee. This proposed collaboration will provide an opportunity to connect university students, the Open Mapping community and relevant local authorities. By making the collected information accessible to the relevant stakeholders, we hope to encourage further environmental inspections, appropriate waste management interventions and community awareness activities.It is also an opportunity to demonstrate that students can contribute to practical solutions beyond their academic assignments and examinations. I believe this connection between university knowledge and community needs is essential for creating meaningful and sustainable impact.

A Personal Reflection: Giving Back to My University Through Open Mapping

Organising and facilitating this programme was a particularly meaningful experience for me. Returning to Eastern University of Sri Lanka, where I completed my undergraduate studies, and having the opportunity to share my knowledge and experience with the academic community was something I truly valued. My journey in Geospatial Technologies and Open Mapping has strengthened my belief that geographical information should not remain limited to technical professionals or academic researchers. With the right guidance, students and community members can become active contributors to creating meaningful geographical data. Throughout this programme, I had the opportunity to introduce students to tools and technologies that can open new learning opportunities, develop their technical skills and connect them with the global Open Mapping community. As a Resource Person and Organiser, one of my greatest satisfactions was seeing students move from learning about mapping applications to actually using them to identify and document environmental challenges in their own surroundings.I strongly believe that universities have an important role in encouraging students to use their academic knowledge to address real-world problems. Initiatives like this can create that connection between education, technology and social responsibility.I hope this programme will encourage more students to explore Open Mapping, participate in humanitarian mapping initiatives and use their geospatial knowledge to contribute to sustainable community development.

Acknowledgement and Appreciation

A successful initiative is always the result of collective effort, encouragement and collaboration. I sincerely extend my gratitude to Open Mapping Hub - Asia-Pacific and the Humanitarian OpenStreetMap Team (HOT) for their generous sponsorship and support in making this programme possible through the Open Mapping Guru Pro+ Community Event Grant. Their continued commitment to strengthening the global Open Mapping community creates valuable opportunities for individuals, students and institutions to use open geospatial technologies for positive social impact. My heartfelt appreciation goes to Prof. Suresh, Dean of the Faculty of Arts, for his encouragement and support; Mr Kiruparaja, Head of the Department of Geography, for his cooperation; and Dr Suthakaran, Senior Lecturer, for his valuable guidance and support. I also extend my sincere thanks to the academic and technical staff of the Faculty of Arts and Culture and all the students who actively participated in the field mapping and technical workshop. I particularly appreciate the enthusiasm, teamwork and commitment demonstrated by the students throughout both days. The support and cooperation received from the Department of Geography and the Faculty of Arts and Culture, Eastern University of Sri Lanka, contributed significantly to the successful completion of this initiative.

Looking Ahead: Mapping for a Better and Healthier Community

The Open Mapping Guru Workshop and Field Mapping Programme 2026 was an important step towards encouraging students to become more than learners of geospatial technology. It demonstrated how young people can use their knowledge, creativity and technical skills to document environmental challenges and contribute to community-based initiatives.The identification of 150 + waste hotspots is an encouraging beginning. However, the real impact of this initiative will be reflected in how the collected information is further used, shared and translated into meaningful environmental action. I look forward to seeing more collaborations between universities, local authorities and the global Open Mapping community, creating opportunities for students to participate in initiatives that make a difference. For me, this programme reinforced one important message: Mapping is more than collecting geographical data. It is about understanding our surroundings, identifying challenges, sharing knowledge and empowering communities to create positive change. Let’s keep mapping, learning and contributing towards healthier and more sustainable communities.

Tuesday, 10. November 2026

OpenStreetMap User's Diaries

Did 3590 Contributions Today (and counting)

I have done 3590 Contributions on OSM today and am still working. I think getting detention was a godsent for my brain but a pain for my fingers. I am still working on more as I do not have any school work left to complete for today. I have done I believe at least 500 buildings today, completing 3 full neighborhoods in my county and starting another. Wish me luck, my fellow mappers. I’m in deten

I have done 3590 Contributions on OSM today and am still working. I think getting detention was a godsent for my brain but a pain for my fingers. I am still working on more as I do not have any school work left to complete for today. I have done I believe at least 500 buildings today, completing 3 full neighborhoods in my county and starting another. Wish me luck, my fellow mappers. I’m in detention until Thursday as well so I think I will be able to get a lot more done depending on how much work my teachers send me on Thursday.


Vending machines in France: what 7,800 OSM objects say about tagging

I maintain a map of vending machines built from OpenStreetMap data, part of a site that connects vending operators with venues (link at the end). It covers France, Belgium, Germany, Austria and Italy and is refreshed every month from Geofabrik extracts. While importing the 8 November 2026 extract, a few things about how vending machines are tagged stood out. I’m sharing them in case they are use

I maintain a map of vending machines built from OpenStreetMap data, part of a site that connects vending operators with venues (link at the end). It covers France, Belgium, Germany, Austria and Italy and is refreshed every month from Geofabrik extracts. While importing the 8 November 2026 extract, a few things about how vending machines are tagged stood out. I’m sharing them in case they are useful to mappers and data consumers.

The numbers. The French extracts (mainland and overseas) contain 37,259 objects tagged amenity=vending_machine. The map shows 7,779 of them: those whose vending=* value (or, failing that, name) is a product people seek out, such as food, drinks, bread, pizza, farm products, hygiene products and food lockers. Left out are, among others, machines with no identifiable product, cigarette machines and parcel lockers. The figures below refer to these 7,779 machines, compared with 17,924 selected the same way in Germany.

Product mix. The most common values are condoms (1,456), pizza (1,425) and bread (934). Germany, with more than twice as many machines on the map, has 132 pizza and 42 bread machines.

One machine, several products. In France, 1,530 machines (20%) list several products in a single semicolon-separated value, in no fixed order: drinks;sweets 418 times, sweets;drinks 30 times; drinks;food 257 times, food;drinks 60 times. That is valid tagging, but data consumers have to split the values before counting.

Opening hours are rare. Only 9% of French machines have opening_hours (11% in Germany). Many are accessible around the clock, and for those opening_hours=24/7 is a one-tag fix.

Payment. In France, 18% of machines have a payment:* tag, compared with 39% in Germany.

Freshness. In France, 22% of machines have check_date or survey:date (38% in Germany), and 31% were last edited before November 2023. Machines are sometimes removed without the data being updated. Adding check_date when you see one tells the next person that it was still there on that date.

Products hidden in the name. For 45 French machines, the product shown on the map came from name rather than vending=*. A vending=* value is far easier for software to use than free text in a name.

If you walk past a vending machine, four tags help most: vending=*, opening_hours, payment:* and check_date.

Corrections and comments are welcome.

The map: https://globalvendingspot.com/fr/carte-distributeurs (also https://globalvendingspot.com/de/automatenkarte and https://globalvendingspot.com/at/automatenkarte). The filtered data, as CSV and GeoJSON under the ODbL: https://globalvendingspot.com/fr/carte-distributeurs/donnees

Data © OpenStreetMap contributors, ODbL.


Florian Lohoff

Micromapping still kills OSM

As i again came by ridiculous mapped junctions i remembered my post of beginning of 2024 "Micromapping will kill OpenstreetMap" and i still stand by that statement. This ignorance about semantics is the cause for developments like Overture Maps. No data consume wants to guess around and get into the conflict with Bob Ross.

I made a quick tool to find parts of these junctions: Wrong pedes

As i again came by ridiculous mapped junctions i remembered my post of beginning of 2024 "Micromapping will kill OpenstreetMap" and i still stand by that statement. This ignorance about semantics is the cause for developments like Overture Maps. No data consume wants to guess around and get into the conflict with Bob Ross.

I made a quick tool to find parts of these junctions: Wrong pedestrian lights


OpenStreetMap User's Diaries

New mapper looking for feedback on campus edits

Hi everyone! I’m a university student, mapping around campus as part of a class assignment. I’m still learning OSM’s tagging conventions and sourcing norms, so I’d really appreciate any feedback, suggestions, or corrections on my edits and changeset comments. If you review any of my edits, feel free to leave a comment or reply here. Thanks so much for your time and guidance!

Hi everyone! I’m a university student, mapping around campus as part of a class assignment. I’m still learning OSM’s tagging conventions and sourcing norms, so I’d really appreciate any feedback, suggestions, or corrections on my edits and changeset comments. If you review any of my edits, feel free to leave a comment or reply here. Thanks so much for your time and guidance!

Sunday, 08. November 2026

OpenStreetMap User's Diaries

Mystic Link Trail sources

The Mystic Link Trail is a conceptual effort to link together various green spaces to form a route from Ward Reservation in Andover, MA, US down to Boston, ending at the wharf where the Constitution is docked. See the main website for all the details. In its present form, it’s a little over 32 miles long.

We have a relation defined in Open Streetmap to gather all the relevant ways, and

The Mystic Link Trail is a conceptual effort to link together various green spaces to form a route from Ward Reservation in Andover, MA, US down to Boston, ending at the wharf where the Constitution is docked. See the main website for all the details. In its present form, it’s a little over 32 miles long.

We have a relation defined in Open Streetmap to gather all the relevant ways, and a downloadable GPX file with mile markers for easy on-device following. Note that there are some areas where bicycles are not permitted, so there will be an alternate relation so riders can bypass some minor sections.

If one thinks of the Bay Circuit trail as a big wheel around the Boston metro area, we are kind of a north-to-south spoke.


I am working on mapping houses in Belmore.

After mapping I will walk around and slowly put all the house addresses.

After mapping I will walk around and slowly put all the house addresses.


weeklyOSM

weeklyOSM 850

♦[1] MIYADAIKU manga map | map data © by OpenStreetMap Contributors. 29/10/2026-04/11/2026 Mapping The iD tagging schema v7.3.0 was released, bringing new features to iD, GoMap!!, EveryDoor, and other editors. It includes several new, better icons. A number of new structural definitions are now available for editing software. Presets now state, for example, that nodes within power=line are more li
weeklyOSM 850
[1] MIYADAIKU manga map | map data © by OpenStreetMap Contributors.

29/10/2026-04/11/2026

Mapping

  • The iD tagging schema v7.3.0 was released, bringing new features to iD, GoMap!!, EveryDoor, and other editors. It includes several new, better icons. A number of new structural definitions are now available for editing software. Presets now state, for example, that nodes within power=line are more likely to be power=tower than, for example, waterway=waterfall. Information about more relation roles was also added. Note that editing software needs to be updated to use this new info. Also included were many other improvements, new presets for railway=platform_edge and more. Many icon improvements, bugfixes, tweaks and documentation improvements. 151 changes in total. Thanks to all contributors!

Mapping campaigns

  • Tykayn is inviting people on Mastodon to contribute to the France Project of the Month (Projet du Mois) on schools . There are 9,900 schools left to be added to OSM in the France metropolitan area, and 45,000 schools have been recorded by OSM contributors since the project began in 2025.

Community

  • jfd553 has described, in his OSM diary, two years of mapping natural features around the Icefields Parkway in Alberta. It was possible to add more details with recent aerial imagery and revise previous CanVec imports. The diary links to a short video that shows an animated time-lapse OSM map that illustrates the progression of edits over this two-year journey.

Local chapter news

  • The OpenStreetMap community held ► its Hackweekend in Berlin on 24 and 25 October 2026, the largest so far with 25 participants. Topics included embroidered OSM maps, LiDAR scan puzzles and a mobile redesign of the BBBike Extract Service.

Events

  • Geomob has announced its upcoming meetings: Lisbon on 18 November 2026 (venue to be confirmed), Berlin on 25 November 2026 at UP42 (Ohlauer Str. 43), Bristol on 24 February 2027 at The RobinHood Pub and Berlin on 3 March 2027. The first Geomob Bristol will be held in conjunction with OSGeo:UK. It is worth noting that the event will be streamed online and will serve as a trial run for FOSS4G 2027, which is due to take place in Bristol from 23 to 29 August 2027.

  • The organisers of Geomob tooted on their meeting held on 1 October in Berlin, at which six speakers presented innovative geodata projects including an open-source mapping platform, AI-assisted indoor mapping, cost-effective traffic light monitoring using dashcams, AI-based geospatial data analysis and the detection of dead trees using drone imagery, for which Sarah Habershon received the audience award.

  • On Saturday 7 November, Christopher Beddow talked ► at itWikiCon 2026 about photomapping and fotoshi, a new app that lets you link photos to features on OpenStreetMap. Photos are distributed under a CC-BY 4.0 licence but their use is permitted for the purpose of improving OpenStreetMap.

Education

  • Fränze Kellig reported ► that the German Foundation for Engagement and Volunteering had approved FOSSGIS’s funding application, enabling the organisation to establish an OpenStreetMap training programme. The first pilot courses will begin in January 2027, with FOSSGIS currently testing and refining the training modules with initial groups.

  • rphyrin attended the Humanitarian OpenStreetMap Team Global Validator Training Session 1 on 29 October 2026 and learned how to use JOSM’s Extrude tool to create complex building geometries more easily.

Maps

  • David Westerhoff has created a map showing where you can travel by bus and train across Germany within a selected time frame. You can also combine several starting points to find, for example, a meeting point or place of residence. The base map is based on OpenStreetMap data (OpenFreeMap), whilst the timetables come from GTFS.de (DELFI). The calculations are carried out directly in the browser.

  • relytworks has made Printed Canyon, a browser-based tool that transforms OpenStreetMap streets, waterways and parks, alongside Overture Maps building footprints, into city map posters and 3D-printable (STL/3MF) city models, as well as GPX tracks into 3D terrain models.

OSM in action

  • [1] MIYADAIKU (Oyasumi-Gamedev) developed a tool that automatically generates manga background illustrations using OpenStreetMap data. Users can change the location and viewpoint, as well as adjust effects and line thickness. Perhaps the day when OpenStreetMap appears in manga credits is not far away.

  • neketguy is developing an art project to create an interactive 3D map of Kyiv using OpenStreetMap data and elevation data from the World Resources Institute. Some landmark 3D models are also created manually using photographic references.

  • Raffael Meyer has released vlcbici, a web app that helps plan door-to-door trips with València’s Valenbisi bike sharing. It reads live station data from the city’s open data portal, picks a pickup station with bikes and a return station with free docks, and routes the walk, the ride and the final walk using OSRM on OSM data. A CyclOSM layer shows the cycling infrastructure. The source code is available under the MIT licence.

Open Data

  • Isometric Bielsko-Biała is a live pixel-art map of 456 km² of southern Poland built from OSM and Polish open data (GUGiK LiDAR and LoD2). OSM supplies the ground, the ~39k buildings newer than the LoD2 data, the road graph for a traffic microsimulation, the rail graph for timetable trains, aerialways, lamps and trails. leaf_type decides the species of 1 million LiDAR-detected trees.

  • Marcelo Medina has created three tools that combine data from the 2024 Bolivian census with OpenStreetMap data. The first answers the question of where to start a business in the Cochabamba Department, the ‘2024 Census Atlas of the Cochabamba Department’ displays census data broken down by municipality, zone, neighbourhood and block, and the third lets you find nearby businesses and services.

Software

  • Nikandr Surkov’s phone app BlockMap, built on the open-source Arnis engine, turns any place into a playable Minecraft world. A new page shows, on central Ubud (Bali), what OpenStreetMap’s roads and buildings, Overture buildings, ESA WorldCover land cover, canopy heights and terrain each add to the world.

  • Simon Legner built DinoData, an OpenStreetMap tag editor inspired by Wikidata’s editing interface.

  • Gomal Amin has developed OpenHVRA, a hazard, vulnerability and risk assessment tool, powered by OpenStreetMap data.

Programming

  • Jonathon Ready demonstrated how he optimised the compact AI model Finch through supervised training and reinforcement learning so that it can answer questions about locations using OpenStreetMap data entirely offline on a smartphone. In a benchmark he developed himself, comprising 100 travel-related questions, Finch achieved the same answer quality as Gemini 3.8 Flash, provided verifiable source references significantly more often, and required only around 782 MB of memory on an iPhone 16 Pro, whilst the experiments also demonstrate how AI models can exploit vulnerabilities in automated evaluation systems.

  • The developers at Voygr are testing six AI language models to see whether they can reconstruct San Francisco without access to maps or the internet, using only coordinates. By comparing 41,526 points with OpenStreetMap data they demonstrated that whilst the best models correctly identify around 86 per cent of the city’s area and well-known geographical features, they largely fail to identify the exact course of the streets, even with greater computational effort.

  • The Leaflet GeoSearch maintainers released version 5.2.0 on 27 October. It added an OpenGeocoding provider for address autocomplete and reverse geocoding using OpenStreetMap and other open data. This release also fixed submitting search results without coordinates. The hosted API requires a key; its geocoding engine is source-available, not open source.

  • Simon Legner compared several existing OSM data formats, including Level0L, JOSM, and OsmChange, and explored what OSM data might look like in TOML (Tom Preston-Werner’s ‘obvious minimal language’ configuration file format).

Releases

  • Another month, another recap of changes to the openstreetmap website. Since the last there have been a number of small interface fixes, a first look into reducing certain inefficient database queries, and a continuation of the work around fixing issues flagged by the error monitoring tool.

  • Version 2.0.0-beta.1 of Leaflet has been released, introducing full tree-shaking support so applications only have to bundle the features they use. As a result a map with a tile layer now requires just 25.6 kB gzipped, down from 38 kB.

Did you know that …

  • … you can set reminders for OpenStreetMap notes using NotesReminderBot? You can also explore other OSM-related bots on the wiki.

OSM in the media

  • Bastian Greshake Tzovaras reported how the State of the Map LatAm conference went and why it is important, for the German magazine Amerika21.

Other “geo” things

  • Kieran Healy analysed New York City’s 311 service requests and complaints data from 2022 to 2025, categorised them by neighbourhood and complaint type, and visualised the results on a map.

  • UNESCO is launching a new comic book on the mangroves of Latin America and the Caribbean, Las visiones del manglar (the visions of mangroves), which was presented during the 17th Conference of the Parties to the Convention on Biological Diversity, taking place in Yerevan, Armenia, from 19 to 30 October 2026. The comic, in Spanish, combines illustrations, storytelling and scientific research to raise awareness of mangrove conservation, in connection with a UNESCO project.

  • The BBC reported that the telephone box at Dunsop Bridge, in the Ribble Valley, Lancashire, was the 100,000th telephone kiosk installed in Great Britain. It is considered a nationally significant kiosk because it stands near one of the claimed geographical centres of Great Britain.

Upcoming Events

Country Where Venue What When
🇪🇸 Madrid TomTom, Edificio Aqua, Calle Agustín de Foxá 4 State of the Map España 2026 (SotMes 2026) 2026-11-06 - 2026-11-07
🇫🇷 Angers L’Arrière Train, 3 rue de Frémur, Angers Angers Rencontre mensuelle OpenStreetMap 2026-11-06
🇮🇳 Bengaluru Sanjay Nagar OSM Bengaluru Mapping Party 2026-11-07
🇦🇹 Salzburg HTL Itzling Maker Days Salzburg 2026-11-07
🇮🇹 Angera Mapathon @ Angera 2026-11-07
Mapathon 2026-11-08
🇩🇰 København Cafe Bevar’s OSMmapperCPH 2026-11-08
CartONG : Mapathons en ligne 2026-2027 2026-11-09
🇹🇼 臺北市 MozSpace Taipei OpenStreetMap x Wikidata Taipei #94 2026-11-09
🇺🇸 Salt Lake City Woodbine Food Hall OSM Utah Monthly Map Night 2026-11-10
🇩🇪 Magdeburg Netz39 e.V. , Leibnizstraße 32, 39104 Magdeburg OSM Stammtisch Magdeburg 2026-11-10
🇩🇪 Hamburg “Variable”, Karolinenstraße 23 Hamburger Mappertreffen 2026-11-10
🇬🇧 City of Westminster The Volunteer pub London pub meet-up 2026-11-10
🇺🇸 San Jose Online South Bay Map Night 2026-11-10
🇩🇪 temporärhaus OSM-Stammtisch Ulm/Neu-Ulm 2026-11-10
iD Community Chat 2026-11-11
🇨🇭 Zürich 192. OSM-Stammtisch Zürich 2026-11-11
🇩🇪 München Echardinger Einkehr Münchner OSM-Treffen 2026-11-11
OSM US Mappy Hour: Mapping Route 66 Past & Present 2026-11-11
🇨🇿 Olomouc Přírodovědecká fakulta Univerzity Palackého Olomoucký listopadový mapathon 2026-11-12
🇩🇪 Berlin Neumanns 221. OSM-Stammtisch Berlin-Brandenburg 2026-11-12
🇫🇷 Tours Étape 84 [Tours] Rencontre locale de novembre 2026 2026-11-12
🇩🇪 Bochum Das Labor, Alleestraße 50, Bochum OSM-Treffen Bochum 2026-11-12
🇮🇳 Kottayam Kottayam, Kerala State of the Map Kerala (SoTM Kerala) 2026-11-14 - 2026-11-15
🇮🇪 Dublin 4 Inns Court, Winetavern Street, Dublin, D08 XY00 OpenStreetMap Ireland AGM - 2026 2026-11-14
🇮🇳 New Delhi South Delhi OSM Delhi Mapping Party No.34 (South Zone) 2026-11-15
CartONG : Mapathons en ligne 2026-2027 2026-11-16
Missing Maps London Mid-Month for Advanced Mappers (no training provided) (Online) [eng] 2026-11-17
🇫🇷 Lyon Tubà Réunion du groupe local de Lyon 2026-11-17
🇩🇪 Chemnitz Kaffeesatz, Chemnitz OSM-Stammtisch Chemnitz 2026-11-17
🇩🇪 Bonn Dotty’s 206. OSM-Stammtisch Bonn 2026-11-17
🇩🇪 Berlin Online FOSSGIS AG OSM und Outdoor 2026-11-17
🇩🇪 Online Lüneburger Mappertreffen (online) 2026-11-17
🇬🇧 Mott MacDonald Offices Mott MacDonald GIS Day Mapathon [18/10/2026] 2026-11-18
🇬🇧 Manchester Pegasus Group Mapathon Charity Day 2026-11-18
🇺🇸 Cal Poly Humboldt Library 121 Cal Poly Humboldt GIS Day Mapathon 2026-11-18
🇩🇪 Karlsruhe Schwarzer Kater Stammtisch Karlsruhe 2026-11-18
🇨🇿 Praha Kanceláře Lékařů bez hranic - Qubix Pražský GeoWeek mapathon s Lékaři bez hranic 2026-11-19
GeoWeek Luxembourg Mapathon [FR/EN] - Hybrid 2026-11-19
🇧🇪 Gent Gemeenschappelijke ruimte Wijgaard Meetup in Gent 2026-11-19
OSMF Engineering Working Group meeting 2026-11-20
🇬🇧 Leicester University of Leicester Friends of MSF Leicester Mapathon 2026-11-20
🇫🇷 Metz Espace Arob@se - Metz Atelier OpenStreetMap Metz 2026-11-21
🇫🇮 Espoo Aalto-University, Space 21. OSM Suomi 2026 2026-11-21
🇩🇪 Magrathea Laboratories e.V. 1. OSM Stammtisch Fulda 2026-11-22
CartONG : Mapathons en ligne 2026-2027 2026-11-23
🇨🇿 Brno Univerzitní kampus Bohunice, Kamenice 753/5, Brno, Listopadový brněnský Missing Maps Mapathon na Ústavu botaniky a zoologie 2026-11-23
🇬🇧 Llanfairfechan Library Mapwyr Cymru: Mapathon Gogledd Cymru #2 🏴󠁧󠁢󠁷󠁬󠁳󠁿 2026-11-23
🇩🇪 Stadtgebiet Bremen Online und im Hackerspace Bremen Bremer Mappertreffen 2026-11-23

This weeklyOSM was produced by MatthiasMatthias, PierZen, Raquel Dezidério Souto, Strubbl, Andrew Davidson, barefootstache, derFred, mcliquid.
We welcome link suggestions for the next issue via this form and look forward to your contributions.

Saturday, 07. November 2026

OpenStreetMap User's Diaries

Ten Years After São Paulo: A Chronicle of a State of the Map LATAM at Home (SotM LATAM 2026, Mexico City)

Ten years ago, I attended my first State of the Map LATAM in São Paulo, thanks to a travel grant. Until then, for me, OpenStreetMap was just the group we’d formed in Mexico out of the legendary Rancho Electrónico, Mexico City’s hackerspace. During those days, I discovered it was so much more: a regional community, with faces, stories, perspectives, and generosity. I understood why these in-perso

Ten years ago, I attended my first State of the Map LATAM in São Paulo, thanks to a travel grant. Until then, for me, OpenStreetMap was just the group we’d formed in Mexico out of the legendary Rancho Electrónico, Mexico City’s hackerspace. During those days, I discovered it was so much more: a regional community, with faces, stories, perspectives, and generosity. I understood why these in-person gatherings matter so much. They gave rise to friendships that have lasted a decade—sometimes in person and mostly online—and I believe that through these networks we’ve accomplished important things. From that very first time, together with other women, we also decided to promote inclusion and diversity in the community, and that’s how Geochicas was born.

That’s why, when I decided to lead the Mexican edition, I did so with great enthusiasm. It was a whole year of intense emotions, thinking about bringing well-known figures and new people from across the region to my city, happy at the idea that they would experience the city at its best and, hopefully, learn more about its cultural details.

A priority from the very beginning was to secure enough sponsorship to fund a significant number of scholarships, allowing even those from the most distant countries in the Southern Cone to attend. More than half of the funds went toward scholarships. Some scholarships could not be used due to visa issues, but the effort was worth it. There were 272 attendees, 113 of whom were women, and three days of technical, community, and personal exchange, with affordable food and drinks. We also wanted the event to be inclusive: there was a quiet room and a workspace for those who needed a break, to relieve stress, or to concentrate.

We made a conscious choice to hold it in the Historic Center, at Patio Chico, UNAM: we wanted it to be more than just a conference, but an experience with maximum interaction among people. And it coincided with the Day of the Dead, when the entire city beats to the same rhythm of empathy and remembrance, with open hearts to honor those we have loved. It was beautiful to see so many people discover this cultural tradition and experience new emotions. It was also a very intense intellectual and practical gathering: new technologies, methods, and mapping topics, building on the work done in Belén and Medellín while introducing its own innovations.

A self-organized, women-led event

The event was led by women. Many people participated, but we devoted all our energy to it for a year, with the intensity building as we neared the end. Let’s make it normal to recognize those who contribute the most and who, because their efforts are so all-consuming, don’t get to appear in photos or speak into the microphone. None of this would have been possible without Yasmila (Mila) Saenz Herrera, who played a central role in organizing the last two SotMs here: together, we made it happen. Thanks also to:

  • Miriam Gonzalez-Sanchez, for securing the sponsorships, which were essential to everything.
  • Adriana Ávila Farfán and Andrea Berrocal, from UNAM-Patio Lab.
  • Zeltzin Palacios and her UAM community.
  • Alma Rangel Macías, from Codeando México.
  • Sandra Lucía Hernández Zetina, Benita Hernández Carbajal, and the volunteers from UAEMex, who handled all the logistics.
  • And many more.

A thousand thanks to our partners: the UNAM General Directorate for the Dissemination of Science, Patio Lab, the Autonomous University of the State of Mexico, and SEDATU (Secretariat of Agrarian, Territorial, and Urban Development). Thanks also to the young mappers and our sponsors, who make all of this possible: Overture Maps Foundation, TomTom, HERE Technologies, Development Seed, Humanitarian OpenStreetMap Team, and OpenStreetMap US. It’s important to keep building our community with you all!

What Made Me Feel It Was Worth It

Seeing the community’s satisfaction and the new connections it’s forming fills me with joy. I’ve heard people say spontaneously on several occasions that they want to help organize community, regional, and national activities, and there’s already talk of a first SotM Mexico. That’s where I see success, because that’s what sustains a community. But let’s be clear: what sustains it is genuine commitment, not just intention—even though everything starts with intention. To those who have expressed this, and to anyone reading this who wants to join us: welcome.

A Call for Self-Care

At almost every event, the reality is that very few people shoulder the bulk of the responsibility, which ends up being much greater than planned. That leads to burnout, and burnout can cause someone to step back from their community involvement. Viewed objectively, the community loses leaders, who are essential resources for it. We should address this collectively: distribute the workload more evenly, learn to truly commit, take care of one another among us organizers, and create conditions for leadership to develop healthily rather than burn out. I’d love to read your comments: How have you experienced this in your communities? What has worked?

PS: Translated with DeepL.


Diez años después de São Paulo: crónica de un State of the Map LATAM en casa (SotM LATAM 2026, Ciudad de México)

Hace diez años asistí a mi primer State of the Map LATAM, en São Paulo, gracias a una beca de viaje. Hasta entonces, para mí OpenStreetMap era el grupo que habíamos formado en México a partir del mítico Rancho Electrónico, el hackerspace de la CDMX. En esos días descubrí que era mucho más: una comunidad regional, con rostros, historias, perspectivas y generosidad. Entendí por qué importan tanto

Hace diez años asistí a mi primer State of the Map LATAM, en São Paulo, gracias a una beca de viaje. Hasta entonces, para mí OpenStreetMap era el grupo que habíamos formado en México a partir del mítico Rancho Electrónico, el hackerspace de la CDMX. En esos días descubrí que era mucho más: una comunidad regional, con rostros, historias, perspectivas y generosidad. Entendí por qué importan tanto estos encuentros presenciales. De ahí salieron amistades que han durado una década, a veces en persona y sobre todo en la virtualidad, y creo que con esas redes hemos hecho cosas importantes. Desde esa primera vez, junto con otras mujeres, decidimos también impulsar la inclusión y la diversidad en la comunidad, y así nació Geochicas.

Por eso, cuando me convencí de liderar la edición mexicana, lo hice con emoción. Fue un año entero de sentimientos intensos, pensando en traer a mi ciudad a gente conocida y a personas nuevas de toda la región, feliz a la idea de que iban a vivir la ciudad en su mejor periodo y ojala conocer más detalles culturales.

Una prioridad desde el inicio fue conseguir patrocinios suficientes para financiar un buen número de becas, que permitieran venir incluso a quienes están en los países más lejanos del Cono Sur. Más de la mitad de los fondos fue a becas. Algunas no pudieron usarse por problemas de visas, pero el esfuerzo valió la pena. Fueron 272 asistentes, 113 de ellas mujeres, tres días de intercambio técnico, comunitario y humano, con comida y bebida accesibles. Quisimos además un evento que cuida: hubo un salón silencioso y una sala de trabajo para quienes necesitaban pausa, bajar el estrés, o concentrarse.

Texto alternativo

Elegimos hacerlo en el Centro Histórico, en Patio Chico, UNAM, de manera consciente: que no fuera solo una conferencia, sino una experiencia con máxima interacción entre personas. Y coincidió con Día de Muertos, cuando la ciudad entera late en una misma frecuencia de empatía y memoria, con el corazón abierto para honrar a quienes hemos querido. Fue hermoso ver a tantas personas descubrir ese rasgo cultural y sentir cosas nuevas. Fue también un encuentro intelectual y práctico muy intenso: nuevas tecnologías, métodos y temas de mapeo, con continuidad respecto a Belén y Medellín y con novedades propias.

Un evento autogestivo y liderado por mujeres

El evento fue liderado por mujeres. Participaron muchas personas, pero dedicamos toda nuestra energía durante un año, con una intensidad creciente hacia el final. Normalicemos nombrar a quienes más aportan y que, por lo absorbente de su esfuerzo, no alcanzan a salir en las fotos ni ante el micrófono. Nada de esto habría sido posible sin Yasmila (Mila) Saenz Herrera, central en el desarrollo de dos SotMs para acá: juntas lo sacamos adelante. Gracias también a:

Miriam Gonzalez-Sanchez, por conseguir los patrocinios, esenciales para todo. Adriana Ávila Farfán y Andrea Berrocal, de UNAM-Patio Lab. Zeltzin Palacios y su comunidad UAM. Alma Rangel Macías, de Codeando México. Sandra Lucía Hernández Zetina, Benita Hernández Carbajal y las y los voluntarixs de UAEMex, que apoyaron toda la logística. Y muchas más.

Mil gracias a nuestros aliados: la Dirección General de Divulgación de la Ciencia de la UNAM, Patio Lab, la Universidad Autónoma del Estado de México y la Sedatu (Secretaría de Desarrollo Agrario, Territorial y Urbano). Gracias también a las juventudes mapeadoras y a nuestros patrocinadores, que le dan el salto a todo esto: Overture Maps Foundation, TomTom, HERE Technologies, Development Seed, Humanitarian OpenStreetMap Team y OpenStreetMap US. Importa seguir haciendo comunidad con ustedes!

Lo que me hizo sentir que valió la pena

Ver las satisfacción y las conexiones nuevas de la comunidad me llena. Varias veces escuché a personas decir espontáneamente que quieren sumarse a organizar actividades comunitarias, regionales y nacionales, y se habla ya de un primer SotM México. Ahí percibo el éxito, porque eso sostiene a una comunidad. Pero hay que ser claras: lo que sostiene es el compromiso real, no solo la intención, aunque todo empieza con la intención. A quienes lo expresaron, y a quien lea esto y quiera sumarse: bienvenidx.

Un llamado sobre el autocuidado

En casi todos los eventos, una realidad es que muy pocas personas cargan con la mayor parte de la responsabilidad, que termina siendo mucho mayor a la planeada. Eso lleva al agotamiento, y el agotamiento puede hacer retroceder a alguien en su compromiso comunitario. Visto con frialdad, la comunidad pierde liderazgos, que son recursos esenciales para ella. Deberíamos atender esto colectivamente: repartir mejor las cargas, saber comprometernos de verdad, cuidarnos entre quienes organizamos y crear condiciones para que los liderazgos se desarrollen sanamente en lugar de quemarse. Me gustaría leer sus comentarios: ¿cómo lo han vivido en sus comunidades? ¿Qué ha funcionado?


Florian Lohoff

Static RouteQA

Just as an example for RouteQA - This is a static find e.g. just by glacing over the Grid for Essen:

RouteQA Grid Essen

Instead of following the tertiary we are sent over the Farmyard.

The first thing is that someone made the K23 deliberatly bad. Someone tagged "lanes=1" although the road is wide but simply does not have lane markings. So changed that to lane_markings=no.

Just as an example for RouteQA - This is a static find e.g. just by glacing over the Grid for Essen:

RouteQA Grid Essen

Instead of following the tertiary we are sent over the Farmyard.

The first thing is that someone made the K23 deliberatly bad. Someone tagged "lanes=1" although the road is wide but simply does not have lane markings. So changed that to lane_markings=no.

Then somebody tagged "smoothness=horrible" - That was only true for 20m of that road - in the Corner to Stalleickenweg.

Then on the Essen side (See the City Boundary?) the road was perfectly made new.

Then on the Farmyard it was partially "service" without anything. I added service=driveway so it should get weighted down, whereas the K23 gets weighted up.

Friday, 06. November 2026

OpenStreetMap User's Diaries

Blue Posts pub + Next Tuesday The Volunteer

Next Tuesday the OSMLondon pub meet-up will be at “The Volunteer” pub near Baker Street!

Last time we were at the Blue Posts near Tottenham Court Road. We’ve been there many times before, but not for several years (we’ve been avoiding Sam Smiths for reasons, as I explained last time). It didn’t seem to have changed much though. We took over a large part of the pleasantly quiet upstairs a

Next Tuesday the OSMLondon pub meet-up will be at “The Volunteer” pub near Baker Street!

Last time we were at the Blue Posts near Tottenham Court Road. We’ve been there many times before, but not for several years (we’ve been avoiding Sam Smiths for reasons, as I explained last time). It didn’t seem to have changed much though. We took over a large part of the pleasantly quiet upstairs area. I think someone else took a photo, so I didn’t bother (?). Anyway we had maptastic chit-chat as always. I noted down a couple of interesting conversation topics:

We talked about a recurring topic: Should we send automated welcome emails after users sign up? It’s pretty odd that we don’t do this, if we compare ourselves to just about any other user sign-up website, but I think the counter-argument has always been that we’re a very international community, and so we can do this by providing data on new contributors in a region, and letting local communities craft much better more friendly language and context-aware welcome emails. I’m sure this topic has been re-hashed many times over the years.

A leading welcoming tool is “OpenStreetMap Welcome Tool” https://welcome.osm.be from LCCWG. I’ve not tried it. I see it’s not enabled for UK/GB/England (I think some UK people are welcoming new mappers in small areas using OSMCha) but a key feature would seem to be the ability to mark a recipient as “has been welcomed”. I was thinking an alternative hack would be to always welcome user’s via a discussion on their first changeset, just as a “weird trick” to turn it into a publicly viewable rather than private message, so we can see who’s been welcomed.

But anyway I personally think the idea of a brief automated welcome email on registration should still be considered, because manually welcoming seems unlikely to reach everyone, and also there’s that frustrating fact that many users sign up then never get as far as making an edit.

And speaking of these internal channels of promotion, Firefishy was plotting and scheming to do some experiments with homepage banners (like the graphics you may have seen for promoting SOTM). We now have the ability to show these in a location-dependant way, which raises questions about how to organise the promotion of events, but Firefishy was pondering doing an experiment with a banner to promote a particular editor in a particular region, and see what kind of shift in the editor usages stats would happen as a result. Kind of like an “A-B testing” experiment.

We talked about updating shops/POIs data, and how we should really try to drive more use of the FHRS data. There’s some handy comparison tools. But we talked about maybe gamifying this a bit more, or perhaps presenting rankings by council regions to encourage competitive mapping.

Those were some things I noted, but there were many other topics besides. If you fancy joining in with this kind of discussion face-to-face in a pub… come along! The next OpenStreetMap London pub meet-up will take place Tuesday 10th at “The Volunteer” pub on Baker Street. It’s 293 metres north of Baker Street tube, which isn’t a very inaccessible watering hole, but with a name like that I couldn’t resist! See you there?

Thursday, 05. November 2026

OsmAnd

Organizing Your Tracks with Smart Folders

A September morning in Vancouver. More than a thousand riders roll out of Stanley Park for the RBC GranFondo Whistler: 122 kilometres of the Sea to Sky Highway, closed to traffic, with Howe Sound on one side and the mountains on the other. Past Squamish, the road starts to climb and keeps climbing all the way to Whistler.

A September morning in Vancouver. More than a thousand riders roll out of Stanley Park for the RBC GranFondo Whistler: 122 kilometres of the Sea to Sky Highway, closed to traffic, with Howe Sound on one side and the mountains on the other. Past Squamish, the road starts to climb and keeps climbing all the way to Whistler.

You cross the line near the top of the results, and everyone says the same thing: you were lucky. With the weather, the wind, the group.

You know better. That result is made of dark February mornings on the seawall, Sunday climbs up Cypress, and long rides to Squamish and back, all recorded in OsmAnd one track at a time. Let’s see what a season of training looks like once Smart Folders put it in order.

Cycling Whistler

Photo by Ben Guernsey on Unsplash

A Folder That Fills Itself​

A training season doesn’t arrive neatly packed. Between the rides sit a few hikes and a drive to Whistler, and the Tracks tab lists everything by date, with no idea which recordings mattered.

A Smart Folder works the other way round: you describe the tracks you want, and OsmAnd collects them. The description is a filter that can check almost anything a track knows about itself, including length, duration, speed, elevation, date, location, activity type, and even heart rate. Set the activity to road cycling, limit the dates from February to race day, save the result as “Road to Whistler”, and the whole season lands in one place while the hikes stay out.

New rides join the folder on their own. The tracks themselves stay where they were, so deleting the folder never deletes a ride.

One catch: activity type is stored in each track, and older recordings may not have one. If some rides are missing, set their activity and refresh the folder.

Smart Folder FilterSmart Folder Tracks

One Collection, Many Views​

Sixty-seven rides in one folder is tidier than a few hundred, but it’s still a list. Organize by turns that list into groups, sorting the folder by a single parameter: activity, date, location, speed, altitude and elevation, or sensor data such as heart rate. The tracks don’t move anywhere; only the way you look at them changes.

Group the season by nearest city, and you see where the rides began: most of them in Vancouver, a handful from West Vancouver, where the long runs to Squamish set off from Horseshoe Bay, and four from Whistler, once summer made it worth driving up for the climbs. Switch to month and year, and the same folder turns into a calendar, from a cautious February to a crowded August.

Each group shows how many tracks it holds, and empty groups don’t appear at all. Below the list, OsmAnd adds everything up: tracks, distance, climbing, descent, and time in the saddle. It does this for the whole folder and for every group you open. That’s where the season starts answering questions.

Smart Folder Organize by Nearest CitySmart Folder Organize by Month

Drawing the Lines Yourself​

Months and cities come with natural borders. Distance doesn’t. Is a 55 km ride a long one or just a solid Tuesday? For length, duration, speed, and altitude, OsmAnd lets you decide where one group ends and the next begins.

Pick one of these parameters, and a slider asks for a step size. Drag it, and the groups rearrange behind it as you go. With a 50 km step, most of the season piles into the first group, which is honest but not very revealing. Bring it down to 20 km, and the season sorts itself out: short morning laps along the seawall, a big block of loops around UBC, the climbs on Cypress and Seymour further up, the long runs to Squamish, and, at the very end, two tracks of almost exactly the same length: the course recon in August and the race itself.

Some of this is free for everyone: grouping by activity, year of creation, and nearest city. The rest, including the monthly calendar from the previous section and every parameter with a step size, comes with OsmAnd Pro. Without a subscription, you can still open these options and preview how the tracks would split before deciding. If a subscription ends, the grouping you’ve already applied stays in place, and only changing it requires Pro again.

Smart Folder Step Size 50 kmSmart Folder Step Size 20 km

Keeping It in Shape​

The race is over, but the folder doesn’t retire with it. It keeps watching for rides that match its rules, and if the list ever looks out of date, a quick refresh brings it back in line. When the next season starts, there’s no need to build anything new. Edit the filter, move the dates forward, and the same folder starts collecting a new story.

Groups are useful beyond reading, too. Any of them can go straight onto the map, so a whole August of riding appears at once, from the seawall to the climbs above Whistler, every route drawn on top of the others. A group can also be exported in one go, which is handy when a coach asks to see your month and doesn’t want a dozen separate files.

If you plan the next season on a bigger screen, Smart Folders also appear in OsmAnd Web once Settings are synced through OsmAnd Cloud. They keep working best with common parameters such as activity, dates, or distance.

Smart Folder Group MenuSmart Folder Group on the Map

The Answer to the Question​

So, was it luck? Open February, and the folder answers modestly: five rides, 103 km, just over five hours on the bike, and 839 metres of climbing. Then open August: twelve rides, 577 km, a full 24 hours in the saddle, and 6,806 metres of climbing, including the day you rode the entire race course just to see how it would feel.

Smart Folder February SummarySmart Folder August Summary

The whole season fits into a single line at the bottom of the folder: 67 rides, 2,923 km, and more than 33,000 metres of climbing. That’s nearly four times the height of Everest, collected one Cypress hairpin at a time.

No tailwind delivers that. So the next time someone tells you how lucky you were, there’s no need to argue. Just open the folder and hand them your phone.

Share Your Story

Every track in OsmAnd has a person and a story behind it. If you’d like to share yours on our blog, whether it’s a long journey, a season of training, or a route you simply love, we’d be glad to hear from you. Write to Tina, and we’ll make it happen together.


We appreciate your interest in us and thank you for taking the time to read this article. Join us on social media to keep up to date with the latest news and share your experiences. Your opinion is important to us.

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Join us at our groups of Telegram: (OsmAnd News channel), (EN), (IT), (FR), (DE), (UA), (ES), (BR-PT), (PL), (AR), (TR).

Wednesday, 04. November 2026

OpenStreetMap User's Diaries

Update on my iD tagging schema and iD grants - completion of 612 hours of work

see community.openstreetmap.org/t/update-on-my-id-tagging-schema-and-id-grants-completion-of-612-hours-of-work/149730 for overview

see below for more specific list, it was too long to be posted on forums

Funded by OpenStreetMap Foundation

I tested and reviewed this changes prepared by others, recommended changes to be merged and it was followed by maintainers:

see https://community.openstreetmap.org/t/update-on-my-id-tagging-schema-and-id-grants-completion-of-612-hours-of-work/149730 for overview

see below for more specific list, it was too long to be posted on forums

Funded by OpenStreetMap Foundation

I tested and reviewed this changes prepared by others, recommended changes to be merged and it was followed by maintainers:

I tested, approved and merged improvement prepared by someone else:

I suggested merging own code written before grant started and it was followed:

Changes I implemented myself:

LLMs

There is also a sad part. Recently I was also experimenting with using LLMs for part of the work. I absolutely dislike that LLM are a thing, their emergence is second worst thing that happened in my life so far.

Some complaints raised about them are just not making sense. But there are also many valid reasons to dislike then. For start I absolutely detest dependency on a proprietary SaaS. That is run by people who outright hate me, or at best merely want to exploit me. Or open weights produced in a proprietary way, in way that inherently makes impossible for me to reproduce it.

Sadly at this point LLMs are actually highly useful. It is quite easy to fall into traps of various kinds, but can be actually effective in some ways.

The question remains whether they actually should be used and which uses are legitimate. And how to avoid various novel problems. And I am still unsure about proper answer here.

Obviously undisclosed use and/or submitting vibecoded pull requests is just invalid. But there is plenty of potential uses that make sense and can potentially be helpful.

(though I hope that this thread is not going to be about LLMs, I am getting allergy to even mentions of them - though at the same time I am tempted to write a long rant why they are bad in general and also specifically for me)

Other work funded by OpenStreetMap Foundation

I recommended closing and it was followed

I closed it outright (as rejected, unclear, duplicate, abandoned, LLM with no human oversight, misplaced, impossible etc):

I recommended closing as fixed and it was followed (not listing ones closed by PR merges):

I closed it outright as fixed (not listing ones closed by PR merges):

Funded by European Union via Nlnet Foundation

Changes I implemented myself:

I tested, approved and merged improvement prepared by someone else:

I suggested merging own code written before grant started and it was followed:

I tested and reviewed this changes prepared by others, recommended changes to be merged and it was followed by maintainers:

I recommended closing and it was followed

I closed it outright as fixed (not listing ones closed by PR merges):

I closed it outright (as rejected, unclear, duplicate etc):


Mapping Icefields Parkway, Part 1: A two-year mapping journey

I spent two years mapping the areas surrounding one of the most beautiful drives in the world. Each morning, I looked forward to discovering and mapping an area adjacent to a one I did the day before. This diary entry serves as an introduction to a series of texts covering the challenges I encountered and how I overcame them. Included below are a few snapshots taken in the field, which capture

I spent two years mapping the areas surrounding one of the most beautiful drives in the world. Each morning, I looked forward to discovering and mapping an area adjacent to a one I did the day before. This diary entry serves as an introduction to a series of texts covering the challenges I encountered and how I overcame them. Included below are a few snapshots taken in the field, which capture the majestic landscapes along the Icefields Parkway. I have also added a “before and after” map excerpt, as well as a short video, to illustrate how my work gradually took shape over time.

The Place

The Icefields Parkway (Highway 93N), in Alberta, owes its name to the spectacular icefields and glaciers that line the road. The parkway, which is a 232 km stretch of highway cutting through Banff and Jasper National Parks, attracts between 1.2 million and 2 million visitors per year. The parkway offers exceptional alpine landscape, with glaciers, rivers, turquoise lakes, and breathtaking mountain views directly from the roadside (Figure 1). Best of all, many of these landmarks can be reached in a single day’s hike (Figure 2).

Figure1 Figure 1: North Saskatchewan River alongside the parkway. Parker Ridge (2350 m) and Nigel SE3 (3025 m) in the background.

Figure 2 Figure 2: Multiple landmark features shown on the “Tracestrack Topo” map (2026), with Figure 1 POV on the bottom right.

The Scouting Trip

I use the term “scouting trip” here, given what I learned (local knowledge) and the time I spent mapping the area afterwards, but visiting the Rockies was a project my wife and I had had for a long time, absolutely not related to OSM! The plan was to spend a week exploring Jasper, Lake Louise and the Icefields Parkway in between. Unfortunately, when wildfires struck Jasper National Park in 2024, it led to its closure and forced us to change our itinerary at the last minute. We therefore had to abandon this entire segment of the trip and reach Lake Louise via highway 11, the Saskatchewan River crossing and the southern half of the Icefields Parkway (Figure 3).

Figure3 Figure 3: Highway 11 toward the Saskatchewan River Crossing and the southern half of the Icefields Parkway.

We then had more time than expected to explore Banff National Park. Here are a few pictures taken along the parkway and showing landmark features such as Bow Lake (Figure 4) and Peyto Lake (Figure 5). Figure4 Figure 4: South view of Bow Lake with large scree slopes reaching the lake.

Figure5 Figure 5: Peyto Lake and its large alluvial fan. To the left, Peyto Peak and its glacier in the background.

We spent some time in Lake Louise, where we visited its namesake lake (Figure 6) as well as its even more popular neighbor, Moraine Lake (Figure 7); however, what we enjoyed most was hiking the trails surrounding the town, which offer multiple access points to the Bow River (Figure 8).

Figure6 Figure 6: Lake Louise and its turquoise waters. Behind me, the “Chateau Lake Louise” and hundreds of tourists like me.

Figure7 Figure 7: Moraine Lake view taken from the “moraine” crest. Out of frame, hundreds of tourists like me.

Figure8 Figure 8: Bow River, just a few hundred meters from where we stayed in Lake Louise.

Unexpectedly, the Jasper National Park authorities reopened the Athabasca Glacier area during our stay, giving us the opportunity to drive the parkway again. Along the way, we stopped at the Big Bend (Figure 9), the only hairpin bend on the parkway, before continuing on our way to reach the Columbia Icefield area (Figure 10). Figure9 Figure 9: Big Bend viewpoint, looking south toward North Saskatchewan River, and Mount Cirrus (3270 m) on the left.

Figure10 Figure 10: Icefields Parkway toward Columbia Icefield and the Athabasca Glacier.

The Columbia Icefield is not actually visible from the road, even though the Athabasca Glacier originates there. It is possible to get close to the glacier on foot by taking a trail called “Hike to Toe of Athabasca Glacier” (Figure 11). The name of the trail is misleading, as it ends where the foot of the glacier was in 2006 (Figure 12). Unfortunately, you can’t go further unless accompanied by a guide or taking an “Ice Explorer Experience” bus tour because direct access to the glacier is prohibited due to the inherent risks of such an environment.

We did enjoy the experience anyway! Figure11 Figure 11: The few hundred meters hike to reach the closest point to the Athabasca Glacier that you can do on your own.

Figure12 Figure 12: The Athabasca Glacier closest view you can reach on your own. Taken where the foot of the glacier was in 2006.

It is with all these breathtaking landscapes in mind, and fantasizing about all I had not seen, that I decided to map around the parkway and add the spectacular natural features that were sorely lacking in OSM.

The Mapping – Existing content

The area already contained data from the Canvec import. This import has a reputation for being of poor quality. Made available almost twenty years ago, the data derived from 1:50K topographic maps were much more complete than what could be mapped from the 30-80 m resolution imagery available at that time in OSM. But now, current high-resolution imagery reveals its limitations. Vegetation (wood, wetlands) is of poor quality; road and hydrographic networks are present; but need most of the time to be aligned with the imagery before making finer adjustments. I also noticed that some key features were added after the import. Maybe the most significant contribution I found came from one user who mapped most hiking trails (there are many) and routes to different summits along the parkway. In such a wild area, this information is helpful for those who, after parking to admire the view, decide to explore the surroundings (like me). However, apart from these elements, the map was empty all along the road (Figure 13), whereas on the ground, the diversity and immensity of the landscapes struck at each kilometer. Figure13 Figure 13: Standard OSM map view from early 2024. Most of the data comes from the Canvec import.

The Mapping – Adding/Editing Data

I had begun making some edits near Jasper while preparing for our trip, but after wildfires affected the town and the park was closed, I had to pause that work to find alternative routes and make new reservations. Once I got home, I started mapping again, but this time following the route we had taken. I did not yet know that I would spend two years mapping the region, thereby extending my stay and reviving my memories, day after day. By the end of this mapping journey, I had added to the map all the natural features present in an area a hiker might traverse in a day or two, between Jasper and Lake Louise. Here is a small example of what the map looks like now (Figure 14). Figure14 Figure 14: Standard OSM map view from late 2026. Same area as Figure 13, after adding/updating all natural features.

There is so much to say about this mapping journey that I plan to cover these various topics in future entries of my journal (hence the “Part 1” in my title). In the meantime, I have illustrated this journey in a short video (46 seconds), which shows the distribution of my contributions over time. Only the nodes are represented in order to achieve a better visual result.

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*Click to open the video and turn on the sound :-) *

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The route a real person takes

Spent the morning with the Bicycle wiki page and a 300-post thread about access=dismount, and the same thing kept coming up: our cycling data is really good at describing the road, and a bit less good at describing the person on the bike.

We tag the surface, the separation, the access. But the thing that decides whether I actually ride a route is rain, fatigue, and whether I trust the st

Spent the morning with the Bicycle wiki page and a 300-post thread about access=dismount, and the same thing kept coming up: our cycling data is really good at describing the road, and a bit less good at describing the person on the bike.

We tag the surface, the separation, the access. But the thing that decides whether I actually ride a route is rain, fatigue, and whether I trust the stretch where the cycle lane ends and the traffic doesn’t slow down. None of that is in the data, and it’s the part that matters on a Tuesday morning when it’s pouring.

I keep coming back to the idea that the gap between “legal to ride” and “would actually ride” is where the interesting mapping is. Maybe that’s a project for a quieter evening.