In T222089#5225239, @Krenair wrote:

wmflabs.org should probably be a whole separate ticket.

@Ecritures misschien wel interessant, maar ik zou er eerst even in moeten duiken.

@Ecritures ik heb hier wel aan gewerkt, maar ik kan me niet meer zo heel goed herinneren of het iets heeft opgeleverd. Wat mij betreft mag het van het bord.

It would also be really nice if this could export to either GeoJSON or TopoJSON, because it makes it a lot easier to integrate query results in visualisation tools. For example, Vega-lite maps.

@valhallasw thanks for trying out a couple of things, and indeed confirming that using the location won't work. I was pretty confused by the HNO / HNE columns as well, unfortunately there doesn't seem to be any kind of description of what those fields actually mean.

@valhallasw that could be an interesting option, but would it also work if there are many monuments that are close to each other, like in the centre of Amsterdam?

When looking closer at this dataset i doubt it's going to be very useful. There's a couple of reasons for that:

@1Veertje: i downloaded your SQL files and converted them to a CSV dump (see attachment). However, i think maybe something went wrong because i don't see many improvements. Many of the streetnames seem to be truncated because of a VARCHAR limit, e.g. rijnr 8895 now has 'Burgemeester van Dobben de Bru' instead of 'Burgemeester van Dobben de Bruijnstraat'. i've also included a Jupyter Notebook with the zip file, maybe you can see for yourself if i missed something.

And the current code (now a nagfree script is located here

Here's a video of the current (very basic) prototype: https://www.youtube.com/watch?v=e59qKhin1Mg&feature=youtu.be

Try this: https://meta.wikimedia.org/wiki/PetScan#Get_the_sitelinks_for_a_certain_project_from_a_SPARQL_query

Not quite sure how useful this is. Matching might be quite difficult because the archives are referring to many different things (people, organisations). I guess manually matching this might be faster than trying to scrape it and trying to automatically match archives / wikidata items.

@S9a8m let me know if you need some assistance with scraping, i can help.

@Aklapper Yes, most definitely. Thanks!

@Pigsonthewing sure thing. This should now work.

Here's something i wrote: https://www.wikidata.org/wiki/User:Husky/ifff-viewer-link.js

I've removed the tool from the Toolforge servers, and removed all the references from other places in my tools. I don't think it really worked anyway. For anyone who's interested: the code for this project is still available as an old commit on my Github: https://github.com/hay/wiki-tools/tree/b760c5607e5aa7b05d83ef02e7d03259619e9ab8/public_html/streetwiki.

@Lea_Lacroix_WMDE what i basically want is an option to use the wbgetentities method with an option to query by label in the same way you can query ids or titles. I was working on matching a set of street names to WD items, i could of course do an individual query for each street using wbsearchentities, but then i can only query one item at a time. So basically i could imagine something like:

Okay, so @Krinkle helped me with getting the old SVN dump into my Github repo, and i hacked the code really ugly and got it working again on the most recent version of WordPress.

In T187896#4213200, @Husky wrote:

@Aklapper the code is actually still on my Github repo:
https://github.com/hay/photocommons
But i'll attend the session anyway. Looks interesting!

@Aklapper the code is actually still on my Github repo:

@matej_suchanek i've tried that, but unfortunately searching by label using SPARQL is far too slow. Queries time out or take forever.

@matej_suchanek both of these options are not useful, i want to query by label, not by ID.

Note that the current spec is available here:

Hey,
thanks @Dereckson for pointing me towards this discussion, didn't even know there was this discussion on upgrading the tool directory.

Hey @Deskana, i'm wondering why you reassigned this task to 'lowest priority'. Thanks!

@Mholloway: cool! Thanks!

The screenshots look really promising! Any chance this will also make the iOS release?