Recent diary entries
The City of Raleigh, NC has also released data on ArcGIS. http://data-ral.opendata.arcgis.com/datasets
Marked the Burrinjuck Dam tramway, a 2ft narrow gauge line created to service the construction of the Burrinjuck Dam. The line ran from Goondah to the dam construction site. Although the track was lifted in 1929 the line is easily traced in the NSW LPI aerial imagery and the right of way appears on the NSW LPI topographic maps.
The line has been traced as far as the Burrinjuck rd / Page st intersection. Beyond that point the Dam access road has razed the line.
I'm going to be too busy to update OpenStreetMap or even to respond to messages quickly, at least for a few weeks. I may make the odd edit in the meantime.
My mission is to colorize all of Cayo District. Adding meadows, forests and rivers.
A Good Day: Watermelon from Nohur, Where Alexander the Great Left Some Troops, and Street Names in DurunPosted by apm-wa on 10 June 2018 in English (English)
Ann and I drove up to Nohur, an ancient Turkmen village she had not yet seen. Alexander the Great came through here a couple of thousand years ago and left some of his legion behind. They settled in Nohur and their descendants are still here, some still with green eyes inherited from their Greek forebears. The village is famous for its watermelons so we bought one. While there I recorded the names of two of the three cemeteries not yet mapped and have now added them to OSM. I have to wonder how many of Alexander's soldiers are buried in them!
When the Mapillary images are uploaded (currently in progress) you can see some of the headstones, which are decorated with ram's horns. Nobody seems to remember exactly why, but it is apparently a custom left behind by the Greeks.
On the return to Ashgabat, we stopped to explore Durun, a typical former Soviet state farm village. It is small so we recorded every street name in the village represented on a street sign (not all streets had signs), plus some POIs. My embassy has published six American books in Turkmen translation so we gave books away to the villagers as we drove around collecting cartographic information. Word spread and at times we were mobbed by children wanting their own copy of "Harold and the Purple Crayon" in Turkmen. All in all it was a very enjoyable Sunday.
Tomorrow we'll start eating the watermelon.
I've created stubs of articles on the five provinces of Turkmenistan:
I've added photos to some of them. Please take a look and let me know what's missing. These are works in progress.
Hi guys, any OSM Editors in Siquijor?
As of the last upload of images from a trip across the Karakum Desert to the city of Dashoguz, and visits to sites in and around Dashoguz, I have contributed a bit more than 200,000 Mapillary images, the vast bulk of them in Turkmenistan and the vast majority taken in areas where nobody else had captured ground-level imagery to that point. I hope some of you will take the opportunity to visit Turkmenistan virtually via Mapillary, since Turkmenistan issues only about 11,000 tourist visas per year and is one of the least visited countries on the planet There are some marvelous sights, however! I'm trying to capture as many as I can.
Somebody vandalized streets I had drawn in Awaza, the resort zone on the Caspian Sea shore. He (yes, it was a male of the species) disconnected streets and moved them around, then added nonexistent streets. I don't understand why someone is motivated to vandalize a map database. It is all repaired now, but repairing the damage cost me time I could have spent doing something else.
As part of the #cittasenzamemoria project, the verification of toponyms dedicated to Vittorio Emanuele III in Sardinia was updated.
The data comes from the map of OpenStreetMap aimed at creating a free content cartography of the world. The map information is freely accessible under license ODbL and updated every day. To facilitate the consultation, the toponyms are also available on the dedicated online map. A total of 39 names were identified below:
id name City
1 Corso Vittorio Emanuele III Bonorva
2 Via Vittorio Emanuele III Cheremule
3 Piazza Vittorio Emanuele III Martis
4 Via Vittorio Emanuele III Ozieri
5 Via Vittorio Emanuele III Semestene
6 Via Vittorio Emanuele III Birori
7 Via Vittorio Emanuele III Borore
8 Via Vittorio Emanuele III Bortigali
9 Via Vittorio Emanuele III Macomer
10 Via Vittorio Emanuele III Mamoiada
11 Corso Vittorio Emanuele III Gesico
12 Via Vittorio Emanuele III Silius
13 Piazza Vittorio Emanuele III Cabras
14 Via Vittorio Emanuele III Morgongiori
15 Via Vittorio Emanuele III Narbolia
16 Via Vittorio Emanuele III Riola Sardo
17 Via Vittorio Emanuele III San Vero Milis
18 Via Vittorio Emanuele III Sedilo
19 Piazza Vittorio Emanuele III Tresnuraghes
20 Corso Vittorio Emanuele III Scano di Montifierro
21 Via Vittorio Emanuele III Flussio
22 Via Vittorio Emanuele III Magomadas
23 Corso Vittorio Emanuele III Sagama
22 Via Vittorio Emanuele III Jerzu
23 Via Vittorio Emanuele III Triei
24 Via Vittorio Emanuele III Ulassai
25 Via Vittorio Emanuele III Collinas
26 Corso Vittorio Emanuele III Furtei
27 Via Vittorio Emanuele III Gesturi
28 Via Vittorio Emanuele III Lunamatrona
29 Via Vittorio Emanuele III Pauli Arbarei
30 Via Vittorio Emanuele III Siddi
31 Via Vittorio Emanuele III Villanovaforru
32 Via Vittorio Emanuele III Villanovafranca
33 Via Vittorio Emanuele III Musei
34 Via Vittorio Emanuele III Berchidda
35 Via Vittorio Emanuele III Florinas
36 Via Vittorio Emanuele III Montresta
37 Via Vittorio Emanuele III Fordongianus
38 Via Vittorio Emanuele III Sardara
39 Via Vittorio Emanuele III San Gavino Monreale
In detail, individual odonyms are also viewable on the wiki page of the project #cittasenzamemoria related to Sardinia.
- Work method
The working method consisted in verifying the data coming from ISTAT 2011 Census. If the route is present in the ISTAT database through ancillary sources, it has been determined that the plates are actually registered to Vittorio Emanuele III and does not have its two homonymous predecessors (Vittorio Emaneuele I and II). If the check is positive, the presence of the road on OpenStreetMap has been checked. The result produced was that almost all the 39 mames checked were mostly already present and therefore verified by the local community of OpenStreetmap users. The strong presence of anthroponyms dedicated to Vittorio Emanuele III in Sardinia is due to the fact that in the constitutional referendum of 2 June 1946 with 60,9 % in Cagliari, the opponents won the elections to introduction of the Republic.
- Final considerations
The work carried out on Sardinia shows that the map of OpenStreetMap can be considered a valid database reliable and certified by the same community of voluntary mappers that with their painstaking work, verify, check and update the data on the maps.
We recently added Korean translation thanks to the precious work of Korean contributors, making JOSM available in 36 languages! But does it mean JOSM supports all major languages of the world? Clearly not: For large regions (Middle-East, North Africa, Balkans...), JOSM has not been translated yet in any official language.
If we check the top 20 languages by the number of native speakers, only 11 are supported: This makes Hindi, Arabic and Bengali the most important languages to add.
We need help for this! You can contribute to translations on Launchpad, or share the news!
In last November 2017 there were around 700 educational institutions in OpenStreetMap, most of them in urban areas and nothing in rural areas, the information about educational institutions present in OpenStreetMap was incomplete and we really couldn’t know how many educational institutions exists in a place, or which places don’t have any schools.
Bearing in mind that many educational institutions do not exist in the map and with the purpose of having the complete information of all educational institutions of Peru in OpenStreetMap, knowing that this information will allow the government to make better decisions such as: Improve access to education, better educational politics as well as services and the quality of education in the country.
As part of a collective effort we made a coordination with the Ministry of Education, to be able to use the data of educational institutions that they manage through SIGMED’s portal and can use all data of schools and kindergartens for import into OpenStreetMap.
The import process was carried out following the import guidelines set in OpenStreetMap.
Process of School’s import
Step 1: Prerequisites
Before to start the import process of import, we identified the categories of the database of SIGMED, these categories includes categories such as Basic regular education(EBR), Basic alternative education(EBA), and productive technical education(ETP), for this process we just selected Basic Regular Education, this category includes 3 levels of education:
Step 2: Community Buy-in
We talked about the import schools, in the last SOTM, this event was made in last November in Lima.
Step 3: License approval
For obtain permission to use the SIGMED data in OpenStreetMap, we made a coordination with the territorial analysis specialist of the Ministry of Education, Sergio Miness, who agreed, and also mentioned that there were plans for import but those did not come true The data of the educational institutions are available for use from the SIGMED portal, which can be used for any purpose.
Step 4: Documentation
- We wrote a documentation about the process import and how to import schools using the task manager, this guide is available in: https://wiki.openstreetmap.org/wiki/Import/Catalogue/Peru/schools
- We created this repository focuses on import schools https://github.com/osm-pe/schools-import
Step 5: Import Review
After the data was downloaded of SIGMED, we selected which tags should be included, after the discussion, we considered the next tags for import:
It was also selected that OpenStreetMap tags should be added, for the correct labeling of educational institutions:
To better manage the large amount of data downloaded from the SIGMED and facilitate the import process, were created:
- A task manager
This which allowed to work in order wayin the importation process of educational institutions, an orderly manner in the importation process of educational institutions because the process import occurs within of specific area, and the task has 4 indicators of status of this block: Not done, in progress, done and validated, in this way we can tracking the progress of task You can find the task manager link here:
Due to the large amount of existing data of Educational Institutions, it was decided to divide the area of the country, this was done according to the density of educational institutions by area.
This task is available from here : https://osm-pe.github.io/schools-import/#5/-9.265/-73.488
Step 6: Uploading
For uploading the data into OpenStreetMap, we used an editor for OpenStreetMap - JOSM, this tool allows to view and manipulate the data prior to upload.
Finally, after 8 weeks of hard work, we managed to import more than 75, 000 educational institutions throughout Peru, we are really happy to contribute to improve the data in OpenStreetMap! This data will be available for anyone to access at the information. This is especially important for rural areas, since schools are now in OpenStreetMap, and local or regional authorities can use the data to assess the impact of the infrastructure and road networks that lead to these educational institutions, as well as to plan impacts that could occur if disasters occur, as well as allocate funds according to the need of each educational institution.
¡Más de 75, 000 escuelas fueron importadas en el Perú!
Hasta el mes de noviembre del 2017, en OpenStreetMap habían alrededor de 700 instituciones educativas en Perú, la mayoría de éstas presentes en áreas urbanas y casi ninguna en el área rural, la cantidad de instituciones educativas que se mostraba en el mapa era incompleta, y no se sabía realmente cuántas instituciones educativas existían en una ciudad o en qué ciudades no habían instituciones educativas.
Teniendo en cuenta que muchas instituciones educativas no existen en el mapa y con la finalidad de tener la información completa de todas las instituciones educativas del Perú en OSM, sabiendo que esta información permitirá al gobierno tomar mejores decisiones como: Mejorar el acceso a la educación, mejores políticas educativas así como los servicios y la calidad de la educación del país.
Como parte de este esfuerzo colectivo hicimos coordinaciones con el Ministerio de Educación del Perú, para poder usar los datos de las instituciones educativas que ellos manejan a través del Mapa de escuelas - SIGMED y poder importarlos a OpenStreetMap.
Para realizar este proceso, seguimos las directrices de importación de OpenStreetMap.
Proceso de importación de instituciones educativas
Paso 1: Pre requisitos
Antes de iniciar el proceso de importación, se identificaron las categorías de la base de datos del aplicativo Mapa de Escuelas del Ministerio de Educación del Perú (SIGMED), estas categorías incluyen: Educación Básica Regular(EBR), Educación Básica Alternativa (EBA) y Educación Técnico Productiva (ETP). Para el proceso de importación se consideró la categoría de Educación Básica Regular, esta categoría incluye 3 niveles de educación:
- Inicial, comprende de 1 a 5 años.
- Primaria, comprende de 6 a 11 años.
- Secundaria, comprende de 12 a 16 años.
Paso 2: Coordinaciones con la comunidad
Se dió a conocer sobre el proceso de importación en el Estado de mapa de Latinoamérica, el que se llevó a cabo en la ciudad de Lima en el mes de Noviembre del 2017.
Paso 3: Aprobación de la licencia
Para obtener el permiso de uso de los datos de SIGMED en OpenStreetMap, se hicieron coordinaciones con el especialista de análisis territorial del Ministerio de Educación, Sergio Miness, quien estuvo de acuerdo, y también mencionó que hace un tiempo ya hubo planes de importación, pero que estos no se llegaron a concretar. Los datos de las instituciones educativas están disponibles para su uso desde el portal del SIGMED, los mismos que pueden ser usados para cualquier propósito.
Paso 4: Documentación
Se escribió una guía con todo lo relacionado al proceso de importación de las instituciones educativas, la cual está disponible aquí.
También se creó un repositorio en github para seguir el proceso de importación de instituciones educativas.
Paso 5: Revisión de la importación
Después que los datos fueron descargados de SIGMED, se seleccionó las etiquetas que deberían ser agregadas y omitidas en el proceso de importación, después se obtuvo el siguiente cuadro:
También se seleccionaron las etiquetas de OpenStreetMap que debían ser añadidas, para el correcto etiquetado de instituciones educativas:
Para manejar mejor la gran cantidad de datos descargados del SIGMED y facilitar el proceso de importación, se crearon:
- Un administrador de tareas
El cual permitió trabajar de manera ordenada en el proceso de importación de instituciones educativas, ya que se trabaja dentro de un área específica, y el cual tiene un indicador de estado de la tarea: No hecho, en progreso, completo y validado; el cual fue diseñado para el control y seguimiento del progreso de la importación de instituciones educativas. El link del administrador de tareas se puede encontrar aquí.
Debido a la gran cantidad de datos existentes de instituciones educativas, se optó por dividir el área del país, esto se realizó de acuerdo a la densidad de instituciones educativas por zona. Ejemplo:
Paso 6 Subida de datos
Para subir los datos a OpenStreetMap, se usó JOSM, el cual es un editor de OpenStreetMap, el mismo que permite la manipulación de datos, antes de subirlos a OpenStreetMap. En este ejemplo podemos observar cómo se realizó el proceso de importación de instituciones educativas. 👇
Finalmente, después de 8 semanas de arduo trabajo, se lograron importar más de 75, 000 instituciones educativas en todo el Perú, nos sentimos realmente felices por contribuir a mejorar los datos en OpenStreetMap, ya que estos datos estarán disponibles para que cualquier persona pueda acceder a esta información. Además, esto es especialmente importante para las áreas rurales, ya que las instituciones educativas rurales, están agregadas ahora en OpenStreetMap, y las autoridades locales o regionales pueden usar los datos para evaluar el impacto de la infraestructura y las redes viales que conducen a estas instituciones educativas, también permitirán planificar los impactos que se podrían dar si ocurren desastres, así como asignar fondos de acuerdo a la necesidad de cada institución educativa.
I recently discovered the Durham County Open Data site. Licensed under ODbL 1.0, it is a large collection of various data sources from election result data to bike racks. Some of the datasets are a few years old but most of it seems up-to-date.
Hopefully someone will be able to use this; enjoy!
Link to the front page
A while ago I launched a few challenges on the new MapRoulette (new! you should check it out :)) that have to do with motorway exit information in the United States. Lots of exits around here do not have that information, encoded mainly in
A destination being added based on a Mapillary image
Obviously, this information cannot be added from aerial images, but now that there is plenty of street level images from OpenStreetCam / Mapillary to choose from, adding destination info as a non-local mapper becomes much easier. That's why I created these challenges.
- A task from the Connecticut destinations Challenge *
See the wiki on
destination for detailed tagging guidance. Happy mapping!
I've been enjoying the Notes features of OsmAnd, both for adding new ones and even more for finding nearby ones when I'm out and about. Every OSMer should tell all their friends to lodge notes! :-) I've been training everyone I can (two people so far; maybe I need more friends).
I also only recently noticed that people near where I live are actually leaving notes (they weren't last time I looked a year or two ago.) Which is great, and I'm trying to fix them all. Many seem to come from MAPS.ME, and sometimes are in the wrong spots or are spurious (most commonly saying a thing is gone when it's not). But more are useful than aren't.
So I've added the RSS feed of notes for this area to my normal daily news aggregator, and hopefully will do a better job of keeping up to date with people's corrections and spam.
Which is correct icon/point to describe fort in OSM? I couldn't find it quickly :/
Some OSM users copy from Google Maps. Others go as far as to add the tag "source"="Google Maps" to features. By using Overpass Turbo, I was able to find all objects with "source" = "Google" and "Source" = "Google Maps". This returned 2734 different features attributed to Google Maps. Click either the link above or this one to see every single one. Perhaps we can fix or delete them all together.
Please note that Overpass Turbo may take a minute or two to search the entire globe for "source"="Google Maps".
I have at least started OSM wiki articles on the major cities of Turkmenistan, as follows:
The intent is to institutionalize all I have learned about mapping in Turkmenistan so far, before my tour of duty ends sometime this calendar year. If other mappers have suggestions for information to add to these articles, I am all ears.
I was going over unnamed 'main' roads in my area using this Overpass query in JOSM:
Most of the time I can use the TIGER overlay to add the missing names. Sometimes I stumble upon a way that should have been tagged as a roundabout or a link (and those usually do not have a name tag). There are some cases when a mapper has added a newly built road from survey or aerial images that does not appear on TIGER yet:
It would be useful to remind myself and others to take some street level imagery there. So I started adding
fixme=streetlevel tags to these ways. Perhaps this can be picked up by OpenStreetCam and Mapillary to add to their apps so people can remember to drive there when they are in the area. Extra points maybe?
update there is already the more generic
fixme=survey which could also be used, however, for some cases you would specifically like street level images. The few
fixme=survey that I found in a quick search in the western USA were mostly trails and paths, which are not the main use case for street level platforms (you can capture them of course).
Last week I implemented history call to retrieve all old versions of an element, version call to retrieve a specific version of the element and added possibility to specify version number for element in multi fetch call, i.e.:
- GET /api/0.6/[node|way|relation]/#id/history
- GET /api/0.6/[node|way|relation]/#id/#version
- GET /api/0.6/[nodes|ways|relations]?#parameters (added optional version number)
- node 21265449 history
- way 4823378 history
- relation 123924 history
- node id=21265449 version=4
- way id=4823378 version=30
- relation id=123924 version=217
- nodes 26047550 version 28, 26047555 version 22
- ways 4903994, 4904157 version 7, 4904160 version 3
- relations 1148410 version 51, 1155947 version 6, 1155950
Unfortunately, current and history tables contains the same data, so currently it's not possible to get all element's history or some old version of element.
Next week I will implement relations for element and ways for node calls. So I will finish all read-only elements calls.