Defining reversion

Through a healthy community and map-gardening many of the critical issues get noticed and acted upon immediately. A revert is absolute and removes changes indefinitely from the map. Repairs are more manual, often done with a mix of reversion and manual fixes, which are harder to track. osm-revert-changesets npm module is aimed at tracking absolute reverts and works well at 1:1 (changeset to changeset) reverts.

Reversion rules used

Currently, the module uses a starting set of 2 rules to identify reverted changesets.

• Deletions of created features
  • If a feature gets deleted at 2nd version. The edit that created the feature at 1st version is reverted.
• Feature state is reset
  • If Nth version of a feature is reset to N-2th version of a feature, then modifications that were done at N-1th, were reverted.

Usage

npm install osm-revert-changesets

const revertChangesets = require('osm-revert-changesets'); revertChangesets('62632427').then((list) => console.log(list));

Log [ '62629726' ]

This is the input used - DWG repair changeset https://www.openstreetmap.org/changeset/62632427. And this is the changeset that got reverted https://www.openstreetmap.org/changeset/62629726.

Use cases

• Reverted could be a flag for changesets in OSMCHA. Reverted changesets could be marked as bad automatically and they don’t have to be reviewed again saving review time. I ticketed this feature request in OSMCHA at https://github.com/willemarcel/osmcha-django/issues/160

• For large reverts conducted by DWG, this module could be used to return a list of reverted changesets to understand extent of damage, accounts involved and map area affected.

• When changesets get reverted, the edits are removed from the map indefinitely. This module could be used to track amount of reversion on OSM.

Known issues

• This module uses and depends on augmented changesets generated from osm-compare project used in OSMCHA. Example changeset: https://s3.amazonaws.com/mapbox/osm-adiff-compare/production/56917896.json
  • If a changeset is not available in this bucket, the npm module throws failed to fetch errors
• Module fails for reversion of changesets that have modified a feature more than once. Example is https://www.openstreetmap.org/way/622327697/history. This feature is created at V1, modified at V2, and then deleted at V3.

I would like community help in improving the reversion rules and to expand success rate of this module. Shifting to public API with longer historical data for getting feature history would improve reliability. If you have feedback and ideas for improvement, please file issues over at https://github.com/manoharuss/osm-revert-changesets/issues/.

I wanted to share how anyone can contribute to suspicious reasons in OSMCha. Recent events have only highlighted that we can tackle the problem of validation by working together and not by isolated efforts.

Wille is working on a new version of this process that would make it easier to flag features in OSMCha but I wanted to document this current way. When the new version lands in a few weeks time, I will document that process publicly too.

What do we need

• a geojson of a OSM feature with metadata tags
• a suspicious reason
• a OSMCHA production token

---

#### 1. Geojson of OSM Feature

At Mapbox, we use the standard geojson schema as per http://geojson.org/. This is the reason why, OSMCHA was created to expect a geojson as an input when we want to post a suspicious reason. Please see the example geojson feature below.

Example Geojson feature with suspicious reason added in properties

{ "type": "Feature", "id": "relation!6517677!3", "properties": { "osm:type": "relation", "osm:id": 6517677, "osm:version": 3, "osm:changeset": 61091946, "osm:timestamp": 1532618174000, "osm:uid": 3769434, "osm:user": "manoharuss", "suspicions": [ { "reason": "Test", "is_visible": true } ] }, "geometry": { "type": "MultiPolygon", "coordinates": [ [ [ [ -93.0056853, 44.9494124 ], [ -93.00572, 44.9494125 ], [ -93.0057205, 44.9493367 ], [ -93.0059132, 44.9493373 ], [ -93.0059135, 44.9492833 ], [ -93.0060122, 44.9492836 ], [ -93.0060123, 44.9492746 ], [ -93.0061143, 44.9492749 ], [ -93.0061143, 44.9492634 ], [ -93.0062995, 44.949264 ], [ -93.0062998, 44.949214 ], [ -93.0064018, 44.9492143 ], [ -93.006402, 44.9491715 ], [ -93.0056853, 44.9494124 ] ] ] ] } }

Pain points

• Currently, OSMCHA expects all the feature metadata tags and full geojson notation including geometry even though all we want is to post are featureId, feature version and suspicious reason. This will change in v2. V2 may also introduce a way to send in an extra instruction. Example: Profanity detectors can send a note mentioning which word was detected profane.

2. Suspicion reason

This can be any name that we can choose. From mapbox, we have decided that, we will have detections named similar to Mapbox: *detection type* apart from the reasons that we already have from osm-compare. When we post to OSMCha, the suspicious reason should be added into the feature properties.

{ ..., "suspicions": [ { "reason": "Test", "is_visible": true } ] }

Note: is_visible must be true, other wise the reason will not be visible in OSMCHA publicly

3. OSMCHA production token

Once you login into OSMCHA, a new production token is automatically generated for your account. You can usually snoop on any API request in networks panel in your browser, to see your token under the request headers.

Entire selected part in the above image is used for authorization.

---

POST to OSMCHA API

With these 3 resources, we can do a POST request to OSMCHA API and it should show up on OSMCHA instantly.You can use this node js snippet to post to OSMCha.

This is my changeset I tested this script on 61091946. I have greyed out my token code, but it should work as is, if you test with your own production token.

---

We are aware that there is currently a lot of noise in OSMCha reasons and we are hoping to clean those up soon from our end. If you are going to have a service continuously running that posts suspicious reasons, please let Wille know.

Thanks :)

Go catch Lukas Martinelli’s talk on validating every change on OSM this Saturday at 10:30AM in De Donato at State of the Map 2018 in Milan. “We will present how we have built bulletproof protection against the daily vandalism and newbie mistakes we see”. Here is the SOTM Talk Summary.

Places on OSM where we have found vandalism from OSM edits on the day of 2018-06-19

You can review these detections on OSMCHA with the reason Flagged for review by Mapbox.

State of the Map 2017 attendees

State of the Map 2017 was a lively event. This was my first attendance at a State of the map conference. There was good participation from experienced community members from different parts of the world along with members from OSMF, DWG and from companies such as Mapillary, Telenav, Facebook, Apple, GeoRepublic, Grab and more.

It is wonderful to be part of this vibrant community. I have Mapbox to thank, for introducing me to OpenStreetMap and allowing me to work with passionate people for mapping, documentation and validation. I would like to use this diary post to answer some of the recurring questions on OSMCha and some notes from State of the Map 2017.

• Arun’s talk made it clear that new mapper validation catches 60% of all cases of data issues on OSM. This was already a reason in OSMCha for participants to try out during the validation workshop.

• I felt that there was a common agreement on peer reviewing amongst local mappers from the SoTM attendees. This promotes constructive feedback, builds a stronger community and results in better data quality.

• It was great to meet Frederick Ramm from DWG. The workflow the validation team at Mapbox follows has been similar to how DWG approaches in fixing issues, escalations and in sharing feedback to users to become core mappers.

OSMCha

• OSMCha is getting adopted amongst the community rapidly. Last week, 311 changesets were reviewed by various members of the community. The recent OSM feature to request a changeset review can help new contributors to map with more confidence and build a error free map. Do read Pascal Niess’ nice blog post about this and for other ways to review changesets.

• If you are a developer or a team who intends to use OSMCha but if you prefer your own instance, feel free to deploy your own. Here are the resources
  • OSMCha frontend - https://github.com/mapbox/osmcha-frontend
  • OSMCha backend and API - https://github.com/willemarcel/osmcha-django
  • API docs - http://osmcha.mapbox.com/api-docs/
• Documentation on using OSMCha is at https://osmcha.mapbox.com/about. It would be great to have this translated into local languages by community members. This will help OSMCha serve and reach out to local communities better.

OSM-Compare

• OSM-Compare is the open library of GeoJSON comparison rules that flags problematic edits in OSMCha https://github.com/mapbox/osm-compare
• We can use OSM-Compare not only for identifying odd changes on OSM, but also as a social tool or watchlist of certain feature edits:
  • I saw passionate rail mappers at SoTM, I think it would help to flag changesets with rail edits so OSM users can identify and interact with each other, in local communities.
  • Blake Girardot recently opened an issue to flag any changes to man_made=survey_point features. This is now a compare function in OSM-Compare ready to flag the first such change in OSMCha.
  • If you have any other niche use case of OSM-Compare that you would like to use it for, awesome!! Please feel free make an issue and I can help you write a compare function in OSM-Compare that you can use as a reason in OSMCha.

Join us in validation

If you are new to OSMCha and not sure where to start, going through review_requested changesets in your local area is great way to begin. This is a new feature that landed in iD editor on OpenStreetMap. These are the steps I would follow:

• Set the OSMCha filter for changesets with the reason Review requested . This link will set it for you.
• Open the filters and modify the bbox to your local map area that you want to review.
• Hit Apply to view the list of changesets that was requested for review
• Go through the changesets and submit feedback to the mapper by commenting on the changeset on OpenStreetMap based on your assessment.

During recent months, we have seen a lot of new user activity and pokemon targeted feature mapping on OSM. This correlated with observed/assumed association of pokemon spawn points with OSM features by PokemonGo players.

From my observations on reviewing changesets, some features are mapped very specifically for specific pokemons. Some of these features are parks, meadows, waterbodies, gardens, protected area’s, village_green’s, natural reserves, golf courses, cemeteries and forests .

So I made these comparators in OSMCha that flag a new user’s(<=10 changesets) changeset if one of these features have been added brand new(Version 1).

1. Park features added by new users

• This reason flags a changeset if there is a creation of these features in it
• recreation_ground, village_green, park, nature_reserve, protected_area, national_park, garden

2. Waterbodies added by new users

• This reason flags a changeset if there is a creation of these features in it
• natural=water, water=, landuse = pond or reservoir, waterway=

3. Pokemon nest features added by new users

• This reason flags a changeset if there is a creation of these features in it
• recreation_ground, park, pitch, playground, golf_course, meadow, grass, cemetery, grass, forest

One can combine reasons in OSMCha and look at changesets now, add bboxes to specific areas and share permalinks. Ex: All pokemon based reasons in Germany.

From our experience validating, a lot of this mapping is really good and rarely do we find any suspicious edits. Let us know if you find these useful or if I need to tweak them based on changing Pokemon trend.

Screenshots of some really interesting mapping activity I have come across

Changeset: https://osmcha.mapbox.com/48145207/

Changeset: https://osmcha.mapbox.com/48323895/

changesets

It is always interesting to review the latest map edits in your local area. It can be fun to send a welcome message to a new contributor or track changes to a neighbourhood that a fellow mapper has surveyed. It’s an opportunity to both learn from an experienced contributor as well as teach someone new a helpful tip to make mapping more engaging. In a more rare case, these tools can help investigate some missing data or suspicous mapping activity.

The OSM Changeset Analyzer (OSMCHA) tool by Wille Marcel has a powerful interface to filter changesets in your area and flag any suspiscous changesets for further action.

Here’s how you can start using OSMCha in your area:

Step 1 : Understanding and using Filters in OSMCha

OSMCha

Currently available filters in OSMCha

Introduction to filters

• Date fields
  • These date fields are based on changeset closed time as on OSM. We can use date range to narrow down changesets (yesterday, last week)
• Creations, Modifications and Deletions
  • This is a simple count of type of edits in a changeset

• A changeset is suspicious when the changeset is flagged by one of the reasons seen below. These are compare functions that flag a certain type of edits. I will go into more details about how compare functions work in OSMCha and how we can use them to flag specific edits. This has to be an another diary post.

• White-list - When you login into OSMCha using your OSM credentials, OSMCha creates a very basic profile that consists a list of changesets from OSM users you wish to not see in your search. This is a personal custom list for each OSMCha user/reviewer. You can add a user to the white-list when you are in that user’s changeset.

• BBOX - This filter allows to easily give an area of interest we would like to validate. In this case, you can zoom into your particular neighborhood and OSMCha retrieves only changesets whose bbox falls on the area you have given.

These filters give a lot of freedom and flexibility to narrow specific type of changesets we would like to retrieve from a specific area. In OSM one can already use the History tab to see the changesets that overlap with the area on the map but OSMCha adds a lot of filters to this idea to assist the reviewer.

Step 2: Validating your neighborhood

Using bbox filter to select area of interest

When we click the search button, OSMCha presents us with a list of changesets that it thinks fit into our search criteria. An embed version of changeset-map shows geometric and feature tags of edits on the map.

Along with the contextual information where the edits are on the map, geometric edits to the feature, you can also click on the features in the changeset map touched by that changeset to see previous version feature tags and current version feature tags.

Did you try using OSMCha? What worked, and what did you not like? Let us know in the comments below.

Feedback

If you come across a bug you would like to give feedback on, use OSMCha-django repository to file an issue. An issue with overlap of global changesets when using bbox filter in OSMCha has been already raised in my previous diary post. We are working on to best resolve this issue.

If you would like improve detection of a particular type of feature edit, check out our OSM-compare repository and open an issue.

OSMCha is a an open source changeset exploration tool originally created by Wille Marcel. Early 2016, few of us at Mapbox were interested in using this tool for trying out validation on a changeset level. Over the course of 2016, we made several improvements to the tool. As of this morning we reviewed more than 23000 changesets and found 1150 to be harmful to the map. OSMCha database consists useful changeset metadata such as changeset ID, username, editor used, changeset comment, source, imagery used, and timestamp.

You can download a CSV of all the reviewed changesets here. For community members who are interested in validating the map using OSMCha, our validation guide can be a good starting point in understanding the tool, how we use it and validate their own neighborhood.

Few things to note

• OSMCha does not parse all changesets from OSM. There are a few that go unparsed each day because of various edge cases that we are working on fixing. So do not take numbers on OSMCha as absolute but as near accurate estimates.

• Some of the mapping activity marked as harmful in OSMCha are not necessarily harmful. Undiscussed, unannounced imports in OSM are constantly tracked and reverted by the DWG. These edits to the map do not necessarily have mapping mistakes in them but were found to be uninvited into the map to maintain a data import protocol, accuracy on the map and local community accord.

• Hence, mass deletion of above imports in revert changesets by DWG cleanup accounts like Woodpeck_repair are also marked as good edits. These can be ignored by filtering out repair accounts.

• The reviewed changesets were from random places on the map and are not specific to any place. For area specific filtering we can take advantage of bbox filter in OSMCha or filter manually as the CSV contains the bbox information for each changeset.

Basic analysis

Since we have a big dataset of reviewed changesets, we can find correlation between harmful changesets to find patterns of vandalism on OSM. I did a basic analysis using a recently added metadata filter in OSMCha stats page with which I have come to below estimates.

Editor wise breakdown of changesets marked to be harmful

Editor wise breakdown of changesets reviewed

Filters we found to be successful

These are percentage of harmful edits observed against the number of reviewed.

iD+suspect word : 14.1%

iD+mass deletions : 7.9%

potlatch+mass deletion : 5.8%

JOSM+suspect word : 5.8%

JOSM+mass deletion : 4.9%

Maps.me : 3.7%

• Suspect word filter flags changesets with apple, google, nokia, here, waze, tomtom, import, wikimapia as words in changeset comment or source.

Going forward

• Having a database of OSM edits that are classified into good and harmful can help future endeavours into implementing smart anamoly detection tools and machine learning algorithms to better protect the map.

• We are looking forward to continue validation using OSMCha, refine OSMCha changeset flagging heuristics, collaborate with the community with better open tools to protect the map.

Let us know your thoughts, how this can be taken forward and share with us your insights to improve feature level detection.

As a follow up to our previous reviews of Maps.me user edits, these are the Maps.me issues we have observed during the month of November during validation using OSMCha. Documenting the errors observed can initiate a conversation on improving user experience, information to the users, characteristics of mapping activity from users. This in turn improves OSM.

Summary

• Reviewed: 1078 CSV
• Suspicious changesets: 46
• No issues: 1032

We commented on these changesets:

• Added my home in the name tag: 1
• Added 76 fuel_stations: 1
• Added ton of outdoor shops: 1
• Added attractions for address and buildings: 1
• Added amenity=school for bus stops, canteen, parking lot due to the presence of an adjacent school building: 1
• Added Korean names in the name:en tag: 1
• Added attraction tag for addresses: 1
• Added description in the name tag: 1
• Added ton of sports shops and other POIs: 1 - Cleanup
• Added 101 benches: 1
• Added 133 confectionery shops: 1

Community members commented on these changesets:

• Wrong naming to the tags: 1
• Irrelavent information: 1
• Added personal name to the supermarket: 1
• missed religion tag but in name:ru tag pointed that this is Ukrainian church: 1
• Added numbers to the name tag: 1

Reverted changesets:

• Added many view points: 1, 2
• Added weird names for post offices like ‘Timber’, ‘Hostel’, ‘Grocery’: 1
• Added convenience shops at the same place: 1
• Adding virus in the name tag of all the neighborhoods in Vietnam: 1
• Added number of bus stops together: 1
• Duplicate POI’s, community reverted the changeset: 1, 2, 3
• Added number of view points with same name: 1
• Added numbers to the name tag: 1

Observations:

• Incorrect name=* tag edits with personal naming 1 2, incorect language input, description, alphanumeric names 1 2, single letter names, weird names, virus in name tag, numbers.
• Dense and implausible number of POIs being mapped like view points, attractions, benches, convenience shops etc.
• We have not observed partial uploads and changesets without any changeset comment are very few.
• Users are not responding to changeset comments.

It would be great if the community comes together, share thoughts and ideas to help the developers fix these issues in future. Issues can be filed in the Maps.me repository.

From,

Chetan, Krishna & Manohar

During the month of August this is the approximate changeset percentage breakdown between editors that uploaded user edits into OSM:

Source: OSMCha

As a follow up to our review of sample edits from Maps.Me, we decided to randomly review changesets during August to understand the difference in quality and contributions from this editor from our previous review.

Summary

• Changesets reviewed: 475

• Problematic changesets: 12

• Minor issues: 33 Raw notes

• No obvious issues: 430

Problematic changesets

---

1.Changesets 1, 2 with a lot of amenity=fountain and tourism=camp_site tags on residential areas with alphanumeric names. We commented on the user’s changeset.

The edits looked like this on the map

2.Changeset with 91 toursim=attraction POIs. A community member commented and DWG reverted the changeset.

Density of artworks as seen on OSMCha

3.Changeset with 78 ATMs. Community reverted this changeset.

4.Changeset with a lot of of tourism=camp_site tags in one area and some are on water. We commented on this changeset asking for clarification.

5.Changeset with a lot of tourism=attraction tags in names such as I, Pa, ps and gym. We commented and reverted this changeset.

6.Changeset with POIs on roads. We commented on the changeset to let the user know of this.

7.Changeset advertising apartment in demand. We commented on the changeset.

8.Changeset added a bookshop and an outdoor shop at a stadium. We commented on the changeset asking for clarification if these are temporary stalls.

9.Changeset added tourism=guest_house POIs with personal names. We cleaned up all his changesets.

10.Changeset added tourism=attraction & tourism=camp_site POIs to map railway bridges, switches and crossings. We reverted the changeset with a changeset comment.

11.Added amenity=bus_stations over a residential area. A community member commented and reverted the changeset.

---

Changes observed since our previous review

• We have not observed name=* modifications from Maps.me users.

• We have not come across partial upaloads and changesets with no changeset comments were very few.

But we have continued to observe below issues:

• New users may not be aware that their edits (personal bookmarks) are uploaded to a public database and visible to everybody.

• Similar to our first review, there were users using tourism tags instead of the appropriate tags.

• Users are not responding to changeset comments.

• Positional errors

Comparatively, we saw less number of problematic changesets with respect to the number of changesets we reviewed. Let us know what you think of the editor and where it should improve.

Number of new contributors on OSM Source: https://wiki.openstreetmap.org/wiki/Stats

There has been a significant spike in new contributors to OSM that coincide with the launch of edit feature in maps.me. Do you think it correlates with new user contributions using Maps.me? Let us know what you think.

From,

Chetan, Krishna & Manohar

Continuing from our previous weekly round-up, we would like to keep you posted on some of our observations this past 2 weeks.

Commented

We commented on the following changesets:

• Deleted a tertiary road: Changeset.

• Deleted landuse=residential polygons: Changeset.

• Deleted buildings: Changeset.

• Added duplicate buildings: Changeset.

• Added POIs with numbers in the name tag: Changesets 1, 2.

• Building, parking lot and service roads deleted: Changeset.

• Some of the POIs added are on roads and river: Changeset.

• Created duplicates of highways and buildings: Changeset.

• Deleted highway=tracks and waterways: Changeset.

Community members commented on the following changesets:

• Deleted highway=path: Changesets 1, 2.

• Added a POI in the middle of the sea: Changeset.

• Changeset using Google as source: Changeset. A DWG member commented on the changeset.

Reverted

• Untagged ways in the same area: Changesets 1, 2, 3, 4, 5, 6, 7. We reverted these changesets.

• Added bus station over residential area: Changeset. A community member commented and reverted this changeset.

• Added operator tag with personal name for bus stops: Changeset. A community member commented and reverted the changeset.

• Imports with not tagged according to OSM: Changesets 1, 2. A community member commented and reverted these changesets. The import looked like this.

  

Look forward to these posts as we wish to continue posting weekly round-ups to inform the community on our findings on OSM.

We’re going to be at SOTM in Brussels next week. Catch up with @planemad, @jinalfoflia, @ramyaragupathy, @pratikyadav and @geohacker on the latest data team projects at Mapbox!

Following up on a recent series of posts that summarized the suspicious changes on the map, an interesting question that we bring to the community - what is a good amount of time to wait for a response from an inexperienced mapper before fixing or reverting their edit?

You can see examples of such changesets that do not seem right on these posts:

• https://www.openstreetmap.org/user/Chetan_Gowda/diary/39219
• https://www.openstreetmap.org/user/Chetan_Gowda/diary/39166
• https://www.openstreetmap.org/user/nammala/diary/39055
• https://www.openstreetmap.org/user/Maanya/diary/38972
• https://www.openstreetmap.org/user/manoharuss/diary/38941
• https://www.openstreetmap.org/user/manoharuss/diary/38907
• https://www.openstreetmap.org/user/manoharuss/diary/39050
• https://www.openstreetmap.org/user/manoharuss/diary/39050 (Maps.me review)

Observations from last week

• User added unexplained nodes with alphanumeric names: 1, 2. A community member commented on these changesets and reverted them.

The community is great at responding to mapping issues but there are few issues lying under the rug. When we see unexplained edits without a clear comment or source, we do not go and fix them immediately, but let the user know the best practice and try and encourage them to to become a better mapper.

During the last 3 months the data team at Mapbox has commented on around 78 changesets and fixed only around 10 changesets. Over the course of last 1 year we have commented on around 250 changesets that did not get a reply from the user (quick map of these changesets).

It is a very subjective question to ask how long do we wait before we take the plunge into fixing or reverting changesets like these which may be suspicious, but is difficult to verify from the original mapper. Happy to hear how you approach this issue.

Sharing this open dataset of Canada road networks from the Canada Open data website. The wiki mentions Statistics Canada(StatCan) as one of the data sources, but the StatCAN wiki page, provides a link to an outdated portal where road data is available only until 2010.

Details

The data quality and technical specifications of this 2015 dataset is detailed in the new StatCAN page.

• Provider: Statistics Canada
• Published date: 2015-05-27
• File formats: Shapefile, GML, JSON
• Frequency: Mentioned “As Needed”
• Contact: http://open.canada.ca/en/forms/contact-us
• URL: Canada road networks files 2015
• License: http://open.canada.ca/en/open-government-licence-canada

The road network supplied includes road classes, road names, city etc. Through a preliminary look in QGIS I have these findings.

Coverage as seen on QGIS, road classification on the left

The road classification is represented in numbers in theclass attribute. Major highways are given under class 12 in the attribute table

Data Quality

There were few concerns on OSM wiki page of StatCan regarding geometry of the roads. But the wiki page seem to be outdated and the concerns were in regards to the older data (2010). The geometry of the roads in this data set seem to align with the OSM layer in QGIS.

Roads in Toronto overlayed on OSM layer in QGIS

The street names on the data seem to be same as on OSM as well

Coverage in Toronto without OSM background

This seems like a great dataset to evaluate the quality of data and coverage of roads in Canada. Would be great to hear from the Canadian OSM community of any previous work using this dataset that can be taken forward.

Turn restrictions are the last missing piece in the puzzle to make OpenStreetMap ready for accurate routing. With Mapillary street photographs and their traffic sign recognition, it is easier than ever to start mapping missing restrictions onto the map.

At the data team in Mapbox, we have been experimenting with creating mapping tools to simplify such efforts and after adding over 1,200 turn restrictions in 30 US cities, we are ready to start mapping in Canada with the help of the local mapping community! Our team will focus on the following 5 cities: Ottawa, Toronto, Montréal, Vancouver and Calgary

How to contribute

Mapping

If its your first time mapping turn restrictions, read the guide to mapping turn restrictions using Mapillary to understand different scenarios and special cases.

Use the OSM navigation map to compare traffic signages from Mapillary and the map data for potential restrictions to add. You can also review the photograph and mark the restriction as valid or invalid.

Check out our project tracker for all the details and collaborating your efforts with the Mapbox data team.

Marking a detected no left into a oneway as redundant restriction on the OSM navigation map

Mapillary

More Mapillary = More detected signages that can be mapped. Check the Mapillary coverage in your city and fill in the gaps! Calgary currently has the poorest coverage amongst the 5 cities. This tutorial will help you can get started with Mapillary.

Measuring progress

We estimate it to take 1 full week to review all the detected turn restrictions in the 5 selected cities with just our team. But could finish it off sooner and add more restrictions with a wider participation. These are the current number of restrictions present that were queried using Overpass:

Canada: 12,700

• Ottawa: 447

• Toronto: 1,129

• Montréal: 372

• Vancouver: 441

• Calgary: 64

The road ahead!

It would be amazing to have the Canadian Mapping Community to help us out in making the map of Canada more navigable and enhanced. We would love to hear your ideas and thoughts on how to make our existing workflow better. Interested folks can contribute to the Mapillary coverage in Canada which would certainly help us add quality data onto the map! Let’s all join hands in making OpenStreetMap the best!

TLDR: Most contributions from MAPS.ME editor are constructive and has significantly increased new contributors to the map. With any new tool, there are common mistakes that is made, many of which could be easily prevented by simple improvements to the editor and awareness for the users. __________________________________________

MAPS.ME is quickly becoming a popular way to contribute to OpenStreetMap, with over 250,000 changes within 3 months of launching the map editing feature.

Following recent reports of bad edits, we decided to review a random sample of changesets in detail last week to understand the quality of contributions from this new editor.

Summary

• Changesets reviewed: 215
• Problematic changesets: 8
• Minor issues: 19 (Raw notes)
• No obvious issues: 188

Problematic changesets

Looking at these changesets in detail can give some insights on what improvements could be made to help new mappers contribute constructively to the map:

1. User added a castle that do not exist which was later deleted by another user.
2. User added a lot “artworks”. A community member commented on the changeset but the user did not reply yet.
3. User added 211 hardware shops. I have commented on the changeset but did not get a reply.
4. User added a duplicate POI. A community member commented but did not get a reply.
5. User added 29 tourism=viewpoint tags to all kinds of things. I commented on the changeset.

6. Department stores everywhere looked like this. I commented on this changeset.

7. User added tourism=viewpoint tags to 23 nodes in one area. I commented on this.
8. User added 40 tourism=caravan_site tags to nodes along the roads. So when I opened it, it looked like this. This was captured in this Russian forum and was later cleaned-up.

Observations

• The problematic changesets seem to indicate that new users may be unaware of best practices of mapping, or do not know their edits are seen by everyone else
• Users do not respond to changeset comments
• Users tend to use an incorrect tag like attraction if they don’t find the appropriate category for their POI
• Changing local names to non local names was observed consistently
• Partial uploads / lack of changeset comments
• Positional errors
• User mistook adding POI for a personal bookmark

For monitoring and reverting changes from MAPS.ME contributors, Ilya Zverev has made a convenient web tool http://mmwatch.osmz.ru/ , and a reverting tool http://revert.osmz.ru/ to track and fix edits by country. In the monitoring tool, one can see the latest edits and tags edited, and also mass revert multiple changesets. The revert tool allows easy revertion of a list of changeset ids.

What are your thoughts on the editor?

From: Chetan, Krishna & Manohar

Here is this week’s collection of suspicious mapping observed between 20 - 24th June.

• This changeset from a new user was observed to be deleting POI’s, beach, public toilets and adding a random square without reference to the imagery or any mentioned source. This was reverted.
• This changeset changed name of the Paracel islands from Chinese to english, changed the locality from Chinese to Vietnamese, added a traingle on the map with no reference. This was reverted by the DWG.
• This changeset was observed to be deleting a lot of buildings and roads.
• This changeset deleted a lot of service roads.
• In this changeset the nodes had landuse=farmland tag.
• This changeset had given building=yes tag to resendential areas instead of the individual buildings.
• This changeset deleted buildings using iD editor with no explanation in the comment.
• This changeset deleted private roads using the iD editor. This was reverted by the community.
• This changeset added address tags to every single object in the changeset including the nodes. The cleanup of this changeset was detailed in this diary post.

And ofcourse, look forward to this roundup again next week. If you observe any suspicious mapping, comment on the changeset and let the mapper know. Mistakes happen all the time.

Happy mapping!

Weekly observations between 27th to 30th June can be found here.

The amount of data on OSM sometimes boggles the mind, there was 23471 new changesets just yesterday. With so much great mapping work being done by the community, there’s always a possibility of a few bad apples. So, here’s a collection of a few that I have stumbled across last week (13 - 17 June).

• This changeset in which a number of highway=footway & footway=crossing & crossing=zebra tags were deleted and nodes on highways with highway=crossing tags were added in downtown Atlanta. It is to be remembered that both these methods are suggested in the OSM wiki for mapping crosswalks.

• This changeset deleted roads in Ethiopia using iD editor. Also 5 harmful changesets from 2 other users from whom one was deleting buildings and the other was editing features without any reference imagery or mentioned source.

• This changeset gave non-latin names in name tag in London and this was reverted.

• In this changeset, nodes had attributes meant for the ways.

• This changeset fixes a user changing trunk road to primary road tag.
• These 3 changesets 1, 2,3 were reverted because they looked like this.

Stumbled on anything suspicous on the map this week? Do drop the mapper a message, for all you know, it was just an honest mistake :) Look forward to another roundup next week.

I have been mapping my home town of Gudivada. This is where I grew up and did all my schooling. In the Telugu language, “Gudi” means temple, and “vada” means a settlement or a town - Gudivada has many Hindu temples.

When I decided to map, I expected that since this is a small town there would just be a node with a name, and not much else. I was wrong though - trunk, primary, secondary, and tertiary roads along with many points of interests and buildings around the center had been well mapped, thanks to the active OpenStreetMap community.

I focused my efforts on mapping residential streets, and adding places like hospitals, temples and schools I was certain about.

Before and after

Here are the residential roads I added within Gudivada. A number of features such as water bodies, public water tanks, school names and area names which I have added most recently are not visible in the ‘after’ gif due to OpenStreetMap not rendering those objects at that zoom level.

Closeup of my edits

Here is a closeup of my edits in my hometown. One issue I encountered was not being 100% sure about road names so refrained from adding local names to the roads. For example, as I was mapping, I came across “Eluru Road” which goes across the town - my hunch is that this road has a different official name.

Link to the map

What I added and modified:

• Missing residential roads were added
• Re-classified many roads to Tertiary roads based on road classification documentation
• Added places like schools, school grounds, property boundaries, water bodies, places of worship, stadium and other amenities.
• Misaligned roads
• Added amenities for existing buildings
• Intersections

What’s next?

I’ve enjoyed mapping my hometown and added numerous features which I am intimately aware of. My plan is to add more details based on satellite imagery and local knowledge, and do a field survey the next time I visit to ground-truth Gudivada data on OpenStreetMap.

I’d also welcome any comments others in the community have to improve what I’ve mapped, or tips for mapping.

Locality mapping and updating addresses

Hello everyone. I am a mapping enthusiast and I seek to add geocoded data for Sri Ramachandra nagar in the city of Vijayawada. It is a city with about 850,000 population and it is a major city in the state of Andhra Pradesh, India. I am familiar with the area around my home.I am looking to tag places of importance in the city, create and edit data in Sri Ramachandra nagar. I have started by tagging full addresses for major establishments I know of. I would like it if anybody in the area helps me out with the door numbers and details of newer businesses and residential buildings.

I have started by tagging around Ayush Hospital. For anybody who is interested to map in Vijayawada, I am willing to collaborate. Usually ton of educational institutions, hospitals have websites. In the business website you can find the full address with door numbers and pincodes. That should help you to enter the information into OSM. These businesses have constant addresses and should help in tagging addresses. Cheers.