Hello everyone,
A few weeks ago, we announced the course on the learning platform,
WikiLearn, on how to upload and edit files on Wikimedia Commons using
OpenRefine: *OpenRefine for Wikimedia Commons: the basics*
<https://learn.wiki/courses/course-v1:Wikimedia-Foundation+WMF_GLAM001+2023/…>
.
Today, we are happy to announce two translations of the course: Spanish and
French!
- OpenRefine para Wikimedia Commons: conceptos básicos
<https://app.learn.wiki/learning/course/course-v1:Wikimedia-Foundation+WMF_G…>
(Spanish
/ Español)
- OpenRefine pour Wikimedia Commons : les bases
<https://app.learn.wiki/learning/course/course-v1:Wikimedia-Foundation+WMF_G…>
(French,
Français)
This course can be easily translated into other languages (more about the
translation process here
<https://studio.learn.wiki/meta_translations/discover_courses/> and here
<https://commons.wikimedia.org/wiki/File:Tutorial_on_how_to_translate_course…>).
More translations, such as Italian, Portuguese, and Basque, are being
worked on.
Just like the English course, the Spanish and French versions are available
at any time, for free. You only need a Wikimedia account and the course can
be followed at your own pace, with computer-graded exercises. A certificate
is awarded at the end and an average of 6 to 8 hours is needed to complete
the course.
Please, feel free to share these translations with people who speak these
languages and who you think might be interested in learning more about
OpenRefine or Wikimedia Commons.
Thanks, Carla Toro and Reda Kherbouche, for their amazing work translating
these courses!
Best,
Giovanna
Giovanna Fontenelle (she/her)
Program Officer, Culture and Heritage
Wikimedia Foundation <https://wikimediafoundation.org/>
Hello all!
We’ve been moving forward on the WDQS Graph Split [1], time for an update!
We have new documentation to help the migration to the split graph:
* Federation limits [2]: Explanation of the limitations of the SPARQL
federation as used on the graph split. This might help you understand what
is possible and what isn’t when you need to federate the main WDQS graph
with the scholarly subgraph.
* Federated queries examples [3]: This document explains how to rewrite
queries to use SPARQL federation over the split graph. We’ve taken a number
of real life examples, and we’ve rewritten them to use federation. While
rewriting queries is not always trivial, the examples that we tried are all
possible to make work over a split graph.
We have been reaching out to people who will be impacted by the graph
split. In particular, we have been having conversations with community
members close to the Scholia and Wikicite projects. In that context, we are
realizing that our initial split proposal (moving all instances of
Scholarly articles to a separate graph - ?entity wdt:P31 wd:Q13442814) is
not sufficient. We have prepared a second and last proposal that will
refine this split to make it easier to use. See "WDQS Split Refinement" [4]
for details. We are open for feedback until May 15th 2024, please send it
to the related talk page [5].
While we refine this split, we are starting work on the implementation of
the missing pieces to make the graph split available. This includes
modifying the update pipeline to support the split and better automation of
the data loading process. We are also working on a migration plan, which we
will communicate as soon as it is ready. Our current assumption is that we
will leave ~6 months for the migration once the split services are
available before shutting down the full graph endpoint.
We need your help more than ever!
If you have use cases that need access to scholarly articles, please read
"Federation Limits" [2] and "Federated Queries Examples" [3], rewrite and
test your queries, and add your working examples to "Federated Queries
Examples" [3].
Send your general feedback to the project page [1].
On a side note, WDQS isn’t the only SPARQL endpoint exposing the Wikidata
graph. You can have a look at "Alternative endpoints" [6], which lists a
number of alternatives not hosted by WMF, which might be helpful during the
transition.
Thanks!
Guillaume
[1]
https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/WDQS_graph_split
[2]
https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/WDQS_graph_spli…
[3]
https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/WDQS_graph_spli…
[4]
https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/WDQS_graph_spli…
[5]
https://www.wikidata.org/w/index.php?title=Wikidata_talk:SPARQL_query_servi…
[6]
https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/Alternative_end…
--
*Guillaume Lederrey* (he/him)
Engineering Manager
Wikimedia Foundation <https://wikimediafoundation.org/>
Hello!
We are happy to announce that there is now a free and publicly accessible
course on the learning platform, WikiLearn, on how to upload and edit files
on Wikimedia Commons using OpenRefine: *OpenRefine for Wikimedia Commons:
the basics*
<https://learn.wiki/courses/course-v1:Wikimedia-Foundation+WMF_GLAM001+2023/…>
.
OpenRefine <https://meta.wikimedia.org/wiki/OpenRefine> is a free
data-wrangling tool that can be used to process, manipulate, and clean
tabular (spreadsheet) data and connect it with knowledge bases, including
Wikidata and Wikimedia Commons.
This online course is available at any time, for free. Anyone with a
Wikimedia account can enroll with the click of a button. It can be followed
at your own pace, with computer-graded exercises. A certificate is awarded
at the end to those who complete the course.
The training is suitable for Wikimedians, Wikimedia affiliate staff, and
partners (e.g. GLAM staff and Wikimedians in Residence). Accomplishing the
course should take an average of 6 to 8 hours.
This course was developed as part of the Wikimedia Foundation's training
and sustainability grant to OpenRefine
<https://commons.wikimedia.org/wiki/Commons:OpenRefine/Training_2023-24>.
It is currently available in English and can be easily translated into
other languages (more about the translation process here
<https://studio.learn.wiki/meta_translations/discover_courses/> and here
<https://commons.wikimedia.org/wiki/File:Tutorial_on_how_to_translate_course…>).
Translations for this course in French, Spanish, and Portuguese are being
worked on and will be available very soon.
Please, feel free to share this course with people you think might be
interested in learning more about OpenRefine or Wikimedia Commons, who are
part of your network, in groups, social media, or any other places.
Thank you!
Best,
Giovanna & Sandra
Giovanna Fontenelle (she/her)
Program Officer, Culture and Heritage
Wikimedia Foundation <https://wikimediafoundation.org/>
Interview Request - University of Cambridge Study
My name is Aarshin Karande and I am a student at the University of Cambridge enrolled in the MSt, AI Ethics & Society program administered by the Leverhulme Centre for the Future of Intelligence<http://lcfi.ac.uk/>. The summative coursework for this program is an original research project submitted through a dissertation.
My dissertation will examine the uses of AI on Wikipedia and how Wikipedians are implicated by them. I am inviting Wikipedians to participate in 45-minute- to 65-minute-long interviews. In these interviews, we will discuss:
*
Your background as a Wikipedian
*
The work you do on the platform
*
Your observations about how Wikipedia has changed over time
*
Your comments about AI
*
Your ideas about what AI means for Wikipedia
*
Anything else you may find relevant and important to this topic
This project is looking for 10 participants. Interviews will be conducted throughout April 2024 remotely via Zoom. Participants' identities will be anonymized to remove any personally identifying information.
If you would like to participate in this study, please message me at ak2471(a)cam.ac.uk. For further information, please refer to the participant information sheet<https://drive.google.com/file/d/1UHk4eexdkx6NSi_BWB0nAo_ZqnOAP-RN/view?usp=…>. If you have any questions or concerns about this project, please message me at ak2471(a)cam.ac.uk.
Cheers,
-Aarshin
Aarshin Karande
MSt Candidate, AI Ethics & Society
Hughes Hall, University of Cambridge
email<mailto:ak2471@cam.ac.uk> • phone<tel:14257498056> • linkedin<http://www.linkedin.com/in/aarshinkarande> • website<http://www.aarshinkarande.com/>
Hi Everyone
I looking at what is possible during Wikimania and any proposal people have
so we be a bit more coordinated in our submissions.
I submitted three proposals so far;
- One the history and how to use QI
- One looking at QI role in the future and start discussion on rule
changes, obviously I'll take the collected information and then use it to
start on Commons proposals
- The third is a good old photowalk, with the kick that it starts as
session, or starts at a hotel and finishes as a session at the venue to
encourage greater participation. This is in preference to an ad hoc last
minute event where ever or when we can fit it in
All of these proposal are open to Collaboration if people want to.
--
Boodarwun
Gnangarra
'ngany dabakarn koorliny arn boodjera dardon nlangan Nyungar koortabodjar'
Dear friends
A few days ago, in a diff article (1), we told you the story on how we
improved the ISA Tool (2) during a co-organized Hackathon (3).
Key outome is... we are happy to announce that a new version of the ISA
Tool is now available on toolforge for you to use. Whilst the tool would
still welcome your technical attention, we were able to fix critical
bugs and to implement some improvements.
After nearly a year dormant, ISA is back !
*
What is the ISA Tool ? *
ISAis a fun, multilingual, mobile-first/microcontributions/tool, that
makes it easy for (groups of) people to addstructured data
<https://commons.wikimedia.org/wiki/Special:MyLanguage/Commons:Structured_da…>to
images on Wikimedia Commons.
With ISA, you can choose a pre-defined set of images on Commons and then
ask contributors to 'tag' these with multilingual structured metadata.
Points are counted for each contribution, and therefore it is possible
to organize 'tagging' or microcontributions competitions or challenges
with ISA. Or you can compete against yourself :)
ISA was originally built to provide better multilingual and structured
descriptions of Wiki Loves Africa images (4). But it is also developed
to be useful to all of the Wiki Loves X competitions, and eventually
ended up being meant forall media fileson Wikimedia Commons. More info
here: (5)
*Campaign #300*
To celebrate both the relaunch AND Women's Rights Month, and to
demonstrate how the ISA tool works, we are launching an ISA campaign
about Women in Art.
This is happening here : https://isa.toolforge.org/campaigns/300
Your contributions, small or big, are welcome to improve the
category:Women in Art
*Create your own campaigns ?*
You are welcome to create your own campaigns (or join older ones). Just
make sure to log-in and you are good to go.
A piece of advice though... make sure not to create very big campaigns
with thousands and thousands of images. Toolforge does not digest huge
sets very well.
500 is ok. 8000 is ok. 200 000 images... is beyond its capacity. We are
still testing and improving. If you see anything weird or broken, please
report here (7)
Best regards
Anthere
(1) the diff article :
https://diff.wikimedia.org/2024/03/13/the-triumph-of-wiki-mentor-africas-fi…
(2) the tool : https://isa.toolforge.org/
(3) the January hackathon :
https://meta.wikimedia.org/wiki/Event:Wiki_Mentor_Africa_Hackathon_2024
(4) the tool page on Commons :
https://commons.wikimedia.org/wiki/Commons:ISA_Tool
<https://commons.wikimedia.org/wiki/Commons:ISA_Tool>(5) opportunity to
remind that Wiki Loves Africa is happening right now :
https://commons.wikimedia.org/wiki/Commons:Wiki_Loves_Africa_2024
(6) women in art campaign : https://isa.toolforge.org/campaigns/300
(7) phabricator: https://phabricator.wikimedia.org/project/profile/3981/
Dear Community members,
I hope you're doing well. We're excited to invite you to the upcoming Wiki
Loves Folklore 2024 Office Hour Part Two, where we'll be discussing how to
make our jury processes better.
Event Details:
- Date: March 2nd, 2024
- Time: 4:00 pm UTC https://zonestamp.toolforge.org/1709388000
- Where: Zoom
https://us06web.zoom.us/j/88637039784?pwd=AIGFVXsrMPB2piCVZ17acvacHuaZgR.1
What's Happening:
-
Introduction by Isaac Chabota Kanguya (Communication Officer): Isaac
will start things off with a quick 10-minute talk. He'll explain why having
fair and inclusive jury procedures is important for Wiki Loves Folklore.
-
Presentation by Suyash (Jury Coordinator for Wiki Loves Folklore
2024): Next,
Suyash will speak for 20 minutes about "How to Set Up a Good Jury for Wiki
Loves Folklore Photography Contest." He'll help to choose good pictures
-
Presentation by Nokib Sarkar (Lead Tool Developer for WLF 2024): Then,
Nokib will talk for 20 minutes about "How We Judge Writing Contests using
Campwiz Tool." He will show how to use the jury functionality in campwiz.
-
Questions and Chat Time: After the presentations, we'll have 10 minutes
for you to ask questions and share your thoughts.
We think this event will be really helpful, and we'd love for you to be
there. To save your spot, just click here
<https://meta.wikimedia.org/wiki/Wiki_Loves_Folklore_2024_Office_Hour_2#Part…>
Thanks so much for all your support with Wiki Loves Folklore. We're looking
forward to chatting with you soon!
Best,
Isaac Kanguya
Communication Officer International Team WLF 2024
Hello all!
We have been hard at work on our Graph Split experiment [1], and we now
have a working graph split that is loaded onto 3 test servers. We are
running tests on a selection of queries from our logs to help understand
the impact of the split. We need your help to validate the impact of
various use cases and workflows around Wikidata Query Service.
**What is the WDQS Graph Split experiment?**
We want to address the growing size of the Wikidata graph by splitting it
into 2 subgraphs of roughly half the size of the full graph, which should
support the growth of Wikidata for the next 5 years. This experiment is
about splitting the full Wikidata graph into a scholarly articles subgraph
and a “main” graph that contains everything else.
See our previous update for more details [2].
**Who should care?**
Anyone who uses WDQS through the UI or programmatically should check the
impact on their use cases, scripts, bots, code, etc.
**What are those test endpoints?**
We expose 3 test endpoints, for the full, main and scholarly articles
graphs. Those graphs are all created from the same dump and are not live
updated. This allows us to compare queries between the different endpoints,
with stable / non changing data (the data are from the middle of October
2023).
The endpoints are:
* https://query-full-experimental.wikidata.org/
* https://query-main-experimental.wikidata.org/
* https://query-scholarly-experimental.wikidata.org/
Each of the endpoints is backed by a single dedicated server of performance
similar to the production WDQS servers. We don’t expect performance to be
representative of production due to the different load and to the lack of
updates on the test servers.
**What kind of feedback is useful?**
We expect queries that don’t require scholarly articles to work
transparently on the “main” subgraph. We expect queries that require
scholarly articles to need to be rewritten with SPARQL federation between
the “main” and scholarly subgraphs (federation is supported for some
external SPARQL servers already [3], this just happens to be for internal
server-to-server communication). We are doing tests and analysis based on a
sample of query logs.
**We want to hear about:**
General use cases or classes of queries which break under federation
Bots or applications that need significant rewrite of queries to work with
federation
And also about use cases that work just fine!
Examples of queries and pointers to code will be helpful in your feedback.
**Where should feedback be sent?**
You can reach out to us using the project’s talk page [1], the Phabricator
ticket for community feedback [4] or by pinging directly Sannita (WMF) [5].
**Will feedback be taken into account?**
Yes! We will review feedback and it will influence our path forward. That
being said, there are limits to what is possible. The size of the Wikidata
graph is a threat to the stability of WDQS and thus a threat to the whole
Wikidata project. Scholarly articles is the only split we know of that
would reduce the graph size sufficiently. We can work together on providing
support for a migration, on reviewing the rules used for the graph split,
but we can’t just ignore the problem and continue with a WDQS that provides
transparent access to the full Wikidata graph.
Have fun!
Guillaume
[1]
https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/WDQS_graph_split
[2]
https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/WDQS_backend_up…
[3]
https://www.mediawiki.org/wiki/Wikidata_Query_Service/User_Manual#Federation
[4] https://phabricator.wikimedia.org/T356773
[5] https://www.wikidata.org/wiki/User:Sannita_(WMF)
--
Guillaume Lederrey (he/him)
Engineering Manager
Wikimedia Foundation