Please, the longer the project.
Hello everyone. My name is Yelanda Pensa. I'm a senior researcher at SUP, which is a Swiss
University at the Institute of Design. But I'm also an active member of Wikipedia, being
contributing since 2006, I've been chair of Wikimedia, Italy, and now I'm also a national
coordinator of Glamso, which means that I spend a lot of time selling in cyclopideas
around as a volunteer. And this is a tool about Wikipedia. I don't think it's necessary
to present Wikipedia. This year is 25th anniversary. It is an open infrastructure, open content.
It is also a website that serves the open science and the open Glamso. It is also an
open education on the resource. So I think it's a good symbol of the open in general.
And the reason why we're developing this tool is because I spend a lot of time working
on account content. And I started by contributing to contemporary African art. And one
of the problems with Wikipedia is that it's very difficult to grasp what a topic is about.
How is the situation of a topic? You get an access to articles once at a time. And when
you work on project, you get list of articles. But it's very difficult to get a sense of the landscape.
So how a topic is documented on Wikipedia? What is the quality of their content? Is it
reach or not? So I've been testing some visualization in some research project, I've been promoting.
So one of the first visualization that we've been working on was to transform 100 articles
related to the South African school system, and seeing how we can show how those articles
are on Wikipedia and how we change them by contributing and improving them.
Another visualization tool that I've been developing with Giovanni Perfeta was created in
2020 during the pandemic. In Italy, all schools were closed. So we were thinking, okay,
Wikipedia is an open educational resource tool. But how is actually the quality of that content?
So we did a research to define list of articles related to the school system. We looked at the
content related from primary school to high school on different subject, looking at high school
books and different books. We organized topics related to disciplines, and we look at how
those articles were in different years. So we started in 2020. We involved the community to improve
articles, and we checked how those articles change throughout time. So what you see in this visualization
is basically each article is a bubble. The dimension of the bubble tells you the dimension of the
article. The dot inside is the dimension of the inchipic, so the lead session, the first part of the
article, which other time was of course a lot red, and also we did a focus group in which also
teacher and students identified as very important. And also you have errors got each article in details
and see how it changed through time, and you can organize a content according to different categories.
So the idea of this visualization was really to identify how the landscape of certain article presented
and also to look at issue that could be fixed quite easily. So for example, if an article was already
mentioned in clean up tags or had no images, so identify what could be the volunteers do quite quickly.
So this project was also replicated in Uruguay, so they used the same the software to
adapted and to look at articles related to the Uruguay end school system. So after this experience,
we decided to create a tool based on this experience and a tool that can be applied to any
set of article, and we decided to focus with the research on climate change and sustainability,
because of course, it's an important topic for everyone and improving content on Wikipedia
can have obviously a broader effect. So we started working on the visualization and at the same time,
Wikipedia education, which is a foundation in the United States that works a lot with classrooms
and school books, was at the same time working on this visualizing impact tool that was already
working on the impact of contribution by students. So we decided to join the two project and work
together and then take a little break. So the idea of the visualization is really to serve
volunteer, to facilitate their work, to allow them to identify what is the priority,
which article they should focus on, but also create a landscape that can be useful for researchers
to identify topic, understanding how a topic is described and how is the treated on Wikipedia,
and also facilitating contribution by Glamso, analysis by journalist and contribution by teachers.
So at the moment, we have a pilot tool that you can find online, so it focuses only on climate change,
but in reality, the tool can extract data from Wikipedia from categories on Wikipedia,
and it already shows articles and the situation. The reason why the first visualization is
you see all the bubbles squeezed on the top is the Donald Trump problem. So of course,
the tool created a system to erase them, so that is actually possible to see the properly
the articles. It's obvious that our first step, but one of the issues that are obviously
we're facing now is that at the beginning, the idea was to focus on the number of visualization,
but today things are changing, of course, with the machines that are visualizing Wikipedia more
than humans. So we are changing some of the feature focusing more on contributors and see
which are the articles that have more contributors. We've been also involving, well, of course,
you find the new or the data and the software online. At the moment, we are still in the
co-designing phase, so some of the visual, we are working on the first visualization, but we will
be comparing languages. The project at the moment focuses on four languages, so Italians,
Spanish, English, and French, and we're also looking at how changes that have been made from one
through time. So the next visualization, which will be the Wikimedia Communities, so you can
select articles according to their staff, with the introducing the fact that at the moment I'm
also working on trying to bring to first them in 2029, the entire open community. So Wikipedia,
open science, open educational resources, creative commerce, open street map communities,
so try to have a joint event in 2029. Thanks.
Please.
Thank you for the question on the type of visualization, so it's so hard and not saying you need to be
back to the future, it's a squeeze of the distribution, and you can describe the
challenges to the applied plans for different visualization, or is this one
sitting your needs for now?
No, one of the, yes, so at the moment the question is about the different visualization that we're
planning. No, there are different kind of visualization, this one is the first
direction that we're working on. The emphasis will be also done on comparing how the initial
set of article was presented and how changes produced a different visualization.
This is something that is very interesting to satisfy volunteers, also to give feedback to the
Wikimedia Communities, because a lot of a Wikimedia Communities are managed by one person or two people,
so the fact of having a feedback from a visualization is also important to encourage them,
but is also interesting for fundraising for affiliates, because they can present a funders,
what actually they did by organizing events, by contributing to Wikimedia.
It is, so the aspect of the before after is probably what it will transform.
Also, another issue is how to create visualization that can be targeting different people,
so this is something that we are browsing. At the moment where we started with this catch,
we have some more sketches in particularly focusing on comparing languages, which is also something
we're focusing on for languages to not make it huge, but we are designing the tools that you can
be broadened. And also consider that this is a dashboard, so Wikimedia
education already manages a dashboard, in particular, to manage events in the community.
So the dashboard will be included within their work, so people will be able to apply it to their needs,
and you can serve really individuals and more projects.
Yes, please.
Are there any more visualizations that are more focused on the users rather than the
editor, such as you, the visualization that you need to coordinate with the user.
The visualization focus more on the behind the scene of Wikimedia, so we don't focus much on
the users of the readers. In particular, now with the change on AI, this is also an issue.
One of the things that we are considering is also how to look at how to identify in articles,
different styles, for example, that could be adapted and could be improved, also according to readers.
But it's true that for example, monitoring the impact of the article is something that a lot of
researcher would love to know more, but there is always a, it's also a tricky issue, because for
example, analyzing a discussion page, we show the size of the discussion page. If an article is,
for example, a controversial, but we don't explore the discussion page and the dynamics,
so also for privacy issues, and so it's something that we are not really putting on,
on front of it. So we're more focusing on the work behind the scene to contribute and to improve content.
Thank you.