I just tried to watch some presentation videos from Wikimania.
Some had very weak sound, some had no sound in the first minutes,
some only played the first minute and then stopped. I don't think
the Wikimania videos are unique in having such problems. Video is
new to Commons, and the expert contributors are more familiar with
still images.
How can we learn to make better videos? Are there some good
instructions? Perhaps a free instruction video (Wikibooks, but a
video instead of a book) on how to produce good videos is what we
need. In fact, the English Wikibooks has a title on "Video
Production", http://en.wikibooks.org/wiki/Video_Production but it
doesn't have a clear focus (pun not intended). It starts out with
discussing satellite TV and has long sections on file formats in
different operating systems.
There is a help page on Commons for converting video to the Ogg
Theora format, but that is only the last step in a long chain.
Given that video is new, how can we find and rate videos, nominate
"good/featured videos", and give advice on how to improve quality?
Is the Commons village pump enough for this? Commons has a
separate graphics village pump. Do we also need a separate video
village pump?
Current digital video cameras use hard disks or memory cards,
instead of tape cassettes. Many new models cost less than 300
euro (or dollars), some as little as 120 euro (memory card perhaps
not included). Some have a special "Youtube mode", and I guess
that kind of usage is what drives the price down. What models are
good, and what should one watch out for?
We can find free still photos on Flickr and copy them to Commons.
Is there somewhere we can find free videos and copy them? Yes, at
the Internet Archive. Somewhere else?
--
Lars Aronsson (lars(a)aronsson.se)
Aronsson Datateknik - http://aronsson.se
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/>