Hi and welcome everyone. I am here today to speak to you about a little bit about Wikimedia's
open source ecosystem. So I assume all of you know what Wikipedia is and maybe some
of you know that it runs on a software that is called MediaWiki. So all the Wikis run
on this software but there's also tens of thousands of websites around the world that
use this. A very cool example is NASA is using it for some other projects. But this is sort
of the core of Wikipedia and the other projects and it's of course something that is open
source that anyone can contribute to but it's not what I'm going to be talking about today.
Because surrounding Wikipedia in all the other projects there is a huge ecosystem of software
tools. You can think of these as like third party integrations. People build bots that
do edits on Wikipedia. That fight vandalism. There are machine learning algorithms. There
are pipelines for data that then go to research purposes. There's a lot going on. So I'm going
to be talking about this part. Just a quick word about me. I'm a software engineer with
a technical engagement team. You can see we're part of the technology department and our
team is kind of split into parts. We have the cloud services team, SREs and engineers
that build services and platforms for all these tool developers. Then we have developer
advocacy. They do a lot of things. They are writing documents and running outreach programs
and doing everything so that our technical contributors can build cool stuff on top of
our platforms and content. So just to give you an idea of the scale of this, we have
over 300,000 editors that contribute to Wikimedia projects every month. Wikimedia comments,
which is the project that is for free, media files, videos, images, so on. There are now
over 90 million media files on there. And we have 1.7 billion unique devices that access
Wikimedia against statistics for every month. So some of you may recognize at least some
of these projects. Of course, Wikimedia is the flagship. There are other ones like Wikidata,
comments that we just mentioned, Wiktionary, and many more. So yeah, we're going to take
a look at these tools, ecosystems that I mentioned in the beginning, and we're going to start
from Wikimedia. This is the thing that most people know about us. And from there, yeah,
we're going to explore the tools that are community-created software that interacts
with and contributes to Wikimedia projects in some way. An example here is PyWikibot.
It's a framework for building bots. So if you have a wiki and you want to run some kind
of bot that does something, some type of edits, you would very likely use PyWikibot as a framework
to develop this. From the tools themselves, we're going to go and have a look at the services
and the platforms that support them. And we're going to start with an example of a couple
tools and how they actually integrate with one of the projects. So this is a wiki project
called Women in Red. And a wiki project is a group of users on Wikipedia that decide
that they want to work on something specific. They come together to work as a group. And
in this case, it's to fight the content-general gap. So they observe that only around 15 percent
of English Wikipedia biographies were about women. And as of the 23rd of January this year,
they have managed to take this number up to around 19.45 percent in about seven or eight
years. And so where does this very precise statistic come from? You can see mentioned
here in red, it's something called human-niki. And so this is what we would call a tool.
And in this case, this is a dashboard. It provides statistics about the gender gap on
all the Wikipedia projects. And you can see here that female content is the orange part
and then the rest is male. And if you go to this website, you can see it in a more granular
way by country, by project, by date of birth, and so on.
So if you want to contribute to this project, an easy way to do it is to go to this Wikipedia
project site and you can see different lists that have been curated. For instance, here
we can see female activists. So you can get a list of all the female activists. And there
are many, many categories like this. And some of these lists are curated by humans, but
most of these lists actually come from a bot that's called ListeriaBot, which curates,
which makes queries on Wikidata, which is another one of the projects. You can think
of it like a huge knowledge graph that you can query using a similar language to SQL.
It's called Sparkle. So yeah, you can use Wikidata to get lists with very high granularity.
You can have activists from Germany or activists from Germany that were born after a certain
date. And so this is what ListeriaBot does.
So we have seen two different tools. One was a dashboard, one was a bot. And there are
thousands of these tools. There are thousands of maintainers. And we're going to take a
look at how we sustain these people. So I mentioned that my team is the cloud services
team. And what we do is we provide hosting. We provide compute virtual machines. We provide
data services for all these tools to function. And so again, to give you an idea of the scale
of this, 30% of all the edits on Wikipedia as of 2020 were made by bots hosted on our
services. For Wikidata, that number is a little bit higher. It's around 50%. So just
to make you aware that this is a quite important part of the ecosystem.
So I mentioned there are thousands of tools. And as of a couple of years ago, we now have
a catalog where you can browse and search and find the tool you need for your project
or if you are a tool maintainer, you can add it here so that people know it exists. Then
what you see here are lists that have been curated. We have something called the Coolest
Tool Award. So if you look down, you can see that Humaniki was one of the award-winning
tools in 2021. Some of you may recognize this as a Jupyter
Notebook. So this is a Jupyter Hub deployment that we have that is directly integrated with
all of our data services so that people can access dumps, they can access Wikireplicas,
they can access a lot of things that otherwise would be gigabyte and gigabyte and gigabyte
of data they would have to download onto their own computers.
Another tool is called Query. It's a public query interface for Wikireplicas. Wikireplicas,
I didn't mention it, there are replicas of our production databases. And the cool thing
about this is that all the queries are public so people can actually search and see other
people's queries and be inspired or if you're not very good with SQL, you can adapt someone's
query to your needs. Here you can see a specific query.
So these services are still tools that serve this ecosystem but we also need somewhere
to host them. So though we have a platform as a services offering, it's called Toolforged.
It's not quite as fancy as Heroku or DigitalOcean or anything of this sort. If you look closely
you see that you have to actually SSH into it. But it's still very powerful and very
convenient for our users. It integrates again with data sources and it has managed databases,
a elastic search cluster that everyone can use without having to maintain all these systems
themselves. So yeah, the back end here is Kubernetes.
Then for more complicated projects, some projects need more compute for instance. We also have
a CloudVPS offering so that people can spin up their own virtual machines and basically
do what they want on them. So this runs on top of OpenStack.
And how could one get involved with this? So it's possible to get involved in any of
these layers, either as a tool maintainer or as maintainer of any of these platforms.
And that's kind of the thing I wanted to highlight a little bit today is that this is kind of
a unique opportunity to actually contribute to platform and to infrastructure. We have
people that work with our team and they are on our IRC channels and they push patches
just like everyone else and if you don't know you would think they are just another software
engineer on the team. And I asked some of them why, what brings you here? And of course
many of them associate with their free knowledge and free knowledge movement and open source
and all of that. But many also said that this is a unique opportunity to actually play with
things like OpenStack or Terraform or Kubernetes in a situation where actually you have real
traffic and real users which is something that is kind of very difficult to do at home
and there are not many other projects where you would have this possibility.
So some ways to get involved. We have several outreach programs. We have Outreachy which
is an internship that runs twice a year. It's targeted more towards underrepresented demographic.
Google summer code that's once a year and both programs are open to anyone so you don't
have to be a student. You could be someone who is changing careers or doing some kind
of a letter move. Google summer code has also become more flexible. It's not just summer
anymore. There are shorter projects. There are longer projects. So that could be a way
to get involved and get some kind of hands-on mentorship. Another way would be to come
to the Wikimedia hackathons. We have one in Athens in May this year and then one is
part of Wikimedia that takes part in Singapore that is in Singapore in August. And of course
if you are brave you can just dive right in because everything we do is open and it's
out there on the internet. Documentation of course but just even our project boards and
fabricator it's a collaborative software for task management and such. So if you go there
you would see that there is a huge variety of tasks. You can see the work boards of different
teams at the foundation. You can see volunteer led projects and projects where people work
together alongside each other. So a way could be simply to find something that interests
you and look at the documentation and then come on our IRC channels and contact us and
that's it. So yeah I have added some links which can be helpful to get started. And you
are of course free to just reach out to me. I had my Twitter handle on the first slide
and my slides are published on the website. We have 45 seconds for questions. Thank you.
Thank you.