This is an announcement for a significant, but not breaking, change to the
response format of the wbsearchentities API. So far, each search result has
included "label" or "description" members- which included the
label/description of the matched entity- so that it could be shown to
users. However, these were plain strings with no indication of the language
of the label or description: if language fallback happened (e.g. if the
search was in Arabic, but the item only had an English description), then
there would be no indication of this in the response. Users of the API
couldn’t know what the language of the returned label/description was
without a separate API call to retrieve the entity’s data. This is for
example necessary for screen readers to read out the label/description in
the correct language. (We will follow up with other changes to make use of
it in the Wikibase UI, so that screen readers there are getting a better
indication of which language to read out.)
We have resolved this with the addition of a new "display" member to the
search result structure, which contains a "label" and "description" that
are not plain strings, but rather objects with "language" and "value"
members (like labels and descriptions in the normal JSON serialization
The old "label" and "description" fields are still there, but deprecated:
we recommend that you don’t use them in new code. Please note that, just
like the "label" and "description" were always optional (i.e. could be
missing for entities that had no label or description available in the
request language or a fallback language), so the "label" and "description"
in the new response are also optional (under the same conditions).
This change was already deployed to Beta Wikidata, Test Wikidata, and
Wikidata. If you have any questions or feedback, please feel free to let us
know in this ticket <https://phabricator.wikimedia.org/T104344>.
*Community Communications Manager for Wikidata/Wikibase*
Wikimedia Deutschland e. V. | Tempelhofer Ufer 23-24 | 10963 Berlin
Phone: +49 (0)30 219 158 26-0
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Körperschaften I Berlin, Steuernummer 27/029/42207.
The next Research Showcase will be live-streamed Wednesday, March 16 at
6:30AM PT / 13:30 UTC. Find your local time here:
The theme is: Patterns and dynamics of article quality.
YouTube stream: https://www.youtube.com/watch?v=o5e6S7ac4q4
You can join the conversation on IRC at #wikimedia-research. You can also
watch our past research showcases here:
The Showcase will feature the following talks:
Quality monitoring in Wikipedia - A computational perspectiveBy *Animesh
Mukherjee <https://cse.iitkgp.ac.in/~animeshm/> (Indian Institute of
Technology, Kharagpur)*In this talk, I shall summarize our five-year long
research highlights concerning Wikipedia. In particular, I shall deep dive
into two of our recent works; while the first one attempts to understand
the early indications of which editors would soon go "missing" (aka missing
editors) , the second one investigates how the quality of a Wikipedia
article transitions over time and whether computational models could be
built to understand the characteristics of future transitions . In each
case, I will present a suite of key results and the main insights that we
obtained thereof. When expertise gone missing: Uncovering the loss of
prolific contributors in Wikipedia
2021 (pdf <https://arxiv.org/pdf/2109.09979>) Quality Change: norm or
exception? Measurement, Analysis and Detection of Quality Change in
Wikipedia <https://arxiv.org/abs/2111.01496>, CSCW 2022 (pdf
Automatically Labeling Low Quality Content on Wikipedia by Leveraging
Editing BehaviorsBy *Sumit Asthana <http://sumitasthana.xyz/> (University
of Michigan, Ann Arbor)*Wikipedia articles aim to be definitive sources of
encyclopedic content. Yet, only 0.6% of Wikipedia articles have high
quality according to its quality scale due to insufficient number of
Wikipedia editors and enormous number of articles. Supervised Machine
Learning (ML) quality improvement approaches that can automatically
identify and fix content issues rely on manual labels of individual
Wikipedia sentence quality. However, current labeling approaches are
tedious and produce noisy labels. In this talk, I will discuss an automated
labeling approach that identifies the semantic category (e.g., adding
citations, clarifications) of historic Wikipedia edits and uses the
modified sentences prior to the edit as examples that require that semantic
improvement. Highest-rated article sentences are examples that no longer
need semantic improvements. I will discuss the performance of models
training with this labeling approach over models trained with existing
labeling approaches, and also the implications of such a large scale semi
supervised labeling approach in capturing the editing practices of
Wikipedia editors and helping them improve articles faster.Related
Labeling Low Quality Content on Wikipedia By Leveraging Patterns in Editing
Behaviors <https://dl.acm.org/doi/10.1145/3479503>, CSCW 2021 (pdf
Emily Lescak (she / her)
Senior Research Community Officer
The Wikimedia Foundation
As some of you may know, several developers are currently working on a
project (funded by a Wikimedia grant) to add Structured Data on Wikimedia
Commons functionalities to OpenRefine. See
https://commons.wikimedia.org/wiki/Commons:OpenRefine for more info.
We are making good progress on this project. As we will probably regularly
add new Wikibase/Commons/Wikidata-related functionalities to OpenRefine,
the OpenRefine team starts hosting online, monthly office hours for
OpenRefine users from the Wikimedia community (including Wikidatans!). You
can meet and ask questions to other OpenRefine / Wikimedia users here, and
talk to members of the development team. These office hours are informal,
have no set agenda, are held via Zoom but are not recorded. Registration is
For now, we have scheduled office hours until the end of June 2022. Time of
the day alternates to accommodate participants from diverse time zones. If
these office hours prove to be popular, we will plan more of these later!
- Tuesday, March 22, 2022 at 9AM UTC
- Tuesday, April 19, 2022 at 4PM UTC
- Tuesday, May 24, 2022 at 8AM UTC
- Tuesday, June 21, 2022 at 4PM UTC
we will post the Zoom links. Feel free to drop by :-)
All the best,
Sandra (User:Spinster / User:SFauconnier)
There has been interest in having more transparency around some of the
operational problems around Wikidata Query Service, to better surface the
work it takes in keeping the service running.
Yesterday, on Sunday, 06 March, there was an outage that lasted a few
hours. During this time, WDQS was overloaded and started sporadically
blocking client traffic. This was directly related to the ongoing issues
with Blazegraph, and why our main priority has been focused on finding a
suitable replacement for it moving forward.
The incident summary is available here
Apologies to all who were affected by this incident.
*Mike Pham* (he/him)
Sr Product Manager, Search
Wikimedia Foundation <https://wikimediafoundation.org/>
The Research team  at the Wikimedia Foundation hosts monthly Office
Hours  to connect with researchers, answer questions, and share updates.
To improve the impact and accessibility of our sessions, we invite you to
share your feedback in a brief optional survey . We estimate that it
will take about 5-10 minutes to complete. We welcome your input even if you
have not attended Office Hours. If you prefer to not respond via Google
form, you can provide your feedback via email. We will accept responses
until April 15, 2022.
Thank you for your time and consideration.
Emily, on behalf of the Research team
Emily Lescak (she / her)
Senior Research Community Officer
The Wikimedia Foundation
Hello again, Wikimedia Hackers!
We invite technical community members and affiliates to apply for Rapid
Fund grants to host local meetups during or around the Hackathon. Grants
can be between 500 and 5,000 USD. Please note that we cannot go above 5,000
USD per grant, so plan accordingly. The deadline to apply is March 20,
2022. This is a quick turn-around, so note that proposals do not have to be
extensive or complex.
Examples of requests include:
Food for community meetups before, during, or after the online Hackathon
(please keep meetups within a month of the Hackathon dates).
Venue rental for attendees
Transportation or commuting expenses
Scholarships to help local community members attend, which can include
data packages, childcare costs, or transportation
The Foundation offers this list of eligible expenses
<https://meta.wikimedia.org/wiki/Grants:Project/Rapid/Learn> (e.g., you
can use this grant money to pay for direct expenses like supplies, but you
cannot use funds to pay for an event coordinator). You cannot pay
honorariums to speakers you have at your events but you can give material
gifts (gift cards, etc.).
Note that at this moment, in-person meetups of 10 people or fewer can be
held without extra approval; if your meetup will be larger please follow
the steps listed for Risk Assessment.
Proposals should support the achievement of Wikimedia’s mission
<https://meta.wikimedia.org/wiki/Mission> and be related to the
Hackathon (this cannot support edit-a-thon projects for example).
There are some countries to which the Foundation cannot disburse funds.
If you have been ineligible for WMF funds through other opportunities,
please email hlepp(a)wikimedia.org to verify your eligibility for this
Both individuals and organizations are welcome to apply.
Someone in your group must have access to a bank account which can
receive international wire transfers.
The Code of Conduct for Wikimedia's Technical Spaces
be in effect throughout the event, on all platforms and at local meetups.
Please have a look at it and ensure you are willing and able to follow it.
How to Apply: Start your application
<https://meta.wikimedia.org/wiki/Grants:Project/Rapid/Apply#Other> in the
yellow box marked “Other”. Enter the title of your proposal: Hackathon +
[Institution/Group/Individual Name] (e.g., Hackathon University of Ghana
Legon) and click “Start my application”. Submit the application. Any
questions can be sent to hlepp(a)wikimedia.org.
Your Wikimedia Hackathon Committee