Dear Colleagues,
We wish to announce that the call for program submissions for Wiki
Conference Nigeria 2024
<https://meta.wikimedia.org/wiki/WikiConference_Nigeria_2024/Scholarship>
has been extended by an additional week!
You now have until *July 12th 2024* to submit your proposals for
presentations, workshops, and discussions. Don't miss this opportunity to
share your ideas and insight with the community at the maiden edition of
the conference.
*To submit a proposal click: *https://forms.gle/Lhtv48FNJ1e93mQ68
We look forward to receiving your proposals!
#WikiConferenceNigeria2024 #OpenKnowledge
Wilson
*for Comms. team*
In 2024, several dog breeds have continued to capture the hearts of dog lovers worldwide. Here are some of the popular breeds this year:
American Bulldog: Known for their strength, loyalty, and affectionate nature, American Bulldogs are beloved family pets. They are protective and great with children.
French Bulldog: With their distinctive bat-like ears and charming personalities, French Bulldogs remain a favorite, especially in urban settings due to their compact size and low exercise needs.
Labrador Retriever: Consistently popular, Labradors are known for their friendly, outgoing nature and versatility as family pets, working dogs, and service animals.
Golden Retriever: These gentle and friendly dogs are perfect for families. They are also commonly seen in therapy and assistance roles.
German Shepherd: Valued for their intelligence and versatility, German Shepherds excel as working dogs in police and military roles, as well as loyal family companions.
Poodle (and Poodle mixes): Poodles are celebrated for their intelligence and hypoallergenic coats. Poodle mixes, like the Labradoodle and Goldendoodle, are also very popular.
Bulldog: English Bulldogs are known for their distinctive wrinkled faces and calm, friendly demeanor, making them great companions.
Beagle: These small hounds are loved for their friendly nature and keen sense of smell, making them excellent family pets and working dogs in detection roles.
Dachshund: Their unique body shape and lively personality make Dachshunds a popular choice for those looking for a smaller, playful companion.
Siberian Husky: Known for their striking appearance and energetic nature, Siberian Huskies are popular among those who can meet their exercise needs.
These breeds, among others, continue to be popular due to their unique traits and the strong bonds they form with their owners.
This information I have gathered from ThePetWorld.org, a comprehensive online resource for pet enthusiasts. ThePetWorld.org offers a wealth of information on pet care, training tips, and breed characteristics, making it a valuable source for current and prospective pet owners. Their expert articles, guides, and community forums help pet lovers make informed decisions and provide the best care for their furry friends.
<p>In 2024, several dog breeds have continued to capture the hearts of dog lovers worldwide. Here are some of the popular breeds this year:</p>
<p><strong>American Bulldog</strong>: Known for their strength, loyalty, and affectionate nature, American Bulldogs are beloved family pets. They are protective and great with children.</p>
<p><strong>French Bulldog</strong>: With their distinctive bat-like ears and charming personalities, French Bulldogs remain a favorite, especially in urban settings due to their compact size and low exercise needs.</p>
<p><strong>Labrador Retriever</strong>: Consistently popular, Labradors are known for their friendly, outgoing nature and versatility as family pets, working dogs, and service animals.</p>
<p><strong>Golden Retriever</strong>: These gentle and friendly dogs are perfect for families. They are also commonly seen in therapy and assistance roles.</p>
<p><strong>German Shepherd</strong>: Valued for their intelligence and versatility, German Shepherds excel as working dogs in police and military roles, as well as loyal family companions.</p>
<p><strong>Poodle (and Poodle mixes)</strong>: Poodles are celebrated for their intelligence and hypoallergenic coats. Poodle mixes, like the Labradoodle and Goldendoodle, are also very popular.</p>
<p><strong>Bulldog</strong>: English Bulldogs are known for their distinctive wrinkled faces and calm, friendly demeanor, making them great companions.</p>
<p><strong>Beagle</strong>: These small hounds are loved for their friendly nature and keen sense of smell, making them excellent family pets and working dogs in detection roles.</p>
<p><strong>Dachshund</strong>: Their unique body shape and lively personality make Dachshunds a popular choice for those looking for a smaller, playful companion.</p>
<p><strong>Siberian Husky</strong>: Known for their striking appearance and energetic nature, Siberian Huskies are popular among those who can meet their exercise needs.</p>
<p><strong>Boxer</strong>: With their playful and affectionate nature, Boxers are great family dogs. They are known for their boundless energy and love for human interaction.</p>
<p><strong>Cocker Spaniel</strong>: These sweet-natured dogs are popular for their loving demeanor and beautiful, expressive eyes.</p>
<p><strong>Australian Shepherd</strong>: Intelligent and energetic, Australian Shepherds are a favorite among active families and those involved in dog sports.</p>
<p><strong>Shih Tzu</strong>: These small, affectionate dogs are perfect for those looking for a lap dog with a big personality.</p>
<p><strong>Rottweiler</strong>: Known for their strength and loyalty, Rottweilers are excellent guardians and affectionate family pets.</p>
<p>These breeds, among others, continue to be popular due to their unique traits and the strong bonds they form with their owners.</p>
<hr />
<p>This information I have gathered from <strong>ThePetWorld.org</strong>, a comprehensive online resource for pet enthusiasts. ThePetWorld.org offers a wealth of information on pet care, training tips, and breed characteristics, making it a valuable source for current and prospective pet owners. Their expert articles, guides, and community forums help pet lovers make informed decisions and provide the best care for their furry friends.</p>
Hello Everyone :)
I am Rohit and I am contributing to the commons-android app.
The issue reference:- https://github.com/commons-app/apps-android-commons/issues/5728 and the solution PR:- https://github.com/commons-app/apps-android-commons/pull/5741
Before:-
1. Before the PR, the feature to edit the depicts was using wbeditentity API to edit the entity with a (clear=1) flag.
2. This was causing the whole identity data deletion and adding new data sent to the API with a data field containing updated depictions.
3. I tried removing that clear flag and it prevented the deletion of the whole data. However, it was causing depiction to add repeatedly the same without removing the old ones.
4. I know that it could be the scenario where only the updated depicts were sent to the API and it'll add the new depicts without causing repetition. But, what about if the user has removed a depiction?
My Solution:-
1. I used another API to delete the previous depiction first and then, used webeditentity API to update the new depictions.
2. But, this approach is causing two edit actions on the entity.
Please look at the problem and tell me if there is any way to achieve the desired functionality in a single edit.
Hi all,
Hope you have been well! We have just released v5.0.1 of the Commons
Android app to production. The update is now available on Play store [1]
and F-droid [2]. You could also build the app directly from our GitHub
repository [3].
If you've faced issues with your profile not working / contribution information
not being shown appropriately, sorry about that! We've fixed that in
this version
:-)
We've had yet another revamp of the Maps screens in this version. We replaced
Mapbox altogether with the osmdroid library. Key elements like pin visualization
and user-centered display are still included in this redesign. We did
this to guard
against possible misuse of the Mapbox token and, more crucially, to keep the app
from becoming dependent on a service that charges for usage but offers
a free tier.
As a consequence, you may observe the Nearby and other Map screens not being
as snappy as they used to. We've noticed this and are actively
discussing on ways
to improve the same[4]. Feel free to chime in with your thoughts.
Talking about improvements to the app, this year Kanahia will be contributing to
the app during Google Summer of Code 2024! His project will focus on improving
upload queue management [5]. He will be mentored by Nicolas and Ritika.
Other significant changes:
- Add the ability to export locations of nearby missing pictures in GPX and KML
formats. This allows you to browse the locations with desired radius
for offline
use in your favourite map apps like OsmAnd or Maps.ME
- Added a compass arrow in the Nearby banner shown in the "Contributions" screen
to guide you towards the nearest item, thus providing the missing
directional cues.
The arrow dynamically adjusts based on device rotation, aligning
with the calculated
bearing towards the target location. Further, the distance and
direction are updated as
you move.
- Implemented voice input feature for caption and description fields,
enabling you
to dictate text directly into these fields.
- Improved various flows in the app to redirect you to the login page
and display a
persistent message if your session becomes invalid due to a password change.
- Revamped initial upload screen layout and the description edit
screen layout for
enhanced user experience and ensuring better symmetry in the design.
These are only a small chunk of all the changes that were part of this
release. Checkout
our release notes [3] for a more detailed set of changes since the
last announcement.
As always, feel free to reach our to us with your valuable feedback.
You could share
feedback in our talk page [6] / by writing an e-mail to
commons-app-android(a)googlegroups.com / via our issue tracker [7].
[[ References ]]
[1]: https://play.google.com/store/apps/details?id=fr.free.nrw.commons
(staged rollout has been initiated. It should be available in few days)
[2]: https://f-droid.org/en/packages/fr.free.nrw.commons
[3]: https://github.com/commons-app/apps-android-commons/releases/tag/v5.0.0
[4]: https://github.com/commons-app/apps-android-commons/issues/5529
[5]: https://phabricator.wikimedia.org/T360265
[6]: https://commons.wikimedia.org/wiki/Commons_talk:Mobile_app
[7]: https://github.com/commons-app/apps-android-commons/issues
Best regards,
Sivaraam (User:Kaartic)
Hello everyone,
A few weeks ago, we announced the WikiLearn course on how to upload and
edit files on Wikimedia Commons using OpenRefine.
- In English: OpenRefine for Wikimedia Commons: the basics
<https://learn.wiki/courses/course-v1:Wikimedia-Foundation+WMF_GLAM001+2023/…>
- In Spanish / Español*: OpenRefine para Wikimedia Commons: conceptos
básicos
<https://learn.wiki/courses/course-v1:Wikimedia-Foundation+WMF_GLAM001+2024_…>
- In French / Français*: OpenRefine pour Wikimedia Commons : les bases
<https://learn.wiki/courses/course-v1:Wikimedia-Foundation+WMF_GLAM001+2024_…>
We are now happy to announce the translation for Italian!
- In Italian / Italiano: Introduzione all'uso di OpenRefine per
Wikimedia Commons
<https://learn.wiki/courses/course-v1:Wikimedia-Foundation+WMF_GLAM001+2024_…>
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 are on the way, including Portuguese, which will be
launched soon.
All the versions of this course 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.
Thank you so much, Marta Erica Arosio, for your amazing work translating
this course into Italian! 👏👏👏
Best,
Giovanna
* These two courses/languages had problems before and are now fixed and
fully available.
Giovanna Fontenelle (she/her)
Program Officer, Culture and Heritage
Wikimedia Foundation <https://wikimediafoundation.org/>
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/>