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F4 es uno de los pocos visores de OpenStreetMap que ha estado en servicio ofreciendo renderizado en 3D por muchos años. Han habido otros servicios, pero cuando se muestra F4 cualquier persona se descresta. He empezado a mapear en 3D, y muchas de las grandes contribuciones, principalmente en Denver, en este ámbito han sido de chachafish. Lo quise contactar para obtener algunos tipos de un experto, pero dejó de mapear desde 2020 (en plena pandemia :( ), entonces me tocó buscar otras opciones.

En el wiki, en communities, hay información dispersa, pero no muestra todas las posibilidades que tiene esta herramienta. Entonces, decidí indagar en la misma página de F4 map, y encontré 2 páginas muy interesantes: render y changelog. En ellas se describe en cierto desorden todo lo que puede hacer esta herramienta.

Entonces, decidí darle un orden, extraer las etiquetas que usa y ahí tener una mejor idea de cómo debo hacer 3D mapping. Fue ahí cuando recordé Taginfo, y decidí listar este visor en este directorio, por lo que creé una entrada: https://github.com/angoca/f4demo-in-taginfo/blob/main/taginfo.json.

Además de lo anterior, es necesario manejar los colores para que se visualice más cercano a la realidad. Para eso se puede usar esta guía de nombres de colores.

Esperemos que esto sea de ayuda para que más personas se aventuren en el mapeo 3D, sobretodo teniendo un poquito más de documentación.

Yo comencé con un pequeño ejercicio en el norte de Bogotá, y estoy muy contento con el resultado del Centro Comercial Plaza Norte:

• Mapa 3D.
• OSM.
• Mapa de emergencias.
• Interno - Otro interno.

For years, an issue with Kurdish language, Arabic script, and OpenStreetMap tiles has been on my radar. In 2023 I got OSM to update Noto fonts on the tile server, but Google has moved their latest changes to individual repos.

I’m continuing to workshop a PR for that.. but in the meantime, I thought to check if OSM needs more of the language-specific Noto fonts. Back in spring 2019 I did a mini survey of where Unicode blocks were used around the OSM world.

Today I added Python scripts to check Planet PBF files (specifically name and alt_name tags on nodes) and find usage across Unicode blocks.

There are names with Latin alphabet and frequently associated characters (superscripts and subscripts, dingbats, diacritics, IPA, half-width, old italic, runic, spacing modifiers, punctuation, emoticons/emoji, and symbols from math, music, currency, and maps).

• Africa has: TIFINAGH, ARABIC (supplements and presentation forms), CYRILLIC, ETHIOPIC, NKO, HEBREW, CJK, HANGUL, and GREEK.

• Asia has: CYRILLIC, GREEK, HEBREW, ARABIC, SYRIAC, COPTIC, ETHIOPIC, BALINESE, JAVANESE, CJK + YI + BOPOMOFO + KANGXI, HANGUL, MONGOLIAN, TIBETAN, THAI, MYANMAR, LAO, KHMER, ARMENIAN, GEORGIAN, THAANA, SINHALA, TAMIL, ORIYA, BENGALI, GURMUKHI, GUJARATI, DEVANAGARI, KANNADA, MALAYALAM, OL_CHIKI, and TELUGU.

For the Americas, OSM already includes fonts for Cherokee and Canadian Aboriginal Symbols.
Those two scripts and OGHAM, TAGBANWA, and BAMUM were misused in Asia. The instance of TAGALOG script was a little uncertain. I removed an Apple logo because it’s from the Private Use Area.

The current font download script is pretty good, and includes additional fonts (Adlam and Tai Viet) which aren’t actively used.

The one alphabet which I will recommend adding is Glagolitic. Stone letters have appeared in several locations around Baška, Croatia (street view , street view 2), but also get misused on tourist site binoculars (assumedly using Ⰹ to represent its shape) and I’d previously seen it in the Canary Islands.

I am considering setting up a script checking weekly edit downloads for common errors and suspicious Unicode blocks.

so the beach town is seeing growth again, after the primary developers went bust in 2007/8. A large amount of blank land between the shops and the harbour has been cleared, and given asphalt roads, concrete footpaths, and brackish ponds for the mosquitoes to grow in! I hope the new holiday home owners like mosquitoes!

My GPS accuracy is not great and my note taking while walking is worse; but I’ve drawn some new ways on the new footpaths; and verified some of the existing paths from Kenwood Drive to Waimarie Ave are still approximately where my GPS says they are. Good fun.

Need to go back with a laptop next summer to add/tweak more. Hopefully LINZ has updated by then to provide even better coverage

The State of the Map Asia 2024 conference wasn’t held in a main travelers’ hub like Thailand but rather chose a much, not that well-known country Bangladesh, and its previously unsettled political situation, which ended with the Prime Minster fleeing to India. Summarizing all these factors might discourage most people from visiting this country, ended up most of the attendees are domestic, and plus someone like me who is a foreigner is lucky enough to obtain a VISA to pay a visit.

Bangladesh is a young country, during the conference we saw many attendees were students, who might help those international aid projects to gather map data. We can see teachers bring their students to attend the conference. And there are also various student clubs, like all Youthmappers in Bangladesh, publishing their project results. One day we might see when the country is prosperous, and students grown up, there is a chance that they will map shops and buildings in the city where they live.

I want to write something about the general participant situation here in the Asia Pacific area. In developed countries like Taiwan, there are individuals who launch interest groups to map specific map features or netizens with enough motive to contribute to OpenStreetMap project. There are other countries that rely on aid projects to map local map data, and sometimes there are sone who will map modern map features. I have heard a talk about solar pannels in Dahka.

The State of the Map Asia splits its session into quite strange 10-minute parts. I accidentally submitted two talks, and did not get rejected. I had to give a talk on the first and second day, one I introduced the community in Taiwan, and the other day I introduced some interesting projects hosted by individual mappers.

I almost can’t fly into Dahka due to the immigration office having some questions about my visit. Finally, the host came to the airport to rescue me and took the connecting flight to Cox’s Bazar. Besides the conference, I had a walk every day on the beach, listening to the sound of the waves of the Indian Ocean. When I recalled the memory of my Bangladesh trip, there was a challenge to get a VISA on arrival. I take the chance to visit Bangladesh when attending a conference and add Bangladesh to the list of South Asia countries.

這改 State of the Map Asia 2024 大會，毋是佇逐家愛去𨑨迌的旅遊勝地泰國舉行，顛倒是佇民風較祕思，國家較封閉的孟加拉舉行。而且佇落尾的時，確實有人簽證問題無法度入境到位會場。閣加添孟加拉政局無穩定，進前總理流亡，共頭前講的原因加加起來，予世界各國的人無想欲來。這个大會會當講是孟加拉人為主，極加加添我這款會當入境的外國人。

孟加拉是少年人的國家，一般看著的參與者是學生，幫贊國際援助計畫累積基礎的地理圖資。閣有參與的老師𤆬學生，有各種的社團，比喻講孟加拉各大學的 YouthMappers 組織攏有參與，發表𪜶參與的計畫。應該是有一工社會發達，一陣學生較有歲，相信下開始畫四箍圍的店頭佮都市的建築。

閣來講起亞太的開放地圖的參與情形，除了社會經濟狀況允準以外，會當有個人發起的興趣小組佮有貢獻動機的網路鄉民以外，足濟是用援助計畫的資源來進行基礎圖資的繪製，順紲執行較現代的議題，親像講綠能相關的，比喻講達卡的日頭能枋的分佈。

演講的部份，𪜶用較奇妙的十分鐘為一个單位進行，家己無細膩投兩份演講，著勉強共平常時紹介 OpenStreetMap 的簡報拆做兩份，第一工紹介台灣的社群，進行的計畫佮未來展望，第二天就是講個別台灣社群成員的計畫。

當時欲入境孟加拉拄著挑戰，予移民官擋咧留話，愛主辦單位出面解釋，才予入境。落尾到位 Cox’s Bazar，除了佇會場發表，嘛聽捌人的經驗，體驗孟加拉旅遊勝地，會當講是孟加拉的墾丁𨑨迌踅踅。我逐家會當到海沙埔散步，體驗印度洋的海風佮海波浪。這馬回想一逝旅行，對孟加拉落地簽申請的難題，趁大會佇孟加拉舉辦的機會來到孟加拉，解鎖一个南亞國家的成就。

這次 State of the Map Asia 2024 並非在旅遊聖地泰國舉行，而是比較封閉的孟加拉，光是簽證就很容易搞死人。而在最後關頭，的確是有很多人就無法到場，簽證沒過無法入境。再加上前陣子孟加拉政局動盪，總理流亡，綜合以上種種因素，導致各國的人不大前往參與。孟加拉人為大宗的大會，再加上能有辦法進來的外國人

在會場觀察參者的人好有活力，很多援助計畫在協助積累當地基礎的地理圖資。另外參與的人口年輕，像是老師帶著學生參與，各種年輕團體組團，例如孟加拉各大學的 YouthMapper 組織都有參與，發表相關的計畫。當社會漸漸發達，大家年紀變年長，相信應該會有人轉為畫生活活動範圍的商家與都市地帶的建築。

而回到亞太這邊的開放街圖參與狀況，除了社會經濟情況允許而能以自發的興趣小組與有貢獻動機的網路鄉民之外，很多是用援助計畫的資源從事基礎圖資的繪製，順便去進行比較是近代的議題，像是跟綠能相關的，如達卡的太陽能板分佈的繪製

演講部分，他們用蠻奇特的十分鐘時間為單位進行，而自己不小心投了兩份演講，就硬著頭皮講了兩場，基本上是自己25+5演講拆一半的內容，各自在兩場演講。第一天談台灣社群，進行的計畫與未來展望，而第二天談個別的社群成員常在進行的計畫。

儘管移民官還有機場設施不是那麼友善，但我順利到達 Cox’s Bazar，除了在會場發表還有聽別人的經驗分享之外，也趁機到這個孟加拉的渡假聖地遊覽，每天到沙灘走走，體驗印度洋的浪與風。回想這一切，孟加拉簽證難申請，趁這次大會在孟加拉，解鎖到這一南亞國家遊歷的成就。

See pt1 of this series here.

See pt2 of this series here.

See pt3 of this series here.

How Does This Relate To OSM Again?

If you have been following the articles listed above, you will know the Field Mapping Tasking Manager (FMTM) is a tool developed by HOTOSM to improve the quality of field verified data associated with geometries.

In the OSM world, this means adding and improving tags for OSM geometries.

A key element of this work flow is conflation of newly collected data with existing data in OSM. Some preliminary work was done on this, but for now the team decided to pivot and focus entirely on improving the usability of FMTM from the perspective of mappers.

The conflation work will be continued further down the line.

Currently, Rob Savoye is also continuing some work in parallel for conflation of roads in the USA, with OSMUS’s osm-merge project.

The roadmap for FMTM can be found here.

Easier Field Mapping

Since release 2024.5.0, we have be focusing on what we have dubbed the ‘Mapper Frontend’.

Our primary goals:

• Mapping should be as intuitive as possible for users, requiring minimal training or existing knowledge (with prompts).

• The application should be fast and responsive, tailored to field mapping needs.

• Data should load real-time, significantly improving the collaborative team experience. Joe wants to know where Jim is mapping currently, to avoid overlap.

• A secondary goal is the potential to package it up in a mobile app wrapper, allowing for easy distribution via mobile app stores.

Mapped Buildings Should Turn Green

• This was one of our first feature requests, and most important from the mapper perspective.
• When a feature is mapped, it should turn green on the map to indicate that it’s done!
• We have implemented this feature in the new mapper app, with further improvements to real-time sync of mapping status coming in the next release too.

Future Work

So, Sam, when can we use FMTM on iOS devices I hear you cry!

This is long overdue, and an essential feature to increase the reach of FMTM.

Over the next two / three months we are working on this as part of a larger push to integrate ODK Web Forms into FMTM.

Once complete, the requirement to install and switch to the ODK Collect app for survey data collection will no longer be present.

Instead, we will have a full field mapping solution built into a single streamlined web application!

Follow progress here, where this is part of the requirement for an ongoing mapping project of informal settlements in Brazil 🎉

Ongoing Campaigns

A project mapping settlements in the Tokha municipality of Nepal is about to commence!

We have also recently had projects mapping informal settlements in Ghana and Tanzania.

See the FMTM timeline with some additional projects listed here.

A Question To Our Users

The name ‘Field Mapping Tasking Manager’ (FMTM) was created quickly, showing an obvious link to the Tasking Manager.

However, we realise it’s probably not the most catchy name, and often creates confusion with the FMTM acronym.

Two possible suggestions have been made for a name change:

• Field-TM (consistent with other tools, e.g. Drone-TM, references TM).
• FieldTasker (describes the tool better, but does not reference TM).

Please comment with name suggestions, feedback, or other ideas!

Future Posts

I plan to make future posts about developments, technical deep dives, and usage of FMTM’s features.

If you liked this article and want to support the development of FMTM, please read the contributing guide here.

Show some love by adding a ⭐ to the FMTM Git Repo.

See you next time!

Had to move the summit as it was in a random place. It’s really cool up there.

Youth Mappers University of Nairobi chapter

El mapeo de interiores no es muy popular ya que requiere conocimientos de la distribución de los espacios dentro de un edificio. Normalmente esto se hace por medio de un plano, que puede ser el de evacuación. Aunque aquí empieza el problema de permisos de uso de datos para mapear en OpenStreetMap.

En Colombia estamos comenzando esta labor, pero quise listar lo que se ha hecho en Latam, y reconocer a los mapeadores:

• Colombia - Catedral Primada, Bogotá - chachafish.
• Colombia - Centro Comercial Plaza Norte, Bogotá - Andrés Gómez (yo).
• Colombia - Sena en La Rosita y Colegio Nacional Universitario Histórico, Velez, Santander - Germán Cruz.
• Ecuador - Quicentro Shopping, Quito - chachafish
• Perú - Jockey Plaza, Lima - chachafish.
• Perú - Aeropuerto Internacional Jorge Chávez, Lima - Diego Sanguinetti.
• Chile - Aeropuerto Diego Aracena, Iquique - est_4391
• Chile - Aeropuerto El Lao, Calama - .
• Chile - Universidad Católina del Norte, Coquimbo -
• Chile - Pontificia Universidad Católica de Chile, Santiago
• Argentina - Tulum - Almacén de de aromas, Bariloche -
• Argentina - Centro comercial Alto Avellaneda, Buenos Aires -
• Argentina - Museo Nacional de Bellas Artes, Buenos Aires -
• Argentina - Museo de artes plásticas ‘Eduardo Sivori’, Buenos Aires -
• Argentina - Edificio Técnico, Buenos Aires -
• Argentina - Universidad Nacional de la Matanza, Buenos Aires -
• Argentina - Universidad de Luján, Buenos Aires -
• Argentina - Terminal de Omnibus Mariano Moreno, Rosario -
• Argentina - Centro comercial Paso del Bosque, Rosario -
• Argentina - Aeropuerto Internacional de Rosario, Rosario -
• Argentina - Tierra Chica, Rosario -
• Argentina - Construcciones en Funes, Rosario -
• Argentina - Universidad Nacional de Córdoba, Córdoba -
• Venezuela - UCAB Guayana, Ciudad Guayana -
• Brasil - Universidades, Sobral -
• Brasil - North Shopping, Fortaleza -
• Brasil - IFRN, Natal -
• Brasil - Mangabeira Shopping, Joao Pessoa -
• Brasil - Caruaru Shopping, Caruaru -
• Brasil - Shopping Camará, Camaragibe -
• Brasil - Shopping Riomar, Recife -
• Brasil - Shopping Recife, Recife -
• Brasil - Shopping Guararapes, Recife -
• Brasil - Park Shopping, Brasilia -
• Brasil - Shopping Sinop, Sinop -
• Brasil - Uberlandia, Uberlandia -
• Brasil - Park shopping Sao Caetano, Sao Paulo -
• Brasil - Museo do Ipiranga, Sao Paulo -
• Brasil - Hemos Sabin Norte Shopping, Bluemenau -
• Brasil - Shopping Patio Chapeco, Chapeco -
• Panamá - Mulicentro, Panamá -
• Costa Rica - Paseo de las Flores, San José -
• México - Biblioteca Pública Central Estatal Francisco Cervantes, Queretaro -
• México - Catedral Metropolitana de la Ciudad de México, Ciudad de México -

• 들어가기에 앞서, LuxuryCoop님의 기존 제안을 보고 영감을 얻어 새로 올린 글입니다. 아래 글을 읽어보기에 앞서, 해당 글을 먼저 읽어보시는 것을 추천드립니다.

본 게시글에서는 지역의 label 태그를 위계별로 어떻게 사용하여야 할 지에 대하여 특히 주목하여 작성해 보았습니다. 기본적으로 OSM Wiki에 명시된 대로 각각의 place 태그에 대한 원론적인 위계에 주목하여 한국의 행정 구역 라벨 위계를 새로이 구성해 보았습니다.

공식 행정구역

광역자치단체

• place=province - 도(道), 특별시, 광역시, 특별자치도, 특별자치시에 사용

해당 태그는 일반적으로 주나 도 등 국가의 1차 행정구역을 나타낼 때 사용되며, 언급한 자치단체 모두 동일하게 대한민국의 1차 행정구역을 나타내므로 모두 ‘province’로 동일하게 표현하였습니다.

기초자치단체

• place=city - 시(市)
• place=county - 군(郡)

시와 군의 경우는 현행 유지되는 태그를 그대로 사용하였습니다.

• place=district - 특별시, 광역시 등의 자치구
• place=borough - 자치구가 아닌 구; 일반구

자치구의 경우 시, 군과 동등한 위계에 있는 기초자치단체로써, 지방 정부에 의해 자치적으로 운영되는 행정 구역이라는, OSM Wiki에 설명되어 있는 district과 그 사용례를 같이 한다는 점에 착안하여 district로 제안해 보았습니다.

일반구의 경우, 자치구와 마찬가지로 구(區)라는 명칭을 공유한다는 점은 존재하지만, 자치구와 달리 별도의 자치권이 없는 시(市) 내부의 하위 행정구역이라는 점을 고려할 때, 자치구와는 다른 태그를 이용하여 이를 표현해야 할 필요성이 있다고 생각하였습니다. 이러한 점을 고려할 때, 일반적으로 도시 ‘내부’의 구역임을 나타내는 ‘borough’ 태그를 사용하여 달리 표기하는 것을 제안하는 바입니다.

• place=subdistrict - 행정동

현행에서는 place=quarter가 동을 표현하는 데 사용되고 있지만, 해당 태그는 행정 구역을 명시한다기보다 도시 내 특정 구역을 태그하는 데 이용되는 점을 고려해보면, 거주 규모와는 별개로 행정구역임을 명확히 명시하는 subdistrict 태그를 이용하여 행정동을 표현하는 것이 좀 더 합리적이지 않을까 제안합니다. district와 연계하는 경우 구와 동의 계층이 명확해진다는 점도 존재합니다.

• ? - 법정동

‘법정동’의 경우는 일부 명칭을 제외하고는 지적 사무 외 행정적 사무와 실생활에서는 거의 쓰이지 않는다는 점을 고려할 때 지역적으로 잘 알려진 몇 법정동명을 제외하고는 법정동 relation의 name으로만 존치하고 label은 삭제합니다. 또한, 잘 알려진 몇 법정동명의 경우에는 규모에 따라suburb/quarter/neighbourhood로 구분하여 남기는 것을 제안합니다.

사실 법정동의 경우에는, 제가 제안하는 위계 구조 상에서 명확히 처리하기에는 애매한 바가 있어서, 혹시 이와 관련하여 좋은 의견 있으면 남겨주시면 감사하겠습니다.

• place=town - 읍(邑)/면(面)

기존 방식대로 읍, 면의 경우는 town으로 태그합니다. 소규모 면의 경우도 town으로 묶여 과대표기될 수 있다는 우려가 존재하기는 하나, 읍과 면 둘 다 동일한 행정 위계를 갖는다는 점을 고려하여 town으로 동일하게 태그합니다.

• place=village - 법정리(里)
• place=hamlet - 행정리/자연부락

현행대로 법정리의 경우 village로 표기하고, 법정리에서 행정 편의 상 더 잘게 쪼개진 행정리 혹은 자연부락의 경우 hamlet으로 표기합니다.

공식적인 행정구역이 아닌 지명

공식적인 행정구역에는 포함되지 않으나, 국지적 혹은 전국적으로 통용되는 지명에 대해서는 다음과 같은 태그 방법을 제안합니다. 각 place 태그 별 예시는 이해를 돕기 위한 단순 예시에 불과하다는 점 참고하시면 되겠습니다.

• place=suburb - 신도시, 신시가지, 혹은 택지지구 등의 대생활권 (예: 분당, 일산, 목동, 동탄 등)
• place=quarter - 중간 규모의 잘 알려진 상권, 혹은 중생활권 (예: 홍대, 성수, 서면 등)
• place=neighbourhood - 단일 거리 단위 상권, 근린 단위의 소생활권 등 (예: 목동 로데오거리, 해방촌 등)

도시의 내부 구역, 특히 생활권을 구분하는 데 있어 suburb>quarter>neighbourhood의 삼분법이 널리 활용된다는 점과, 행정동과는 무방하게 지역적 지명을 자유롭게 표기할 수 있다는 점에서 이 방식을 제안하였습니다.

• place=locality - 단순 자연지명 등

일반적인 거주 지역과는 외따로 떨어진 지역이나 단순 지명만 남은 지역 등을 표기할 때 사용합니다. 한두 가구 등을 표현할 때 place=isloated_dwelling을 사용할 수도 있겠지만, 한국에서 한두 가구 외따로 떨어진 지역의 지명을 일반적으로는 따로 부여하지 않는다는 점을 고려할 때는 굳이 이용할 필요가 있나? 싶긴 합니다.

해당 제안에 대한 다양한 의견, 피드백 환영합니다. 긴 글 읽어주셔서 감사합니다.

Нам нужно больше пользоваться сервисами для панорам, такими как Panoramax.

Яндекс это конечно отличный сервис, но он все же не самый дружелюбный к OSM’у, и права на его панорамы могут отозвать в любой момент. Призываю всех неравнодушных людей у которых есть файлы уличных панорам (или даже фотографии уличных объектов) зайти на https://panoramax.openstreetmap.fr/upload и загрузить их туда. У iD есть отдельный слой для панорам с этого сайта, и у людей которые картируют с него будет больше открытых данных с которых можно будет удобнее брать информацию.

Hey hey. We at the Yerevan Tree Map project were pulling to our database new nodes tagged as natural=tree for a while now, without actually pushing changes back. Now we are starting to do so. The OSM API is not quite straightforward, so we’re learning on the go. We have some 4k plus trees to push, we’ll be adding them in small batches. Later we’ll start pushing updates to existing tree nodes (e.g. when someone measures the tree or updates its state).

(English below, thanks to Deepl.com)

Ce post a été initialement publié ici.

Des données OSM en anglais, mais aussi en français, accessibles dans l’IFL pour les pays francophones du Sud

Des données OSM téléchargeables avec des attributs dans une langue autre que l’anglais, non pas avec un service web, mais une plateforme dédiée au partage de données et métadonnées géographiques, où l’on peut comprendre, voir, interroger, filtrer avant de télécharger : c’est ce que permet cette approche ETL (pour Extract, Transform, Load, soit en français « Extraction, Transformation et Chargement ») dans l’Infrastructure de Données Spatiales des Libres Géographes. Dans ce billet, je reviens sur le contexte et l’historique de ce projet personnel mené sur mon temps libre, avant d’expliquer l’approche technique mise en œuvre et, évidemment, comment accéder à ces données.

Le contexte : sortir du « english fits for all »

Si l’anglais domine l’écosystème OSM et reste la langue de référence du projet, plusieurs initiatives permettent aux non-anglophones de participer au projet et d’en bénéficier : un forum multilingue, la traduction du wiki et de certaines plateformes d’auto-apprentissage, des interfaces utilisateur traduites pour les applications et les éditeurs, y compris les préréglages d’étiquettes OSM.

Mais quelle que soit la technologie ou le service utilisé, les données OSM brutes, une fois téléchargées, restent exclusivement en anglais, et toute recherche ou filtrage des données OSM dans un logiciel SIG ne peut se faire que dans cette langue.

Ayant beaucoup formé à l’utilisation des données OSM en géomatique (notamment QGIS) depuis 2011, j’ai été vite confronté aux difficultés qu’ont pas mal de francophones non anglophones à exploiter les attributs des données OSM. Difficultés d’autant plus frustrantes, dans le cas des pays du Sud, qu’il s’agissait souvent des premières données détaillées disponibles sur leur territoire. Une barrière se levait, mais une autre lui succédait.

Cette contrainte a donc tendance ralentir le processus d’apprentissage pour les contributeurs OSM non anglophones, mais surtout, elle reste un obstacle à l’adoption par des publics extérieurs à la communauté OSM : par exemple, les services publics habitués à créer/distribuer/utiliser des données dans la langue officielle, ou l’une des langues officielles, de leur pays.

De fait, dès mes débuts dans OSM, j’ai toujours eu en tête de permettre l’utilisation des données OSM sans devoir forcément passer par l’anglais.

L’historique : un service qui aurait pu exister dès 2013

Malgré l’engouement né de la réponse communautaire au tremblement de terre à Haïti en janvier 2010, il restait difficile de promouvoir OSM auprès des géomaticiens humanitaires sans service permettant de récupérer la donnée OSM dans les formats SIG les plus courants sans devoir déployer une base PostgreSQL locale. Pour résumer, ces géomaticiens voulaient du shapefile.

Dans le cadre du projet HOT STM020 à Saint-Marc en Haïti financé par l’USAID, co-conçu et mis en œuvre avec Nicolas au printemps 2012, nous avions tenu à inclure dans le budget une ligne pour un « Data download point » qui allait devenir le HOT Exports (alors avec un « s » final), développé par GeoFabrik. L’année suivante, le projet CAP103, cette fois dans le nord et nord-est haïtiens, fut l’occasion de financer l’ajout de capacités de transformations de tags et de traductions au HOT Exports. L’un des rares visuels existants encore de cette v1 en atteste (en bas, dans les Expert functions) :

De fait, dès 2013, il aurait été possible de proposer une traduction des tags OSM en anglais dans une autre langue. Mais personne ne s’en est immédiatement saisi. Pour ma part, j’ai commencé à travailler dessus au printemps 2015 lors d’une résidence volontaire à Dakar et élaboré une première liste d’étiquettes OSM traduites en français et implémentées dans le HOT Exports. Certains étudiants et étudiantes en géomatique au Sénégal ont pu en bénéficier lors de sessions consacrées à l’usage des données OSM dans QGIS. Mais à la mi-2015 est sorti HOT Export v2, totalement réécrit, et toutes les capacités de transformations et traductions de tags y ont été supprimées. À nouveau, pas le choix, l’anglais ou rien.

J’ai repris le projet sur mon temps libre à partir du confinement de 2020, dans le but d’utiliser cette fois comme plateforme l’IFL, l’Infrastructure de Données Spatiales (IDS) Francophone Libre des Libres Géographes basée sur le projet geOrchestra, qui fournissait déjà des couches métiers dans le cadre de certains projets de l’association. J’ai aussi complété la traduction, couvrant désormais 1400 étiquettes liées aux clés OSM les plus courantes identifiées par taginfo, et en utilisant les traductions des Map features du wiki OSM ou des préréglages de JOSM.

La première version provisoire, qui ne concernait que quelques pays d’Afrique de l’Ouest, a été présentée lors du GeoCom (la conférence annuelle geOrchestra) de 2023, le SotM France 2024 et le SotM 2024 à Nairobi. Optimisé suite à des remarques de l’audience lors de ces conférences, le service concerne désormais tous les 28 pays francophones du Sud (ceux listés dans la page Afrique Francophone de Wikipédia + Maurice, le Liban et Haïti) et les mises à jour sont faites en continu, via des réplications minutes. Pourquoi pas tous les pays francophones ? Parce que les données sur la France métropolitaine prendraient trop de place sur l’IFL.

L’approche technique : des couches Planet et thématiques OSM détaillées, en anglais ou français

Classiquement, les données sont hébergées dans des bases pg (PostgreSQL/PostGIS) alimentées par imposm, qui était en 2020 l’outil de transformation des données osm.pbf considéré comme le plus performant. Ce n’est sans doute plus le cas désormais que ses développements et sa maintenance se sont taries, alors qu’osm2pgsql a au contraire été relancé, notamment via un financement de l’OSMF. Lors du SotM 2024 à Nairobi, Jochen Topf m’a d’ailleurs présenté les avantages d’osm2pgsql par rapport à imposm, et peut-être ferai-je la migration un jour, mais en l’état actuel imposm couvre le besoin et la fonction d’update imposm run est bien pratique. Les données OSM sont récupérées depuis les points d’extractions et réplications mises en ligne par l’association OpenStreetMap France, dont le gestionnaire a gentiment accepté d’y rajouter quelques pays qui manquaient.

Concernant les couches, il y a donc pour chaque pays concerné deux jeux de données déjà prêts, l’un dans l’anglais original, l’autre traduite à la volée en français en utilisant un tableau de traduction de référence, publié ici sur GitLab. Les remarques, suggestions ou compléments y sont bienvenus.

Chaque jeu de données contient à la fois des couches thématiques toutes prêtes, mais aussi des couches Planet (c’est-à-dire une couche de points regroupant tous les objets ponctuels dans OSM, et deux autres dédiées respectivement aux objets linéaires et polygonaux) permettant de créer sa propre thématique. En effet, j’ai toujours trouvé dommage que les services existants ne proposent par défaut que des thématiques (Download de Geofabrik ou Bbbike) ou que des couches Planet (HOT Export). Les thématiques disponibles sont : limites administratives, lieux, transports, obstacles, édifices, couverture du sol, hydrographie et points d’intérêts (POI).

Certaines thématiques comportent plusieurs couches, lorsqu’elles sont représentées par des types de géométrie différents (points, lignes ou polygones). Les POI sont disponibles non seulement sous leur forme originelle (points ou polygones), mais aussi dans une couche de synthèse qui comprend les objets ponctuels et les centres des objets polygonaux.

Par ailleurs, chaque couche OSM dans l’IFL permet de retrouver l’ensemble des tags : les clés les plus utilisées dans chaque thématique disposent chacune d’un champ dédié dans la table attributaire, mais il y a également un champ au format jsonb qui contient tous les tags originels de chaque objet. Par ailleurs, si aucune de ces couches ne contient de métadonnées OSM, un champ ajoute_a permet de connaître la date à laquelle chaque objet a été intégré dans la base pg de l’IFL. Il est donc possible d’identifier les derniers objets édités dans OSM, postérieurs à la date de l’extraction utilisée au départ de la création de la base.

Ces couches sont donc accessibles non pas au travers d’un service web, mais d’une IDS. Pourquoi une IDS et pas un site web spécifique ? À la fois pour des raisons pratiques, mais aussi pour prouver qu’une IDS fait cela très bien. Côté pratique, l’IFL étant déjà en place, nul besoin de développer un site web ad hoc. Côté preuve du concept, une IDS libre comme geOrchestra dispose de toutes les fonctionnalités offertes par les standards OGC et les briques logicielles libres comme PostgreSQL/PostGIS, GeoServer, GeoNetwork et MapStore, pour proposer des traitements sur les données, une interface cartographique interrogeable, des métadonnées et des outils de téléchargement. Enfin, la donnée est déjà prête à être téléchargée, sans passer par la création de points de téléchargement personnalisés comme dans le HOT Export, approche qui nécessite ensuite un stockage côté serveur difficile à estimer.

L’accès aux données : via des fiches de métadonnées ou des applications cartographiques par pays

Il y a deux entrées possibles depuis l’IFL pour accéder aux données OSM sur les pays francophones du Sud : via des fiches de métadonnées ou des applications cartographiques.

Les métadonnées comprennent :

• des fiches de métadonnées consacrées à la présentation de chaque thématique disponible ;
• des fiches de métadonnées dédiées à chaque pays francophone couvert avec un lien de téléchargement intégré via des menus déroulants et un lien vers une application cartographique dédiée à chaque pays ;
• une fiche de métadonnées parent qui détaille l’ETL et relie les fiches de métadonnées entre elles.

Des applications cartographiques de visualisation, interrogation, filtrage et téléchargement, sont dévolues à chacun des pays. Il est possible, grâce aux fonctionnalités de MapStore, de télécharger une thématique sur un pays entier, mais aussi de filtrer sur les attributs, sur une zone dessinée à la main ou la zone d’une autre couche, par exemple les limites administratives. Il est donc tout à fait possible, à partir de la couche de POI, de récupérer les hôpitaux, cliniques et pharmacies d’une région ou d’un district urbain, comme ci-dessous dans la Communauté urbaine de Yaoundé :

Des vidéos en ligne ou téléchargeables montrent ces différents accès :

Voilà pour cette longue présentation. Pour conclure, je dirais qu’à une période où les annonces de méga jeux de données mixant plusieurs sources ou issus de l’IA, cet ETL montre qu’il y a encore moyen de faire des choses fines, porteuses de sens et adaptées à des contextes locaux avec OpenStreetMap.

This post was originally published here.

OSM data in English, but also in French, accessible in IFL for French-speaking countries in the South

Downloadable OSM data with attributes in a language other than English, not with a web service, but with a platform dedicated to sharing geographic data and metadata, where you can understand, view, query and filter before downloading: that’s what this ETL (Extract, Transform, Load) approach in the Libres Géographes Spatial Data Infrastructure makes possible. In this post, I’ll go back over the background and history of this personal project carried out in my spare time, before explaining the technical approach implemented and, of course, how to access this data.

The context: moving away from “English fits for all”

While English dominates the OSM ecosystem and remains the project’s reference language, several initiatives allow non-English speakers to participate in and benefit from the project: a multilingual forum, translation of the wiki and certain self-learning platforms, translated user interfaces for applications and editors, including OSM tag presets.

But regardless of the technology or service used, the raw OSM data, once downloaded, remains exclusively in English, and any searching or filtering of OSM data in GIS software can only be done in that language

Having trained extensively in the use of OSM data in geomatics (particularly QGIS) since 2011, I was quickly confronted with the difficulties many non-English speakers have in exploiting the attributes of OSM data. These difficulties were even more frustrating in the case of developing countries, as this was often the first detailed data available for their territory. One barrier was removed, but another followed.

This limitation therefore tends to slow down the learning process for non-English speaking OSM contributors, but more importantly, it remains an obstacle to adoption by audiences outside the OSM community: for example, public services accustomed to creating/distributing/using data in the official language, or one of the official languages, of their country.

In fact, from the beginning of my involvement with OSM, I have always had the idea of making it possible to use OSM data without necessarily having to use English.

Background: a service that could have been here in 2013

Despite the enthusiasm generated by the community response to the Haiti earthquake in January 2010, it remained difficult to promote OSM to humanitarian geomaticians without a service that allowed them to retrieve OSM data in the most common GIS formats without having to deploy a local PostgreSQL database. In short, these geomaticians wanted shapefiles.

As part of the USAID-funded HOT STM020 project in Saint-Marc, Haiti, designed and implemented with Nicolas in the spring of 2012, we were eager to include in the budget a line for a “data download point” that would become HOT Exports (then with a final “s”), developed by GeoFabrik. The following year, the CAP103 project, this time in northern and northeastern Haiti, was an opportunity to fund the addition of tag transformation and translation capabilities to HOT Exports. One of the few surviving visualizations of this v1 testifies to this (below, in Expert Functions):

In fact, it would have been possible to offer a translation of OSM’s English tags into another language as early as 2013. But no one took it up immediately. For my part, I started working on it in the spring of 2015 during a volunteer stay in Dakar and made a first list of OSM tags translated into French and implemented in HOT Exports. Some geomatics students in Senegal were able to benefit from this during sessions dedicated to the use of OSM data in QGIS. But in mid-2015, HOT Export v2 was released, completely rewritten, and all tag transformation and translation capabilities were removed. Again, no choice, English or nothing.

I took over the project in my spare time from the 2020 confinement, this time with the aim of using as a platform IFL, the Spatial Data Infrastructure (IDS) Francophone Libre of the Libres Géographes (based on the geOrchestra project), which was already providing custom layers for some of the association’s projects. I’ve also completed the translation, which now covers 1400 tags linked to the most common OSM keys identified by taginfo, and using translations of OSM wiki Map features or JOSM presets.

The first provisional version, covering only a few West African countries, was presented at GeoCom 2023 (the annual geOrchestra conference), SotM France 2024 and global SotM 2024 in Nairobi. Optimized in response to audience feedback at these conferences, the service now covers all 28 French-speaking countries in the South (those listed here in Wikipédia + Mauritius, Lebanon and Haiti), with continuous updates via minute replications. Why not all the French-speaking countries? Because data for metropolitan France would take up too much space on the IFL.

The Technical Approach: Detailed Planet and Thematic OSM Layers, in English or French

Typically, data is hosted in pg databases (PostgreSQL/PostGIS) fed by imposm, which was considered the most efficient osm.pbf data transformation tool in 2020. This is probably no longer the case, as its development and maintenance have dried up, while osm2pgsql has been relaunched, largely thanks to funding from OSMF. At SotM 2024 in Nairobi, Jochen Topf explained to me the advantages of osm2pgsql over imposm, and maybe I’ll make the switch someday, but for now imposm covers the need, and the imposm run update feature comes in very handy. The OSM data is taken from extraction points and minute replications put online by the association OpenStreetMap France, whose manager has kindly agreed to add a few missing countries.

As for the layers, there are two ready-made datasets for each country concerned, one in the original English, the other translated on the fly into French using a reference translation table published here on GitLab. Comments, suggestions and additions are welcome.

Each dataset contains both ready-made thematic layers and planet layers (i.e. a point layer that groups all point objects in OSM, and two others dedicated to linear and polygonal objects, respectively), allowing you to create your own thematic layers. In fact, I’ve always found it a bit unfortunate that existing services offer only thematic layers by default (download from Geofabrik or Bbbike) or only planet layers (HOT Export). The themes available are: administrative boundaries, places, transportation, obstacles, buildings, land cover, hydrography, and points of interest (POI).

Some themes include several layers if they are represented by different types of geometry (points, lines or polygons). POIs are available not only in their original form (points or polygons), but also in a synthesis layer that includes point objects and the centers of polygonal objects.

In addition, each OSM layer in the IFL can be used to retrieve all tags: the most commonly used keys in each theme each have a dedicated field in the attribute table, but there is also a field in jsonb format that contains all the original tags for each object. Furthermore, if none of these layers contains OSM metadata, an added_at field provides the date when each object was integrated into the IFL pg database. This makes it possible to identify the most recently edited objects in OSM after the extraction date used to create the database.

These layers are therefore not accessible via a web service, but via an IDS. Why an IDS and not a specific web site? Both for practical reasons, but also to prove that an IDS does this very well. On the practical side, the IFL already exists, so there’s no need to develop an ad hoc web site. On the proof of concept side, an open source IDS like geOrchestra has all the functionality provided by OGC standards and open source software building blocks like PostgreSQL/PostGIS, GeoServer, GeoNetwork and MapStore to provide data processing, a searchable map interface, metadata and download tools. In the end, the data is ready to download without the need to create custom download points as with HOT Export, which requires server-side storage that is difficult to estimate.

Accessing the data: via metadata sheets or country-specific mapping applications

There are two ways to access OSM data on French-speaking countries in the South from the IFL: via metadata sheets or map applications.

Metadata includes :

• Metadata sheets dedicated to the presentation of each theme available;
• Metadata sheets dedicated to each French-speaking country covered, with an integrated download link via drop-down menus and a link to a cartographic application dedicated to each country;
• A parent metadata sheet describing the ETL in detail and linking the metadata sheets.

Map applications for viewing, querying, filtering and downloading are dedicated to each country. Thanks to MapStore’s functionality, it is possible to download a theme for an entire country, but also to filter on attributes, on a hand-drawn area, or on the area of another layer, such as administrative boundaries. It is therefore perfectly possible to retrieve, from the POI layer, the hospitals, clinics and pharmacies of a region or urban district, as shown below in the Yaoundé Urban Community:

Online or downloadable videos show these different access points:

So much for this long presentation. In conclusion, I’d like to say that at a time when announcements of mega datasets that mix multiple sources or come from AI, this ETL shows that there are still ways to do smaller, but still fine, meaningful things with OpenStreetMap that are adapted to local contexts.

I just discovered https://github.com/openstreetmap/tile-attribution And it seems like a great way to get involved with openstreetmap via GitHub - It doesn’t require any coding ability, one would need an active GitHub acount to add an issue to the issue tracker but basically find a site using your favourite search engines (lets say https//ddg.gg as an example).

Check any sites who are not providing attribution to openstreetmap when using openstreetmap and report the full hostname of website to the issue tracker :-)

What can we all share to people on social media we use to promote friends & family to support OpenStreetMap’s work?

Have a great day! Josh G of Australia.

https://hardened.computer/@xuid0/113795267986230039

HIII!!! happy new year! i’ve decided to try an maintain a editing streak for the entirety of 2025 and it’s going pretty well (at time of writing i’ve edited daily since december 25th of 2024)! nothing much aside from that i just try to use streetcomplete when bored lol

El Palacete Pinho, en el barrio Ciudad Vieja en Belém de Pará (Brasil), fue la sede de la tan ansiada reunión de mapeadoras y mapeadores de Latinoamérica. Habían pasado cinco años (pandemia incluida) del último SOTM en Encarnación, Paraguay. Pero, para mí, eran seis años, desde la última vez que participé en el evento, en 2018, en Buenos Aires. Así, que ese hermoso palacio, ubicado a pocos metros del río Acará, fue el espacio en el que nos conocimos, encontramos y reencontramos; durante un fin de semana aprovechamos para reconectar con la comunidad regional de OpenStreetMap. De este modo, finalizamos una semana llena de eventos que comenzó con la FOSS4G el lunes antes de ese fin de semana.

En esos días me di cuenta de que ha pasado un tiempo desde que comencé a involucrarme con el mapa de OSM. Lo noté con claridad cuando reconocí otras personas que tienen también su tiempo de colaborar (aunque me tomó unas horas reconocerles) e intentaba recordar de que otro evento les conocía. Pero, además, al ver tantas personas jóvenes involucrándose con distintos intereses temáticos, proyectos e iniciativas. Lo primero que me llevo del SOTM Latam 2024 es una bocanada de frescura al escuchar nuevas voces en la comunidad. Vamos bien y para rato.

Este recambio está impulsado por el apoyo que brindan organizaciones como YouthMappers, HOTOSM y Universidades. Lo cual muestra una diversidad de temáticas de mapeo interesante, que incluyen movilidad (bicicleta, aceras, transporte público), resiliencia, el interés en la Amazonía y población vulnerable. En cuanto al rol de las universidades, y siendo que trabajo en una de ellas, me llamó la atención no solo por las presentaciones durante el SOTM sino también durante el Track Académico del FOSS4G. Este aspecto fue un tema de conversación que tuve con varias personas asistentes al SOTM Latam, pues el espacio académico aparece como relevante para impulsar el trabajo conjunto entre docentes/investigadores y estudiantes universitarios con interés en el mapeo.

A los dos días (y sus noches) les sacamos provecho tanto como fue posible. El crecimiento de la comunidad comienza a generar una hermosa presión para que el evento se alargue un poco más. Afortunadamente, ya para este año tenemos sede para el siguiente SOTM, la hermosa ciudad de Medellín, Colombia. Esta noticia me genera satisfacción por dos razones. La primera es que la comunidad colombiana de OSM está haciendo un trabajo espectacular y estoy seguro de que el evento será un éxito rotundo. La segunda razón, es la cercanía con Centroamérica, lo que espero que nos ayude a participar con más personas presentando ponencias y talleres en Medellín.

El brote de cólera de 1854 en Londres representa un hito fundamental en la historia de la epidemiología. Este estudio de caso nos transporta a una época en la que la comprensión de las enfermedades infecciosas era limitada y las teorías sobre su propagación eran muy diferentes a las actuales. A través de la meticulosa investigación de John Snow, descubriremos cómo un médico logró desentrañar el misterio de este brote, desafiando las creencias establecidas y sentando las bases de la epidemiología moderna. Este caso no solo nos enseña sobre la importancia de la investigación epidemiológica para controlar enfermedades infecciosas, sino que también nos revela cómo la combinación de observación cuidadosa, pensamiento crítico y métodos innovadores puede conducir a descubrimientos transformadores en el campo de la salud pública y ¡Lo descubrió haciendo el primer análisis geoespacial de la historia!

Para la actualización de este estudio de caso usaremos la herramienta Umap para rehacer el análisis de John Snow que identifica la fuente del brote de cólera de 1854 en Broad Street, Londres .

Para este ejemplo, utilizaremos los datos del blog de Robin quén se encargó de digitalizar los datos originales de Snow.

1. Recuperemos los datos y descomprimámoslos en nuestro directorio actual desde: http://www.rtwilson.com/downloads/SnowGIS_v2.zip

2. Transformamos los datos .shp en geojson

3. Cargamos la información y visualizamos los resultados del mapa de colera de 1854

Starting the new year with milestone achievements! In this 22nd development update, we’re excited to present comprehensive mobile support improvements across OpenStreetMap-NG. We’ve also reached critical development milestones that put us on the final stretch toward public beta testing.

🔖 You can read other development diaries here:
https://www.openstreetmap.org/user/NorthCrab/diary/

⭐ This project is open-source — join us today:
https://github.com/openstreetmap-ng/openstreetmap-ng

🛈 This initiative is not affiliated with the OpenStreetMap Foundation.

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Video Summary

This week’s video demonstration focuses primarily on our mobile interface improvements. Through practical examples and side-by-side comparisons, I showcase how OpenStreetMap-NG elevates the mobile experience.

⬇ Click the image below to play

or click here: https://peertube.monicz.dev/w/kRt9W3qqcRtxSwxsGiXmUN

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Enhanced Mobile Support

We’ve significantly improved mobile support across the entire platform, addressing critical usability issues present in the current OSM implementation. Highlighted enhancements include:

• Persistent search bar on mobile devices
• Smooth, animated navigation transitions for a more polished experience
• Reorganized navigation menu with logical grouping and improved accessibility
• Optimized map scale indicator placement for better readability
• Better text formatting and spacing in content pages like “About”
• Properly scaled and positioned UI elements across all pages
• Functional GPS traces interface (fixing current broken mobile experience)
• Responsive settings pages with proper layout and scrolling
• Working OAuth2 application management interface
• Properly rendered profile pages with optimized spacing
• Mobile-friendly sign-in and sign-up pages (great first-time experience)

While these highlights showcase our most notable improvements, we’ve applied the same attention to detail across every corner of OpenStreetMap-NG. Each page, component, and interaction has been optimized for mobile users.

▶️ Watch video segment

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Planet Replication Sync

We’ve achieved another milestone in OpenStreetMap-NG’s data synchronization capabilities. The project now supports continuous planet replication data synchronization (minutely, hourly, daily), expanding beyond our previous reliance on planet dumps and extracts.

With replication support in place, OpenStreetMap-NG gains the ability to generate custom geographic extracts without requiring additional tooling. Additionally, this functionality marks a foundation for the future OSM Ruby to OSM-NG migration procedure.

▶️ Watch video segment

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Preparation For Release

As we approach the public beta testing phase, we’ve completed several critical components:

• Email notification system (including message templates)
• Background automatic changeset management
• Various performance optimizations and fixes

What’s Left:

• Dark mode implementation

The focus on implementing dark mode before public beta is strategic - we want to gather useful feedback on this feature during the testing period when user engagement will be at its peak. This approach ensures we can identify and address any visual or usability issues early in the development cycle.

▶️ Watch video segment

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🌠 Sponsors

This update was sponsored by 17 individual supporters on Liberapay and GitHub Sponsors.

Thank you people of the map! 🦀

• ~1847430
• gileri (Eric G.)
• mutipg
• RedAuburn (Harry Bond)
• ~1819511
• AurimasF (Aurimas Fišeras)
• starsep
• gander (Adam Gąsowski)
• owiecc (Szymon Bęczkowski)
• kkalata (Kamil Kalata)
• okainov (Oleg Kainov)
• sunsurfr
• bryceco

Early supporters of the project receive something special: the time-limited OpenStreetMap-NG Founder profile badge. We believe in inclusive community building, so this unique reward is available to every supporter during the development phase, regardless of donation amount.