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(1/3) Dear Mastodon community,

we need your expertise and support:

As you may have heard, we're working on several tools to counter and facilitate .

One of them is called *Spot*. It's basically an AI-driven natural language interface for geospatial searches in ().

I.e. you ask the tool about...

(2/3) ...an info pattern like "traffic lights in Berlin that are located no more than 100m from a metro station and no more than 50m from a pharmacy" – because you have this image of a political rally you want to verify.

*Spot* will then show you the matching results in a nice interface. No coding needed, just plain English.

Now in order to come up with better *Spot* results, we need people who know the tag really well – and can help us navigate it in an efficient way.

Many thanks for your favs and boosts and most of all: your helpful comments, links, and tips! We'll check out all of them. And we'll get back to individual users if there are more specific questions. Cheers!

@dw_innovation hi! Incidentally I gave two talks at CCC, one about advanced #OSM usage and one about #OSINT, which also features exactly what you're doing with this tool (using an example from one of Julia's quiztime posts ;) I regularly do this kind of research using overpass.

This tool sounds great! Are you aware there's a very similar tool from @Bellingcat? github.com/bellingcat/osm-sear

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GitHubGitHub - bellingcat/osm-search: A user friendly way to search OpenStreetMap data for features in proximity to each other.A user friendly way to search OpenStreetMap data for features in proximity to each other. - bellingcat/osm-search

@dw_innovation The JOSM and iD presets are a good source for commong language to tag mapping. The Name Suggestion Index might also help.

Feel free to reach out via Mastodon or Email. You can find my address and the talks on my website.

Really looking forward to this tool! 2/2

@jomo @dw_innovation @Bellingcat Can you link your talks? I would be interested.

Some issues I could think of here is the use of ChatGPT, you would probably want this a little more in-house. Also to be dependable for OSINT, you would need some sort of fuzzy matching, where not all features are a must or could deviate from what you described. Lastly some sort of inclusion of historical changesets may be great, since places change all the time :)

@dw_innovation this looks like a fantastic use of ml... assist in a task and allow the user to verify the results. I can see this being an incredibly useful tool if you can get it to where it needs to be.

@dw_innovation I need this like I need two holes in my head. This looks well worth engaging with, on the right infrastructure. Thank you for the paper reference.