Immer wieder werden wir als OpenStreetMap-Community bzw. der FOSSGIS e. V. als Vertreter von OpenStreetMap in Deutschland gefragt, ob wir Schulungen zu OpenStreetMap für andere Vereine und Organisationen anbieten können. Bisher fehlten uns dafür leider die Kapazitäten – dabei liegt es natürlich in unser aller Interesse, mehr Menschen für OpenStreetMap zu begeistern und als aktiv Beitragende zu gewinnen.

Als Community wollen wir natürlich selbst bestimmen, was und wie geschult wird. Es geht nicht nur um technische Grundlagen wie den Umgang mit den OpenStreetMap-Editoren, sondern auch darum, wie unsere Community funktioniert: Wie wir gemeinsam Entscheidungen treffen, welche Daten wir erfassen wollen – und welche nicht – und wie man sich konstruktiv einbringt.

Solche Schulungen zu entwickeln und durchzuführen, ist aufwendig. Einzelne engagierte Community-Mitglieder haben das bereits getan, doch wir möchten das gerne nachhaltiger gestalten, damit es dauerhaft und in größerem Rahmen funktioniert. Deshalb haben wir letztes Jahr einen Förderantrag bei der Deutschen Stiftung für Engagement und Ehrenamt (DSEE) eingereicht – und die gute Nachricht: Der Antrag wurde bewilligt!

Bis Ende 2027 stehen uns 100.000 EUR zur Verfügung (90% davon von der Stiftung, 10% Eigenmittel des FOSSGIS e. V.), um ein nachhaltiges Schulungsangebot aufzubauen. In erster Linie werden sich die Schulungen dabei an andere ehrenamtliche Organisationen richten, zum Beispiel den Naturschutzverein, den Fahrradclub oder die freiwillige Feuerwehr. Nach Ablauf der Förderung soll sich das Angebot aus dem laufenden Betrieb tragen.

In den nächsten Wochen werden wir jetzt eine Arbeitsgruppe „OSM-Schulungen“ im Verein aufbauen, sie ist die Verbindung zur Community und sorgt dafür, dass Ideen und Prioritäten aus der Community in die Schulungsinhalte einfließen. Für die inhaltliche Koordination wird ein Auftrag an einen Freelancer vergeben. Die Hauptaufgabe liegt darin, Material zu sichten und Schulungsmodule zu entwickeln – stets in enger Abstimmung mit der Arbeitsgruppe. Und wir richten eine neue Teilzeitstelle im FOSSGIS ein, die sich um die Organisation der Schulungen kümmern soll: von der Werbung für das kommende Angebot und dem Austausch mit Organisationen, die an Schulungen interessiert sind, bis zur Durchführung der Anmeldungen und dem Schreiben von Rechnungen. Wenn möglich, soll diese Stelle auch dauerhaft nach Ende des Förderprojektes erhalten und ggf. ausgebaut werden.

Wenn Du Interesse hast, ehrenamtlich an der Arbeitsgruppe mitzuarbeiten oder Dir vorstellen kannst in Zukunft Schulungen als Freelancer oder gegen Übungsleiterpauschale zu übernehmen oder an einer der bezahlten Stellen interessiert bist, dann melde dich gerne per E-Mail an jochen.topf@openstreetmap.de.

Das Projekt wird durch die Deutsche Stiftung für Engagement und Ehrenamt über das Programm transform_D unter der Nummer DSEE-TD-1065697 gefördert.

Taking info from

https://www.rigacci.org/wiki/doku.php/doc/appunti/hardware/gps_logger_i_blue_747

and

https://www.technologyblog.de/2019/05/gps-rollover-zerstoert-gps-logger/

and

https://wiki.openstreetmap.org/wiki/Holux_M-241

a modified mtkbabel can set the time when reading from the device. That should probably go into some check whether it’s really a M-241 that is connected, but as long as the battery lasts the device shows the correct time again and logs tracks in this year and not dated 2006..

$ diff -u /usr/bin/mtkbabel ./mtkbabel
--- /usr/bin/mtkbabel   2019-10-12 12:23:29.000000000 +0200
+++ ./mtkbabel  2026-03-03 19:37:37.482923895 +0100
@@ -166,7 +166,7 @@
 #-------------------------------------------------------------------------
 my $debug    = $LOG_WARNING;     # Default loggin level.
 my $port     = '/dev/ttyUSB0';   # Default communication port.
-my $baudrate = 115200;           # Default port speed.
+my $baudrate = 38400;           # Default port speed.
 my $ro_weeks = 0;                # Weeks offset to fix Weeks Rollover Bug

 # GPX global values.
@@ -356,6 +356,18 @@
     set_data_types($model_id);
 }

+# Set time to work around week rollover bug
+
+my ($sec,$min,$hour,$mday,$mon,$year) = gmtime;
+
+$year += 1900;      # year is years since 1900
+$mon  += 1;         # month is 0-11
+
+packet_send(sprintf('PMTK335,%04d,%02d,%02d,%02d,%02d,%02d', $year, $mon, $mday, $hour, $min, $sec));
+$ret = packet_wait('PMTK001');
+printf "Set time string: $year, $mon, $mday, $hour, $min, $sec\n";
+printf "Return for setting time: $ret\n";
+
 #-------------------------------------------------------------------------
 # Erase memory.
 #------------------------------------------------------------------------- 

I have created a tag, diet:excipient_free=* , which is about finding clean supplements, i.e., without harmful ingredients that can make us infertile, inflamed, obese or even epileptic.

For example, whenever we look for magnesium (bis)glycinate, we want one thing, but many so-called “magnesium” supplements come with a lot more ingredients that might reduce the price, or enhance the appearance, but of course, at a cost; to hurt and make us need another supplement to compensate with the side effects. (Maybe they should rename those “magnesium” supplements to corn syrup supplements instead.)

Almost if not all of those ingredients fall into one category, excipients. Let’s use diet:excipient_free=* on pharmacies and nutrition supplement stores to promote a healthier future without dyes, fillers, flavorants, preservatives and other inactive ingredients that can cost us our health.

🌳 Percebendo que havia poucas informações no OpenStreetMap sobre o Parque Evaldo Cruz, em Campina Grande - PB, iniciei há uns meses o micromapeamento da área motivado pela reforma que ocorreu no local, por ser uma área verde que frequento cotidianamente e ser parte do Parque do Povo, onde acontece o Maior São João do Mundo.

Identificação em campo de Handroanthus impetiginosus (Ipê-roxo-de-bola)

📚 Sou pesquisador da área ambiental então sempre tento mostrar o potencial que o mapeamento para o OpenStreetMap possui. Os resultados abaixo são relacionados às árvores mapeadas e identificadas no local do parque, um trabalho que iniciei faz mais de seis meses e está quase 100% pronto. Quem quiser acompanhar esses e outros mapeamentos, costumo divulgá-los no Instagram - OMapaPB.

🗺️ Esses mapas mostram as espécies de árvores que existem no parque atualmente. A identificação foi feita por chaves botânicas disponíveis na Plataforma Reflora e SiBBr, literatura da Embrapa e, principalmente, a coleção de livros sobre espécies arbóreas brasileiras e exóticas de Lorenzi.

🌲 As principais árvores encontradas são de espécies exóticas como as mungubas, algarobeiras, flamboyants e os ipês-rosa-de-el-salvador que é muitas vezes plantado como nativo por várias prefeituras.

DOI: https://doi.org/10.5281/zenodo.18810801

Nesse próximo mapa, é possível verificar a quantidade de indivíduos de cada espécie, essencial para determinar a riqueza e diversidade das espécies.

DOI: https://doi.org/10.5281/zenodo.18810614

O interessante de mapear o formato da copas das árvores, é que é possível renderizá-las em 3D, por exemplo no F4Map.

Renderização em 3D do Parque Evaldo Cruz pelo F4Map

Embora mais etiquetas possam e devem ser utilizadas num inventário arbóreo (como Diâmetro a Altura do Peito - DAP, altura, fitossanidade e etc) e já existam etiquetas assim no OpenStreetMap, optei por não adicioná-las no momento.

Exemplo de etiquetas usadas no mapeamento de um indivíduo da espécie Tabebuia rosea. Abrir no OpenStreetMap

🐜 Com o tempo mais informações serão adicionadas e já estou iniciando o mapeamento de outro parque urbano, o Parque da Criança. Estou muito orgulhoso do resultado e espero que incentive outras pessoas a fazerem o mesmo 🙂. É um trabalho de formiguinha que é muito prazeroso.

Gente que fecha nota dizendo que resolveu o problema, mas não resolve. Ou gente que resolve mas não fecha a nota.

Die digitale Transformation wird oft abstrakt diskutiert. Mich hat jedoch eine praktische Frage beschäftigt: Wie kann ich in meiner Lehre zeigen, dass (Geo)Daten, Algorithmen und künstliche Intelligenz tatsächlich zur Lösung urbaner Herausforderungen genutzt werden können? Mir ging es dabei nicht nur um theoretische Konzepte, sondern um anwendungsnahe Lehrforschung: realen Daten, greifbare Fragestellungen und idealerweise einen konkreten Mehrwert für die Stadt Mainz.

Wieso bin ich ein Fan von Lehrforschungsprojekten? Die Studierenden haben sich in meinen Mastermodulen immer wieder klar positioniert: Sie wollen mehr Forschung, mehr Praxisbezug, „Hands-on“ und eigenständiges Arbeiten mit fachlicher Begleitung. Daraus ist folgendes Format entstanden: projekt- beziehungsweise problembasiertes Lernen anhand konkreter Projektausschreibungen. Im Modul „Geo-Government und Digitale Transformation“ arbeiten die Studierenden so in Zweierteams an Fragestellungen und entwickeln eigenständige Lösungsansätze.

Die Projektausschreibungen als Ausgangssituation

1. 1. Verkehrsfluss, Stauursachen und KI-gestützte Prognosen
      Mainz steht regelmäßig vor Herausforderungen durch Staus und stockenden Verkehr, insbesondere während der morgendlichen und abendlichen Rush Hour. Die hohe Verkehrsbelastung beeinträchtigt nicht nur die individuelle Mobilität, sondern wirkt sich auch auf Umwelt, Luftqualität und Stadtklima aus. Im Mittelpunkt steht daher die Analyse, wann und wo die größten Engpässe im Mainzer Stadtverkehr auftreten und welche räumlichen sowie zeitlichen Muster sich erkennen lassen. Ebenso ist zu untersuchen, welche Faktoren Stausituationen verstärken. Aufbauend darauf soll geprüft werden, wie KI-gestützte Verfahren dazu beitragen können, Verkehrsflüsse präziser vorherzusagen und gegebenenfalls aktiv zu steuern.
   2. Bikesharing in Mainz: Nutzung, Nachfrage und Verfügbarkeit
      Bikesharing gilt als flexible und nachhaltige Alternative zum privaten Pkw und ist ein wichtiger Baustein moderner urbaner Mobilitätskonzepte. In der Praxis zeigt sich jedoch häufig ein Ungleichgewicht: An stark frequentierten Standorten fehlen zu Stoßzeiten verfügbare Räder, während sie an anderen Stationen ungenutzt bleiben. Ziel ist es, räumliche und zeitliche Nutzungsmuster zu analysieren, Engpässe und Überangebote zu identifizieren und Einflüsse wie Tageszeit, Wochentag oder Wetterbedingungen zu berücksichtigen. Darauf aufbauend stellt sich die Frage, wie KI-gestützte Modelle dazu beitragen können, Verfügbarkeit und Nachfrage besser aufeinander abzustimmen.
   3. Parkhausnutzung und intelligente Lenkung des Innenstadtverkehrs
      Viele Autofahrende kennen die Situation: Statt direkt einen freien Stellplatz zu finden, kreisen sie durch die Innenstadt. Dieser Parksuchverkehr erzeugt zusätzlichen Verkehr, erhöht Emissionen und belastet die urbane Infrastruktur. Zu analysieren ist, wie sich die Auslastung der Parkhäuser über Tages- und Wochenverläufe verteilt und welche wiederkehrenden Muster, etwa bei Veranstaltungen oder Ferienzeiten, erkennbar sind. Darauf aufbauend soll untersucht werden, wie KI-gestützte Prognosen helfen können, Belegungsentwicklungen vorherzusagen und Parksuchverkehr gezielt zu reduzieren.

Forschung statt Reproduktion: Mein didaktischer Ansatz
Das Lehrformat verfolgt bewusst einen forschungsorientierten Ansatz. Im Mittelpunkt stehen weder reine Literaturarbeiten noch bloße Demonstrationen bestehender Tools. Stattdessen sollen die Studierenden eigenständig Hypothesen entwickeln, ein geeignetes Forschungsdesign konzipieren und reale Datenbestände analysieren. Entscheidend ist dabei für mich nicht die Präsentation einer vermeintlich „perfekten Lösung“, sondern der Aufbau einer gewissen Methodenkompetenz, die Förderung kritischen Denkens und die reflektierte Anwendung von KI. Gerade in einem Masterstudium geht es meines Erachtens nicht allein um die Fragen „Was ist technisch möglich?“, sondern vielmehr um: Was ist fachlich sinnvoll, ethisch vertretbar und (administrativ) umsetzbar?

Und wer weiß, vielleicht münden die Ergebnisse am Ende sogar in eine Publikation …

OpenStreetMap old timers know about the infamous 2009 TIGER import of road data in the US that continues giving to this day. Our story has none of the, maybe deliberate, shenanigans (see the TIGER improvement project) that went on back then in the US, but there are clearly some similarities in the lessons that should be learnt.

Back in July of 2011 the Swiss community undertook a big effort to import municipality boundaries from swisstopo (the marketing name of the federal Swiss GIS department) (see osm.wiki/Switzerland/swissBOUNDARIES3D). Being an OSM n00b at the time with just a bit over a year editing experience I didn’t really do anything useful for the import proper, but I did organise the explicit permission needed from swisstopo as this was many years before their data would become available for use on open terms for us in September 2021. With a couple of technical hiccups along the way that are not really documented, we finally managed to complete the work by early August.

Fast forward to today: I’ve been going on for a few years now that we really need a quality assurance process so that we can discover and track differences between swisstopos data and what is in OSM. We knew and fully expected that there would be differences, because:

• at the time of the import we simplified the boundaries quite significantly because of the resource constraints of the computer hardware available to us,
• over the last 14 years we independently followed the mergers and other changes of the municipalities (see osm.wiki/Switzerland/2026_Municipality_Mergers), and didn’t expect this to improve the accuracy of the boundaries, and we knew that now and then there would be associated minor geometry changes that we wouldn’t be able to track,
• and then just general decay due to glueing and accidental modifications.

Thanks to work by our community member habi inspired by earlier work by Branko Kokanović from Serbia, we have now have daily QA data and boy, we were wrong.

We had already got an inkling of the real issue back in 2024/2025 when we started getting complaints from the French community and an unnamed big tech company about municipality boundaries in lakes (see https://community.openstreetmap.org/t/heads-up-municipality-boundaries-in-lakes/125007). At the time we assumed that this was simply due to cantonal policy changes that annoyingly hadn’t been included in the Federal Statistics Office municipality mutations documentation (this is what we use to determine which and when to merge or otherwise change municipalities) and we duly fixed all of those that we were aware of last year.

As said, this was annoying, but largely inconsequential as we are talking about water areas with no really relevant infrastructure.

But looking at our newly generated QA data it was clear that not only did we have another bunch of border in lakes issues (see https://community.openstreetmap.org/t/municipality-borders-in-lakes-yet-again-but-with-a-twist/141020) including some really weird things in the Thuner- and Brienzersee, there was a larger numbers of significant differences, for example every single municipality border in the canton Ticino (the Italian speaking part of Switzerland), and not only that: inspection of the data revealed that all these issues had already been present in the original data that we had imported back in 2011.

What we hadn’t realised back then was just how much the swistopo data was a work in progress, and I while I would note that swisstopo didn’t put a big red warning about this on their documentation, there was no deliberate subterfuge on their behalf, at worst somewhat exuberant marketing. We were simply blinded by the belief that this was the gold standard and naively assumed that any errors would be ours.

The good news is that habi and myself have fixed the most egregious issues over the last two weeks and with some more chipping away we should soon have a better than good enough set of boundaries available.

habis work can be found here: https://github.com/habi/swissboundaries

PS: we’ve come a long way since 2011: I’ve done all the boundary work on my phone that can easily hold the full complement of swisstopo boundaries as a geojson layer.

Привет сообществу OpenStreetMap!

Не знаю, будет кто-то читать эту запись или нет, но попробовать написать в дневник — очень интересный опыт. Нигде не слышал, что здесь есть такой функционал, а раз имеется 😊 — нужно пользоваться.

В этой записи я хотел бы поделиться своим первым опытом. По сути, этот текст будет «водой» и не принесет много полезной информации.

Как я стал мапером

Однажды мне потребовалось найти адрес в моем поселке, но каково же было мое удивление, когда выяснилось, что никаких адресов нет (по крайней мере, точных). Мало того, отсутствовали и ключевые объекты инфраструктуры.

Недолго думая, я начал искать информацию о том, как редактируют карты, и наткнулся на «Народную карту» Яндекса. Какое-то время я вносил правки там: добавил и исправил достаточно много объектов. Процесс показался, как ни странно, очень интересным и «залипательным» — так у меня появилось хобби в картографии.

Знакомство с OSM

О проекте OSM я знаю относительно давно, но особого внимания ему не уделял. Как я сейчас понимаю — очень зря! Такого классного редактора, как iD, я еще не видел. Инструменты настолько простые, что ты не работаешь ими, а получаешь наслаждение, если так можно выразиться.

Про документацию я вообще молчу! Она бесподобна. Снимаю шляпу перед людьми, которые переводили её на русский язык. С ней очень удобно работать: один клик — и ты уже читаешь именно то, что тебе надо, а не тонну неструктурированной и разбросанной информации.

Итоги

Как проходит одобрение правок и когда они появятся на основной карте — я пока не знаю, да на данном этапе это и не важно. Надеюсь, что быстро.

В общем, очень жалею, что раньше не редактировал здесь и не уделял проекту внимания. Проект классный, документация — моё почтение, инструменты на высоте!

Всем спасибо за внимание, всем пока!

 

Part of the rationale for getting a folding bike was that I could avoid climbs by putting it in the boot of the car and heading out for flat rides in areas that are less hilly than our immediate surroundings. The plan has worked, but after a few months I felt ready for something a bit more demanding. At the weekend I tried routes around Wooler, but the weather wasn't great and that turned into a short, cold ride with showers of rain and hail. 

Three days later the weather today was a big improvement. So I headed back to Wooler to attempt something more ambitious. I began by revisiting Weetwood and Fowberry. Instead of turning back I then headed for Chatton. Then on to Chillingham, where I had a break outside St Peter's Church. I continued south, almost as far as Old Bewick. Then back via Lilburn Tower. I wanted to avoid riding along the busy A697 so I had intended to head north through Haugh Head. However, I missed the turning. A short stretch along the A697 wasn't as bad as I feared, then I was back on quiet country lanes and the Pennine Cycleway through North Middleton, and Coldgate Mill.

Highlights of the ride were the quiet roads, a variety of fords and old bridges, and great views across lovely countryside. The hedges haven't started to blossom yet, but spring is definitely in the air. I couldn't have asked for better weather. I was looking for something a bit more demanding than usual, and this certainly wasn't as flat as I've been used to. But for a ride of just over twenty miles, it felt more demanding than I intended. I'm not ashamed of getting off and pushing. But really, a bit more practice across similar terrain  is called for. 

Прогулка с StreetComplete — добавил 300+ объектов в Минске. Приятно видеть, как карта наполняется деталями!😊

3 March 2026: Writing this at a Missing Maps “London” remote meeting, realizing that I’d never written a OSM diary about the research I did within the ecosystem. I’m so late! But I’d love to still write this down. This placeholder is cross-linked with my blog.

From October 2020 to June 2021, I conducted ethnographic research within the (humanitarian) OpenStreetMap universe, trying to understand how communities, crises, and corporations came together on OSM. My thesis was ultimately about how humanitarian technologies like open source maps are used and created in response to crisis, and the convoluted mix of humanitarian values, corporate interests, and international networks that intersect on the OpenStreetMap platform.

The project and community is incredibly complex, a confluence of humanitarian actors, technology workers, and crowdsourced labor. My initial questions focused on why people contribute to open-source platforms like OSM (and Wikipedia for that matter), but they later evolved into what role humanitarian mapping plays within the wider ecosystem of geospatial and mapping technologies it is a part of.

Increasingly, as this was just before the wave of new AI technologies, I found that OSM data was being used in order to train AI systems like those used for road detection, etc.

While the written work is in the process of publication (eventually!), there are a number of public videos that share some of my public-facing findings on the subject.

Crisis Maps, Community, and Corporations (an Anthropologist’s perspective)

This talk shares my initial findings from this period, drawing from interviews and studies of political economy, science and technology studies, and humanitarianism. Social science methods might help us to better understand this changing period of OSM and HOT history, as it heads into the future.

Mapping crises, communities and capitalism on OpenStreetMap: situating humanitarian mapping in the (open source) mapping supply chain

This presentation focused on humanitarian mapping through qualitative study, and summarised the final findings from my MA. It aimed to scaffold a notion of the “open source mapping supply chain”, situating both humanitarian mapping and OpenStreetMap itself within a larger ecosystem of commercial, humanitarian, open source, government, and other actors in developing geospatial-related technologies.

I started a new wiki talk page discussion on the conflicting/controversial usage of the wetland=tidalflat tag regarding implied and explicit surface types:

• Change of definition to mainly encompass mud and discourage use on sand flats

Also posted a comment on positive related changes being worked on by the carto team:

• openstreetmap-carto PR: #5067 Use dedicated style for landcover polygons over water

Hoy comienzo la plenitud de mi sinceridad

This FAQ is continuously being improved and expanded and may change at any time.

Q: Why does SOSM oppose the MODI bill, isn’t improving the efficiency of our mobility infrastructure a good thing?

A: We have always supported making more mobility data available and suggested that it is one of the missing pieces to creating viable competing services to google and Apple. We are simply opposed to regulation that couples access to that data to use of the navigation data of a single market player.

Q: What is Verkehrsnetz Schweiz and why is it a problem?

A: Update March 2026

For transparency sake the full previous version of this FAQ item can be found below.

swisstopo currently positions Verkehrsnetz Schweiz as a set of tools that allows building more complete datasets from their routable base transport data swissTNE Base in an automated fashion and allowing third parties to incorporate their ids in a so generated dataset.

This is technically an interesting approach, particularly compared to the monolithic design used in Austria and that is now emphasised in swisstopos marketing. However this does not really address our concerns that use of MODI is legally closely tied to the use of swissTNE Base as the reference dataset and the proposed law does not mandate any other way of access.

It should be clear that while swisstopo has not announced that it will publish an enriched version of swissTNE including the additional data (POIs, buildings etc) required for a full navigation product, it is building the tools to do exactly that. In the swisstopo app navigation support is already available and swisstopo is clearly already competing in this space.

The situation is similar to if google claimed that google maps is just the internal tools they use to build the google maps service, in a certain fashion true, but at the same time very misleading.

Previous version:

Verkehrsnetz Schweiz is swisstopos new product entry in to the navigation data market.

Verkehrsnetz CH is a completely conventional set of geodata suitable for navigation and similar purposes just like the products Tomtom, Here, apple, google, OpenStreetMap and others have been creating since decades. As any of these players will attest to, aggregating data from multiple sources, applying quality checks, arranging for updates and so on is the name of the game, and not something that is unique to swisstopos product.

The navigation data market is healthy with many competitors to choose from even though most consumers use products from google, a further player with a “me too” product is likely not a concern for any of the other players or us.

Matter of fact we are a bit tickled by the fact that OSM it important enough that one of the key competitive features of Verkehrsnetz CH is that it will be available in an OSM compatible format so that swisstopo it can easily use it to push out OpenStreetMap of existing applications.

Realistically the market for such a product in isolation is small, however legally and technically coupling the access to the mobility data infrastructure to use of Verkehrsnetz Schweiz changes this equation and will tilt the playing field substantially to the advantage of swisstopo.

Q: Do you have an example why the coupling of MODI access to Verkehrsnetz Schweiz would be anti-competitive?

A: Update March 2026

swisstopo has removed mentions of producing an OSM compatible dataset as a core requirement of Verkehrsnetz CH.

Consider the following scenario:

You are running a, hypothetical, e-bike rental service, and the bikes have OSM-based navigation devices. You want to use the federal government’s mobility data (MODI) to improve navigation, e.g., to avoid closures or traffic jams. As required, you must use the Verkehrsnetz CH to retrieve the relevant data. In other words, you either have to make additional efforts to continue using original OSM in your navigation systems, or you can simply get data from swisstopo in an OSM-compatible format and frictionlessly access MODI.

And if you want to (automatically) make the usage status of your bike docks available to everyone, since multimodal navigation systems can then, for example, direct users to a dock that still has bikes, you will of course also have to use Verkehrsnetz CH data to upload the data to MODI, even if you otherwise use OSM to manage your locations.

If the access to the MODI data were designed to be both technically and legally provider-neutral, no one would be favoured. As planned, regardless of if we provide workarounds for access in the future or not, there will always be additional friction and uncertainty as to whether it will work correctly and users will gyrate to using Verkehrsnetz CH because it is “guaranteed” to work.

Q: This is Switzerland, shouldn’t have any disagreements on the bill been worked out before it got to this stage?

A: Yes you would have expected as one of the few organisations that are directly impacted by the regulation we would have been addressed early. However not only were we not invited to the consultation phase and had to, after we had found out, submit our statement within a day, our concerns have not been taken seriously by any of the bodies we have contacted.

It has to be said that we are arguing a fine techno-legal point here and the importance may be lost on many. Not to mention that we are small voice compared to the many swisstopo receptions, handouts to consultants and not to forget the cantons expecting free money from the federation.

Q: Won’t this rein google in and provide more opportunity for small businesses to provide services?

A: swisstopo has naturally played the bad big tech card in promoting Verkehrsnetz Schweiz a quote from their “Faktenblatt Verkehrsnetz CH” promotional material:

Kartendienste wie OpenStreetMap oder Google verfügen über umfassende Verkehrsdaten. Diese sind jedoch nicht in jeder Hinsicht frei zugänglich oder sind mit kommerziellen Interessen verbunden, z.B. werden beworbene Informationen bevorzugt angezeigt. Zudem ist nicht immer transparent, woher die Daten kommen.

The reference to OpenStreetMap was removed after intervention by us, it however nicely illustrates the mind frame of the authors.

But naturally companies like google and apple are unlikely to be affected at all as they do not provide direct navigation data access and can, if they even want to use the MODI data over what they already have access to, hide this behind their APIs and likely will save money in the process.

A look over the border to Austria where more than a decade ago a similar project was passed in to law, doesn’t show any less use of google, it does show a distinct lack of products that use OpenStreetMap or other sources and instead a de-facto monopoly for certain sectors that is based around the GIP (Verkehrsnetz CH equivalent) and the VAO (semi-private MODI equivalent). It should be noted that the VAO services are not free, which is the likely longer term MODI scenario too.

Q: Where can I find the text of the bill and related material?

A: Documentation of the MODIG bill from the federal council

Q: Isn’t this all open data and therefore not a problem?

A: Most parts of Verkehrsnetz CH and MODI are expected to be available as open data. However besides that not guaranteeing that the terms will be compatible with OSMs distribution licence, there are carve outs that might actually require update commitments and similar that would not be possible to fulfil in an OSM context, see fossgis.de Stellungnahme zum Mobilitätsdatengesetz for a similar issue with German regulation.

More importantly, while the promise of open data is that it will fuel innovation and create more economic activity, that would require the publishing entity to not itself corner the market with its own products. There is no legal requirement in Switzerland for this, and as swisstopo shows, the main effect of allowing it to publish data on open terms now is that it is under substantially less pressure to justify its offerings on economic terms. “it’s open data” has literally become the universal excuse for all its activities.

As mentioned above there is some hope that we will be able to use the published data to shoehorn MODI compatibility onto an OSM data distribution if the legislator decides not to require a vendor neutral access. But by its very nature this will be a 2nd class, high friction solution.

It really shouldn’t matter if you are building your app or service on Tomtom, Here, google, apple, OSM or swisstopo data and services, the technology is there to make MODI vendor agnostic, what is missing is the political will to require it.

Q: What are SOSMs concrete demands?

A: SOSM demands that the MODI components Verkehrsnetz CH and NADIM are decoupled and that the bill requires geodata-provider agnostic access to NADIM.

We further suggest that the establishment of Verkehrsnetz CH is moved to a separate bill to allow an independent evaluation and decision on the merits of the undertaking.

Q: Doesn’t the bill require that the MODI is independent of market players?

A: Art. 6 a. of the MODI bill stipulates “Die MODI ist von den Marktakteuren unabhängig” (MODI is independent of market participants). However it then completely ignores that by any definition, including its own, swisstopo is such a market participant, and that Verkehrsnetz CH is a product that swisstopo is actively promoting on the market.

Not only has swisstopo positioned itself as a competitor to other mapping service providers in its promotional material for Verkehrsnetz CH, it provides map services to web developers in competition to other players, and even offers products to end users in competition to other market participants. See for example https://www.swisstopo.admin.ch/de/swisstopo-app

Every map tells a story. Some stories are drawn with roads and buildings. Others are written through people, voices, and lived experiences. This is the story of how mapping became a bridge between climate vulnerability and community resilience in the heart of Dhaka. Under the Climate Resilience Fellowship, proudly supported by OpenMappingHub Asia Pacific, our Team 8 embarked on a journey called “Healthy Homes, Safer Futures.” Our goal was simple yet powerful: to strengthen climate awareness and resilience among vulnerable communities living in Dhaka’s urban informal settlements.

Where It All Began

In early May, all ten fellowship teams gathered in Dhaka, sharing ideas and aspirations for climate action. We were two coordinators: Mohammad Azharul Islam — Oceanographer and GIS Analyst at the Center for Geoservice and Research Ahsan Habib Saimon — Capacity Building Officer at Christian Commission for Development in Bangladesh Together, they envisioned a project that would connect data, digital tools, and grassroots knowledge to create safer living environments.

Walking Through Vulnerability

On 22nd August, our team stepped into the narrow alleys of Mirpur’s slum settlements. Climate change here is not an abstract concept it is visible in waterlogged pathways, overheated tin roofs, poor sanitation, and fragile housing structures. After consultations and careful observation, we selected Duaripara Slum as our core study area. Over the following days, we collected data from more than 400 households, representing over 8,200 people. But beyond the numbers were conversations, stories of survival, adaptation, and hope. Community leaders shared their concerns about flooding, health risks, and extreme heat. Residents spoke about their struggles but also about their determination. Mapping was no longer just about coordinates. It became about understanding lived realities.

Building Knowledge, Building Confidence

On 24th August, we conducted our first capacity-building training with 20 community participants from Duaripara. We discussed: - Climate risks in urban slums - Health impacts of poor WASH practices - Climate-smart hygiene behaviors - The power of community-led solutions Through practical demonstrations and interactive discussions, participants began to see themselves not as victims of climate change but as agents of change. The energy in the room was transformative.

1st Training

The first training focused on climate resilience and community preparedness, and it was facilitated by M. Rezaul Karim from Dushtha Shasthya Kendra (DSK). With his extensive experience in community health and development, he guided participants through the realities of climate vulnerability in urban informal settlements like Duaripara. The session explored how flooding, extreme heat, poor drainage, and inadequate sanitation directly impact household health and safety. Through participatory discussions and practical examples, he emphasized locally adaptable solutions, safe water management, improved hygiene behavior, and collective preparedness strategies. His facilitation style encouraged open dialogue, allowing participants to connect climate concepts with their daily experiences and recognize their own role in strengthening resilience.

2nd Training

The second training centered on community mapping and digital data collection, led by Mohammad Azharul Islam from the Center for Geoservices and Research and an OpenMappingHub GURU under OpenMappingHub Asia Pacific. He introduced participants to open-source mapping tools, particularly KoboToolbox, and provided step-by-step hands-on guidance on using smartphones for survey design and data submission. Participants learned how to collect GPS points, structure questionnaires, ensure data accuracy, and maintain ethical standards such as informed consent. The training transformed digital tools from unfamiliar technology into accessible instruments for community empowerment, helping residents understand how mapping can make their challenges visible and actionable.

Digital Skills for Local Change

On 5th September, we introduced participants to KoboToolbox, an open-source digital platform for field data collection. For many trainees, this was their first time using digital survey tools on smartphones. Curiosity quickly turned into excitement as they: - Learned to design simple surveys - Practiced submitting digital forms - Understood how community data can influence planning Technology, once distant and unfamiliar, became accessible and empowering. The following day, they took these skills into the field, collecting household data, speaking with neighbors, and documenting vulnerabilities. It was a powerful moment: community members mapping their own community.

Reflection and Impact

On 24th September, we gathered once more to reflect. Participants shared how they had: - Improved hygiene practices at home - Discussed preparedness measures with neighbors - Increased awareness about climate risks - Built confidence in using digital tools - Small behavioral shifts were already visible in cleaner surroundings, better conversations around sanitation, and stronger collective engagement.

“Healthy Homes, Safer Futures” was no longer just a fellowship project. It had become a shared movement.

You can learn more about our project through our website: Healthy Homes, Safer Future Also watch this video: Healthy Homes, Safer Future (YouTube)

Nimman Road, Chiang Mai(Thailand) is a well-mapped, high-traffic corridor. It scores a B on network density: good intersection frequency, reasonable block lengths. But it scores near zero on crossing coverage because there are no highway=crossing nodes tagged within the 800m analysis radius. The street has physical crossings. They’re just invisible to any tool that relies on OSM, which is most tools.

That’s what SafeStreets shows: not just a score, but which data gap is causing it.

What SafeStreets is?

A free tool that scores the walkability and pedestrian safety of any street address globally(graded out of 10). No account required, 190+ countries. OSM is the backbone, and the only data source that works everywhere.

How OSM powers it, three functions?

1. Address geocoding via Nominatim Every analysis starts here, with a ~50km geolocation bias for local lookups while preserving global search. No proprietary geocoding.
2. Street infrastructure scoring via Overpass API (800m radius) We query within an 800m circle for:

highway=crossing nodes → crossing safety footway=sidewalk and highway=footway ways → sidewalk coverage highway=primary/secondary/tertiary/residential/living_street → network topology Way attributes: lanes, width, surface, maxspeed, lit, sidewalk, cycleway

Four sub-metrics from this graph:

Intersection density (nodes with degree >= 3 per km2) Average block length (total street length / intersection count) Network density (total street km per km2) Dead-end ratio (degree-1 nodes penalize walkability)

These combine into the Network Design component (35% of the total score). 3. 15-minute city scoring via Overpass API (1,200m radius) Service reachability on foot, scored by nearest distance (<=400m = 100pts, <=800m = 75pts, <=1,200m = 50pts):

Grocery: shop=supermarket/convenience/greengrocer Healthcare: amenity=pharmacy/clinic/hospital Education: amenity=school/kindergarten/library Recreation: leisure=park/playground/sports_centre Transit: public_transport=stop_position/platform, highway=bus_stop, railway=station/tram_stop/subway_entrance Dining: amenity=restaurant/cafe/fast_food

This feeds the Accessibility component (25% of total score) and a separate 15-Minute City Score.

1. Map rendering via Leaflet + OSM tiles Scored infrastructure overlaid on OSM base tiles. What’s missing, and what would help We’re explicit in the UI about what we can and can’t measure:

✓ Crossings exist and where ✓ Lit / not lit (where tagged) ✓ Service accessibility via POIs ✗ Pavement condition ✗ Sidewalk obstructions (vendors, parked bikes) ✗ Crossing quality (marked, signalled, raised), sparse outside Europe/North America

The most useful contributions for Southeast Asian cities: sidewalk=, crossing=marked/uncontrolled/traffic_signals, and lit= on way segments. These tags directly change scores for real addresses. Nimman Road would improve immediately with accurate crossing nodes added.

The project

SafeStreets is live at safestreets.streetsandcommons.com. Built by Streets & Commons, a civic tech initiative based out SEA If you’re mapping in SE Asia and want to see a specific street analysed, or if you work on pedestrian tagging schema, I’d love to hear from you in the comments

Portal North Bridge construction and study documents

https://archive.org/details/@isstatenisland/lists/7/portal-bridge-documents?sort=date

I gathered and uploaded documents relating to the Portal Bridge capacity enhancement project and its replacement, Portal North Bridge. The documents (except the Amtrak bulletins) come from NJDEP’s DocMiner. The Amtrak bulletins were retrieved by FOIA request. It appears the FEIS disappeared off the web many years ago.

The original plans intended to build a 3-track fixed span to the north. The documents from 2019 and later depict the currently chosen plan, the two-track fixed structure to the north. The south structure is not funded.

https://archive.org/details/portal-bridge-project-feis-final-4f-october-2008 Portal Bridge Capacity Enhancement Project - Final Environmental Impact Statement and Final Section 4(f) Evaluation, October 2008

https://archive.org/details/portal-bridge-project-feis-final-4f-appendix-vol1-october-2008 Portal Bridge Capacity Enhancement Project - Final Environmental Impact Statement and Final Section 4(f) Evaluation, October 2008: Appendix Volume 1

https://archive.org/details/portal-bridge-project-feis-final-4f-appendix-vol2-october-2008 Portal Bridge Capacity Enhancement Project - Final Environmental Impact Statement and Final Section 4(f) Evaluation, October 2008: Appendix Volume 2

https://archive.org/details/portal-bridge-project-relocation-study-january-2010 Portal Bridge Capacity Enhancement Project - Relocation Feasibility Study, January 2010

https://archive.org/details/portal-bridge-project-gc02-construction-plan-sheets-2019 Portal Bridge Capacity Enhancement GC.02 Contract - Construction Plan Sheets, August 15th 2019

https://archive.org/details/portal-bridge-project-environmental-impact-sheets-2020-2025 Portal Bridge Capacity Enhancement Project - Environmental Impact Sheets, January 2020 with November 2025 modifications

https://archive.org/details/AMTK-NEC-employee-timetable-supplemental-bulletin-20260214-NYW1-25-b/mode/2up Amtrak - Northeast Corridor Employee Timetable Supplemental Bulletin 2026-02-14, NYW1-25-b

https://archive.org/details/AMTK-NEC-employee-timetable-supplemental-bulletin-20251213-NYW1-23-b Amtrak - Northeast Corridor Employee Timetable Supplemental Bulletin 2025-12-13, NYW1-23-b

Всем привет! Я GISTracer из Минска.

По базовому образованию — технолог-машиностроение. Работа с чертежами, допусками и технической документацией выработала главные качества: внимательность, усидчивость и привычку к точности. Именно они привели меня в OpenStreetMap.

Сейчас вхожу в тему профессиональной картографии и ГИС. Интересуюсь качественной векторизацией по спутниковым снимкам, работой в JOSM и постепенно наполняю карту полезными деталями.

Понимаю, что хорошая карта — это тысячи мелких правок, сделанных с вниманием. Этим и планирую заниматься.

Буду рад обратной связи и советам от опытных участников. Всем качественных тегов и чистых подложек!

1. 你驾车，Android Auto上使用OSM导航软件
2. 副驾不能晕车，放个笔记本在大腿上，在iD上连接两点，用编辑器把缺失的路现画上
3. 你在导航上规划路线，看哪里特别绕
4. 副驾对着卫星图画缺少的路
5. 你开车，副驾补全车道和路线信息