Theres now a Docker image available for the OSM Analytic Difference Engine. This images contains the tracker with a ‘region of interest’ polygon covering Denmark and an Nginx frontend.

Find the source and more information about the OSM Analytic Difference Engine here:

https://github.com/MichaelVL/osm-analytic-tracker

See a running instance here:

https://osm.expandable.dk/

I have put OSM Analytic Difference Engine on github. In short its a backend for a live service providing real-time insight into edits within a region of interest. Special focus has been made to analyse the changesets and provide a concise description of what has changed.

Some of purposes of this engine:

• Prof-of-concept for an improved changeset-info service (improved compared to looking up changeset details on http://openstreetmap.org)
• Provide insight into changes in your area of interest
• Improve team spirit of a regional OSM team/task-force.
• Quality insurance through peer review
• Learning by seeing how other make edits to your region of interest.

The service is available as a web-service and provide three different information elements:

• An overall summary with a overview map containing bounding boxes of recent edits
• A list of changesets with analytic details
• A visual diff for the changes of each changeset (try the ‘VisualDiff’ link on each changeset)

Example of the analytic details:

Find it here:

OSM Analytic Difference Engine for Denmark

OSM Analytic Difference Engine on github

Keeping OSM updated and in sync with the real (changing) world is in my opinion one of the key challenges for OSM. Adding new roads and POIs is fun - keeping them up to date is less so!

Have you ever come across POIs or roads and made a mental note to yourself to check later in e.g. JOSM if they are on OSM and tagged correctly? I have, and unless I document in detail what I am seeing with photos, there is a good probability that I miss some essential details. Also with photos, I often have lots of photos recording stuff that is already correctly tagged in OSM. Thus the hit/miss ratio is becoming smaller and this will continue as OSM mature.

To help myself spotting differences between the OSM database and the real world I wrote a small Android app that can display OSM data for nearby objects. With this its easy and efficient to be on the lookout for OSM updates.

The app looks like this:

and it can be found on google Play: OSMfocus

I’m hoping this will be useful for others and that it will results in more OSM updates.