2nd February 2017
The women relay flower ceremony(Maiken Sandberg, CC BY-SA 4.0).
In front of and during the World Orienteering Championships last year I was a member of the media team. My objective was to write (almost)real time route analytics and comments during the races.
A few weeks before the event one of the persons responsible for outreach asked me if I could update some of the outdated articles on the Swedish Wikipedia. I said “sure”. I could need some more experience actually editing Wikipedia.
Prior to this the Swedish Orienteering Federation had updated their site(“big event, lot of exposure - lets update our site”). Guess what, they broke all their links.
Once my bot was done updating them all I could start editing. When the championships started most of the relevant biographies was up to date.
At this point I started to improvise a small project, I convinced a key member of the media team that it would be a good idea to publish images taken by the media team under open licensing so they could be used on Wikipedia. Because it was so close upon the event and so improvised I had to chat with all of the different authors and import the images from the official image gallery on my own.
I did the last batch upload just a few days ago and now I have uploaded more than 240 images(including logos), not a large number but for a one man project reaching beyond what I usually do, I’m happy with the result.
There is of-course a lot I would do in another way next time(when it’s not improvised). At least next time I will be able to give an example of a media team at a major sport event which worked with Wikimedia Commons.
Checkout the World Orienteering Championships 2016 category to have a look at the images.
Tove Alexandersson running towards the gold medal during the middle distance(Klas Bringert, CC BY-SA 4.0).
12th December 2016
Recently there has been multiply discussions about the connections between Wikidata and OpenStreetMap. Many Wikimedians has been concerned about the one way connection through the wikidata tag over at OpenStreetMap and the lack of a way to find the corresponding OpenStreetMap element from within Wikidata.
The easiest way in the past has been to head over to Overpass Turbo and query for the Wikidata id. I would say that even for OSM folks and SparQL hippies it’s a bit of an annoying process.
Because of this I created a Wikidata UserScript a while ago witch adds a link to the OpenStreetMap Element which has the Wikidata id referenced.
You can try it out by adding the following line to your common.js file:
importScript('User:Abbe98/osm.js');
Behind the scene it’s using the Overpass API for looking up the OSM element, it’s source is available over at Github.
28th November 2016
There is tons of georeferenced maps over at Wikimedia Commons and the Wikimaps Warper and earlier this year we added the ability to retrieve the georeferenced data from the Warper by the Commons page ID. This allows developers and others writing UserScripts and Gadgets to fetch Warper data directly from Commons.
So a while ago I wrote a gadget which would embed any georeferenced map directly on it’s Commons page. To install it import it by adding importScript('User:Abbe98/warper-viewer.js'); to your common.js file.
Then visit a georeferenced map, here is a few suggestions:
It’s quite addictive browsing the maps.
12th November 2016
A few weekends ago Jan Ainali, Lars Lundqist, Ulrika Nilsson, David Zardini and myself attended the Hack4Heritage hackathon in Stockholm. We ended up creating the site Kyrksok.se, a directory for churches in Sweden.
Kyrksök links together various sources such as Wikipedia, Commons and Bebyggelseregistret and makes their content more accessible and discoverable.
Setting up a site and display content is never that interesting or much of a challenge not even if there is content from a lot of different sources as long as there is links between them.
Guess what,
there was no such links,
Luckily Wikidata is a perfect place to link all the datasets together.
Actually most of the time spent on Kyrksok was spent on linking Bebyggelseregistret to Wikidata and on the existing data, mostly common tasks such as normalizing labels and verifying existing statements and links.
Once all the third-party URIs was in Wikidata, we could fetch a list of churches which had the required data using Wikidatas SparQL endpoint(Kyrksok query: visualized/source).
By using Pywikibot and KSamsok-PY we could then index data from all the data sources we needed without much work. Everything was indexed to a SQLite file. That’s mainly it, we had by then a great dataset indexed form a bunch of different sources.
We then fired up a rest API(Python/Flask) for this SQLite file with both search/bounding box methods, still this API is made in less the 80 lines of code. Just check it out.
The best thing about this is that this approach can be applied to any idea, the data in Wikidata is extremely diverse. Wikidata has become a incredible important source for many of the project I’m involved in including Biocaching.
Go ahead and check out all the Kyrksök repositories over at Github.
(Kyrksök = “church search”)
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