The Wikibase registry was one of the outcomes of the first in a series of Federated wikibase workshops organised in partnership with the European research council.
The aim of the registry is to act as a central point for details of public Wikibase installs hosted around the web. Data held about the installs currently includes the URL for the home page, Query frontend URL and SPARQL API endpoint URL (if a query service exists).
During the workshop an initial data set was added, and this can be easily seen using the timeline view of the query service and a query that is explained within this post.
2017 has been a great year with continued work at WMDE on both technical wishes projects and also Wikibase / Wikidata related areas. Along the way I shared a fair amount of this through this blog, although not as much as I would have liked. Hopefully I’ll be slightly more active in 2018. Here are some fun stats:
- 7,992 page views
- 5,350 visitors
- 4 total posts (that’s terrible, but its April 2018 now and I already have 6 under my belt)
- 1840 words
Top 5 posts by page views in 2017 were:
- Guzzle 6 retry middleware
- Misled by PHPUnit at() method
- Wikidata Map July 2017
- Add Exif data back to Facebook images
- Github release download count – Chrome Extension
To make myself feel slightly better we can have a look at github and the apparent 1,203 contributions in 2017:
It’s time for the first 2018 installation of the Wikidata Map. It has been roughly 4 months since the last post, which compared July 2017 to November 2017. Here we will compare November 2017 to March 2018. For anyone new to this series of posts you can check back at the progression of these maps by looking at the posts on the series page.
Each Wikidata Item with a Coordinate Location(P625)will have a single pixel dot. The more Items present, the more pixel dots and the more the map will glow in that area. The pixel dots are plotted on a totally black canvas, so any land mass outline simply comes from the mass of dots. You can find the raw data for these maps and all historical maps on Wikimedia Tool Labs.
Looking at the two maps below (the more recent map being on the right) it is hard to see the differences by eye, which is why I’ll use ImageMagik to generate a comparison image. Previous comparisons have used Resemble.js.
While working on a new Mediawiki project, and trying to setup a Kubernetes cluster on Wikimedia Cloud VPS to run it on, I hit a couple of snags. These were mainly to do with ingress into the cluster through a single static IP address and some sort of load balancer, which is usually provided by your cloud provider. I faffed around with various NodePort things, custom load balancer setups and ingress configurations before finally getting to a solution that worked for me using ingress and a traefik load balancer.
Below you’ll find my walk through, which works on Wikimedia Cloud VPS. Cloud VPS is an openstack powered public cloud solution. The walkthrough should also work for any other VPS host or a bare metal setup with few or no alterations.