How are the candidate pairs for the merge game generated?
For example, when I fired up the 'Merge Items' on the Distributed Game, it
asked me if the following two items are the same topic or different:
Nicola Kirsch [Q1986126]
Nicky Kirsch [Q13104330]
I don't think they're matches, but how did it pick these two to ask about
in the first place?
It sounds like there is a batch process that runs and identifies potential
pairs. If so:
- How often does that process run?
- What criteria does it use to predict potential matches?
- Is the list of potential pairs stored somewhere and viewable without
clicking through the game?
- Do any of the other matching/merging tools use the same dataset?
A few days ago I opened a thread  in the discussion of the property
P1184 («handle») to argue about the single value constraint defined in
I am not going to extend this mail, because I exposed my arguments in
the talk page and I think this kind of discussions have to be placed and
registered in Wikidata.
Thanks in advance for your attention.
Iván Hernández Cazorla
You may be interested in this consultation that Sandra started on Commons.
---------- Forwarded message ----------
From: Sandra Fauconnier <sfauconnier(a)wikimedia.org>
Date: Wed, Apr 25, 2018 at 12:17 PM
Subject: [libraries] feedback request: GLAM ontology and metadata mapping
for Structured Data on Commons
To: North American Cultural Partnerships <glam-us(a)lists.wikimedia.org>,
Wikimedia Chapters cultural partners coordination - closed list <
cultural-partners(a)wikimedia.ch>, Wikimedia & Libraries <
libraries(a)lists.wikimedia.org>, "Wikimedia & GLAM collaboration [Public]" <
For those interested in (the admittedly a bit nerdy, but important issue
of) ontologies and metadata schemes around GLAM, media files and the
upcoming structured data on Commons
<https://commons.wikimedia.org/wiki/Commons:Structured_data>: there is
currently a first feedback round
(and probe of interest) to start working on metadata and ontology mapping
on this topic for Wikimedia Commons.
Why? When we are better able to 'map' the metadata schemes used by GLAMs to
the (newly) structured data on Wikimedia Commons, we hope the upload and
synchronization of files will become a lot smoother.
Please check the request for feedback page on Commons
and leave your comments on the talk page there
This first feedback round runs until 4 May.
All the best! Sandra
Libraries mailing list
Learn more about how the communities behind Wikipedia, Wikidata and other
Wikimedia projects partner with cultural heritage organizations:
From: Wikipedia Volunteer Response Team
Sent: Saturday, April 21, 2018 6:10 PM
To: John D
Subject: Re: [Ticket#2018032210008751] infobox
Dear John D,
This queue is ONLY for English Wikipedia, you MUST use the Russian queue
There is nothing at all we can do.
Wikipedia - https://en.wikipedia.org/
24/03/2018 13:44 - John D wrote:
> and uses the russian template.
> it is coming from the identifier but stretches the box rather than dropping down
> to the next line. and is based on the rank.to turn it off.
> From: Wikipedia Volunteer Response Team
> Sent: Saturday, March 24, 2018 2:44 AM
> To: John D
> Subject: Re: [Ticket#2018032210008751] infobox
> Hi John,
> Could you provide an example of an article that has this problem, so that I may
> take a closer look?
> Yours sincerely,
> Kevin Payravi
> Wikipedia - https://en.wikipedia.org/
> 03/22/2018 14:33 - John D wrote:
> > how do you stop the info box on the article page from getting wider from data coming from
> > the hidden wikidata page ?
This editor put the name in all languages in english,
is that right ?
“I added the name in all languages using Latin-script, with the order given name-surname and no declension,
So yes, the name should be the same in all these languages”
“Update 78 language (s) with the labels” " Helen Balfour Morrison"
This editor is saying that all russian church pages are wrong,
is that right ?
“You can't have P279 and P31 in the same item”
they were not in the same box.
Removed claim: subclass of (P279): Eastern Orthodox Church (Q35032))
Removed claim: subclass of (P279): Russian Orthodox Church (Q60995))
“This editor is attacking and removing all instances of location , https://www.wikidata.org/wiki/User_talk:Ksc~ruwiki
06:15, 23 March 2018 (Removed claim: located in the administrative territorial entity (P131): Kozelsk(Q154661))
This editor put it back without looking at history. where i tried to fix.
20:06, 6 April 2018 (Created claim: located in the administrative territorial entity (P131): Kozelsk (Q154661))
This bot is adding country code to local phone no. when p 474 is already there.
(Changed claim: phone number (P1329): +7-812-323-74-36, Normalizes phone number format)
A friend asked if we have a query showing "humans" sorted by "country of
citizenship". He is particularly interested in Mozambique, I am
particularly interested in former countries.
What would be particularly helpful is when there is a separate column for
the genders. For some former countries like the Ottoman Empire it takes
more effort to find women to write about.. Making them visible is important.
(apologies for cross-posting)
We’re sharing a proposed program for the Wikimedia Foundation’s upcoming fiscal year (2018-19) and would love to hear from you. This plan builds extensively on projects and initiatives driven by volunteer contributors and organizations in the Wikimedia movement, so your input is critical.
Why a “knowledge integrity” program?
Increased global attention is directed at the problem of misinformation and how media consumers are struggling to distinguish fact from fiction. Meanwhile, thanks to the sources they cite, Wikimedia projects are uniquely positioned as a reliable gateway to accessing quality information in the broader knowledge ecosystem. How can we mobilize these citations as a resource and turn them into a broader, linked infrastructure of trust to serve the entire internet? Free knowledge grounds itself in verifiability and transparent attribution policies. Let’s look at 4 data points as motivating stories:
Wikipedia sends tens of millions of people to external sources each year. We want to conduct research to understand why and how readers leave our site.
The Internet Archive has fixed over 4 million dead links on Wikipedia. We want to enable instantaneous archiving of every link on all Wikipedias to ensure the long-term preservation of the sources Wikipedians cite.
#1Lib1Ref reaches 6 million people on social media. We want to bring #1Lib1Ref to Wikidata and more languages, spreading the message that references improve quality.
33% of Wikidata items represent sources (journals, books, works). We want to strengthen community efforts to build a high-quality, collaborative database of all cited and citable sources.
A 5-year vision
Our 5-year vision for the Knowledge Integrity program is to establish Wikimedia as the hub of a federated, trusted knowledge ecosystem. We plan to get there by creating:
A roadmap to a mature, technically and socially scalable, central repository of sources.
Developed network of partners and technical collaborators to contribute to and reuse data about citations.
Increased public awareness of Wikimedia’s vital role in information literacy and fact-checking.
5 directions for 2018-2019
We have identified 5 levers of Knowledge Integrity: research, infrastructure and tooling, access and preservation, outreach, and awareness. Here’s what we want to do with each:
Continue to conduct research to understand how readers access sources and how to help contributors improve citation quality.
Improve tools for linking information to external sources, catalogs, and repositories.
Ensure resources cited across Wikimedia projects are accessible in perpetuity.
Grow outreach and partnerships to scale community and technical efforts to improve the structure and quality of citations.
Increase public awareness of the processes Wikimedians follow to verify information and articulate a collective vision for a trustable web.
Who is involved?
The core teams involved in this proposal are:
Wikimedia Foundation Technology’s Research Team
Wikimedia Foundation Community Engagement’s Programs team (Wikipedia Library)
Wikimedia Deutschland Engineering’s Wikidata team
The initiative also spans across an ecosystem of possible partners including the Internet Archive, ContentMine, Crossref, OCLC, OpenCitations, and Zotero. It is further made possible by funders including the Sloan, Gordon and Betty Moore, and Simons Foundations who have been supporting the WikiCite initiative to date.
How you can participate
You can read the fine details of our proposed year-1 plan, and provide your feedback, on mediawiki.org: https://www.mediawiki.org/wiki/Wikimedia_Technology/Annual_Plans/FY2019/CDP…
We’ve also created a brief introductory slidedeck about our motivation and goals: https://commons.wikimedia.org/wiki/File:Knowledge_Integrity_CDP_proposal_%E…
WikiCite has laid the groundwork for many of these efforts. Read last year’s report: https://commons.wikimedia.org/wiki/File:WikiCite_2017_report.pdf
Recent initiatives like the just released citation dataset foreshadow the work we want to do: https://medium.com/freely-sharing-the-sum-of-all-knowledge/what-are-the-ten…
Lastly, this April we’re celebrating Open Citations Month; it’s right in the spirit of Knowledge Integrity: https://blog.wikimedia.org/2018/04/02/initiative-for-open-citations-birthda…
Dario Taraborelli Director, Head of Research, Wikimedia Foundation
wikimediafoundation.org • nitens.org • @readermeter
Dear Mr. or Ms.,
I thank you for your efforts. We are writing now a scientific publication in which we explain how and why we should use Wikidata in Medicine. We will explain first the knowledge-related matters faced by physicians and other health specialists. Then, we introduce Wikidata as a major medical knowledge database and explain its structure and the useful medical information it contains. Finally, we will explain how Wikidata can solve the knowledge-related problems faced by medical scientists and expose successful experiences of using Wikidata for the support of medicine. We are managing to publish this brief report as an editorial in Journal of Biomedical Semantics or in Artificial Intelligence in Medicine. I ask if someone is interested to join this effort.