Almost two years ago I published a web service that finds suspicious OpenStreetMap (OSM) map changes. You can use the service here and find some more information in previous blog posts. Especially Changeset discussions revealed that they are more or less de facto standard for communication between contributors during map change reviews.

However, when I am inspecting map changes, I sometimes see new contributors using uncommon OSM tags. Therefore I think it could be useful to add an additional assessment parameter to the aforementioned suspicious OSM map changes page. The newly introduced indicator states the matching ratio between the contributed and the most popular OSM tags. This means, if the changeset contributor used many uncommon tags at her/his map changes objects, the matching rate will be low. If the contributor applied many common (“popular”) tags, it results in a high matching rate towards 100%. For the calculation I used Jochen Topf’s taginfo API to get commonly used OSM tags. An API description can be found here. Furthermore I added the average age (in days) of modified and deleted objects. This indicator can be used to see if the contributor edited objects, which have been mapped today (0 days) or exist already for a longer period of time, e.g. 1566 days. The values for the average version numbers are computed in a similar fashion.

The latest version of the OpenStreetMap editor iD has a new feature: “Allow user to request feedback when saving“. This idea has been mentioned in a diary post by Joost Schouppe about “Building local mapping communities” (at that time: “#pleasereview”) in 2016. The blog post also contains some other additional and good thoughts, definitely worth reading.

However, based on the newly implemented feature, any contributor can flag her/his changeset and ask for feedback. Now it’s your turn! How can you find and support those OSM’ers?

• Step 1: Based on the “Find Suspicious OpenStreetMap Changesets” page you can search for flagged changesets, e.g. limited to your country only: Germany or UK.
• Step 2: Leave a changeset comment where you e.g. welcome the contributor and (if necessary) give her/him some feedback about the map changes. You could also add some additional information, such as links to wiki pages of tags (map features), good mapping practices, the OSM forum, OSM help or mailing lists. Based on the changeset comment other contributors can see that the original contributor of this changeset already has been provided with some feedback.

As mentioned in my previous blog post about detecting vandalism in OpenStreetMap (OSM) edits, it’s highly recommended that contributors use public changeset discussions when contacting other mappers regarding their edits. This feature was introduced at the end of 2014 and is used widely by contributors today. Each and every comment is listed publicly and every contributor can read the communication and, if necessary, add further comments or thoughts. In most cases where questions about a specific map edit come up, it is desirable that contributors take this route of communication instead of private messaging each other.

For my presentation at the German FOSSGIS & OpenStreetMap conference I created several statistics about the aforementioned changeset discussion feature. For this blog post I reran all analyses and created some new charts and statistics. Let’s start with the first image (above): It shows the number of commented or discussed changesets per month since its introduction. The peak in January, 2017 is based on a revert with several thousands of changesets.

The OSM project still records around 650 new contributors each day (out of almost 5,000 registered members per day). Some countries (such as Belgium or Spain) already provide platforms to coordinate the introduction to OSM for new mappers. Others use special scripts or intense manual work to send the newly registered contributors mails with useful information (Washington or The Netherland). However, oftentimes new contributors make, as expected, beginner-mistakes. Personally, I often detect unconnected ways, wrong tags or rare fictive data. Unfortunately, sometimes (new) members also delete, intentionally or unintentionally, existing map data.

At the end of 2014, many people were anticipating the newly introduced changeset discussions feature. A few months later, I developed a page that finds the latest discussions around the world or in your country. By now, many OSM members use changeset discussions for commenting or questioning map edits of other members.

Over the past few years I have written several blog posts about the (non-) activity of newly registered OpenStreetMap (OSM) members (2015, 2014, 2013). Similarly to the previous posts, the following image shows the gap between the number of registered and the number of active OSM members. Although the project still shows millions of new registrations, “only” several hundred thousand of these registrants actually edited at least one object. Simon showed similar results in his yearly changeset studies.

The following image shows, that the project still has some loyal contributors. More specifically, it shows the increase in monthly active members over the past few years and their consistent data contributions based on the first and latest changeset:

However, this time I would like to combine the current study with some additional research. I tried to identify three different OSM contributor groups, based on the hashtag in a contributor’s comment or the utilized editor, for the following analysis:

The reputation of a contributor in OpenStreetMap (OSM) plays a significant role, especially when considering the quality assessment of the collected data. Sometimes it’s difficult to make a meaningful statement about a contributor by simply looking at the raw mapping work represented by the number of created objects or used tags. Therefore, it would be really helpful if we would have some additional information about the person who contributes to the project. For example: Does she/he help other contributors? Is her/his work somehow documented or based on one of the “discussed” proposals? Or does she/he work as a lone warrior in the OSM world?

In 2010 I created “How did you contribute to OpenStreetMap?” (HDYC) as a kind of fun side project. Nowadays many people use it to get some detailed information about OSM contributors. Some of you are probably familiar with the “verified” icon used on some celebrity Twitter accounts. I created a similar new feature for the aforementioned HDYC page. If you connect your related OSM accounts, your profile will be marked as “verified”.

#Hashtags are commonly used on Twitter to find content for a specific topic. Also in the OpenStreetMap (OSM) universe they are popular and utilized to mark changesets, which have been contributed during a special event, such as mapping parties or HOT tasks. However, in most cases, they are added in the changeset comment section. Back in November, 2015, several people discussed the pros and cons about (only) this approach. You can find a general overview of good changeset comments here. The aforementioned wiki page also shows why it is important to write a “concise and adequate“ description of the edit. Anyway, I also support the opinion that we should not generalize this statement and only add hashtags in our changeset comments. I prefer the different approach in which the contributor adds an extra changeset tag for the hashtag(s). For example, the widely used JOSM editor allows optional tags (as you can see here). On the other hand, the iD editor, which is used in many cases by new contributors, doesn’t offer this feature. However, I am sure that with some minor changes this could be fixed. A more or less complete set of recommended or mandatory changeset tags can be found here.

Since its rise in popularity, the well-known online encyclopedia Wikipedia has been struggling with manipulation or, in the worst-case, vandalism attempts. Similarly, the OpenStreetMap (OSM) project suffered several times over the past few years of cases where incorrect map data edits were made. These erroneous edits can stem at times from (new) contributors or illegal data imports (or automated edits) which have not been discussed in advance with the community or the Data Working Group (DWG) and corrupted existing project data. The current OSM wiki page gives a great overview about general guidelines and e.g. types of vandalism. Another page in the wiki also mentions a prototype of a rule based system for the automatic detection of vandalism in OSM, which I developed in 2012. However, the system has never actually been implemented. Today, the contributors of OSM can use a variety of different tools to inspect an area or particular map changes. A few of them are listed below (complete list can be found here):

Almost one year has passed again. This means it’s time for the fourth OpenStreetMap (OSM) member activity analysis. The previous editions are online here: 2014, 2013 and 2012. Simon Poole already posted some interesting stats about the past few years. You can find all his results on the OSM wiki page. However, similar to last year, I try to dig a little deeper in some aspects.

Overall the OSM project has officially more than 2.2 million registered members (Aug, 9th 2015). For several of my OSM related webpages I create a personal OSM contributor database, based on the official OSM API v0.6. Anyway, when using this API, the final table will show a list with more than 3 million individual OSM accounts (Aug, 9th 2015). I’m not sure what the cause for this gap of almost 1 million members between the official number and the member number extracted with the API could be. Maybe some of you have a possible explanation? However, I think many accounts are created by spammers or bots.

OSMstats contains several statistics about the OpenStreetMap (OSM) project, such as daily-created objects, the amount of active contributors or detailed numbers for individual countries. One way to determine the sum of created or modified Node objects, is to use the minutely, hourly or daily OSM replication change files and counting the values for each country of the world. Sadly, this approach has some drawbacks. Firstly, the official files do not contain, for example, all Nodes of a modified way, which is required, when trying to find the country where the change took place. Furthermore, the determination of the country for a specific OSM object really depends on the border’s level of detail: More detailed country borders make the processing quite time-consuming. Some of you probably experienced this problem before when using Osmosis or a different OSM processing tool. Anyway, for calculating additional country statistics I tried a new approach: