Hello All,
I am glad to see too many comments and views, these conversations help
understand and improve upon. Let me be clear that this is purely a {HACK},
this is not official and it's only a hack, a step in AI. Most people have
concern on the following issue
*Privacy* - If some one wants to use such feature app need image to train
the model (AI Model), which is store in encrypted blob format (image not
visible to anyone, If any one want to use such feature then he have to use
under CC License)
*@Benjamin Lees : *Its secure! its not simply you show {X} Image to camera
and simply login to his account. What face technique I am using same technique
using in payment industry.
*@**Winged Blades : *Very soon I will share source code and blog, I hope
you will get you all answer.
@*Subhashish Panigrahi : *I went though all your comments, If some one want
to use such feature then he have to use under CC licence.
If you more doubt will discuss on phone/email.
Thanks & Regards
Santosh Shingare,
Executive member, Wikimedia India Chapter
+91 9890984632
Skype: cherishsantosh | http://wiki.wikimedia.in
On Fri, Aug 9, 2019 at 7:01 PM Winged Blades <wbgodric(a)gmail.com> wrote:
> What Subhasish says. I don't have remote expectations of this getting
> cleared by Legal or by the community and oppose the proposals very strongly
> ....
>
> Also, the algorithm used in OpenCV is quite backdated, and is quite
> susceptible to false positives.
>
>
> On Fri, Aug 9, 2019 at 2:47 PM Subhashish Panigrahi <psubhashish(a)gmail.com>
> wrote:
>
>> Santosh - how valuable it might be, I am unable to understand how this is
>> relevant to Wikimedia projects. Maybe you could elaborate on anything that
>> is not obvious. Also, face recognition leads to the questions related to
>> questions on privacy, personal data collection, and even surveillance. For
>> instance, there is a huge debate going on about the potential issues
>> related to the face recognition based security gates that have recently
>> been installed in several Indian airports. Face recognition for logging
>> into Wikimedia projects might just open a pandora's box as the anonymity of
>> contributors is core to Wikimedia projects. I am not sure if there is any
>> discussion that exists anywhere about even adding a test project but I'd
>> highly discourage biometric-based authentication. I think this community
>> and probably the foundation does not have the legal, technical and other
>> infrastructure that is required to manage a few hundred thousand personal
>> data including biometric data as the latter is extremely vulnerable. Any
>> data breach could cost lives. Many of our community members work in regions
>> with geopolitical conflicts and biometric data tied to one's Wikimedia
>> contribution could potentially lead to danger to their lives. Similarly,
>> there is not enough education about individual privacy and biometric data
>> collection which is why many online users, out of ignorance, end up sharing
>> their private details online. The more the personal data collection options
>> on a platform, the more the risk of that data being leaked and misutilised.
>> No offense to the hard work, but {{STRONGLY DISAGREE}} for any such
>> projects even on an experimental basis.
>>
>> S
>>
>>
>> On Thu, Aug 8, 2019 at 4:37 PM Santosh Shingare <cherishsantosh(a)gmail.com>
>> wrote:
>>
>>> Hello Wikimedian,
>>>
>>> 3D face recognition has become a trending research direction in both
>>> industry and academia. Using your face to authorize to unlock your phone is
>>> popular, but on the web it has not been seen a lot, maybe because it’s not
>>> trivial to implement. Is it possible to implement face verification using
>>> just HTML5, Javascript and some Go? Yes! I did it in an hour using
>>> Javascript, Nodejs, and OpenCV for wikipedia login.
>>>
>>> I Implemented face recognition and web login for wikipedia. Please check
>>> following video and screenshots. Very soon I will share code on Github.
>>>
>>> -
>>> https://commons.wikimedia.org/wiki/File:Web_login_with_face_recognition.webm
>>> -
>>> https://commons.wikimedia.org/wiki/File:Web_login_with_face_recognition_log…
>>> -
>>> https://commons.wikimedia.org/wiki/File:Web_login_with_face_recognition_and…
>>> -
>>> https://commons.wikimedia.org/wiki/File:Web_login_with_face_recognition_and…
>>>
>>>
>>> Feel free to revert if you have any question.
>>>
>>>
>>> Thanks & Regards
>>>
>>> Santosh Shingare,
>>> Executive member, Wikimedia India Chapter
>>> +91 9890984632
>>> Skype: cherishsantosh | http://wiki.wikimedia.in
>>> _______________________________________________
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>>> To unsubscribe from the list / change mailing preferences visit
>>> https://lists.wikimedia.org/mailman/listinfo/wikimediaindia-l
>>>
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>
Hi All,
Here are the minutes from this week's TechCom meeting:
* RFC Meeting on RFC 2019 Process Amendments
<https://phabricator.wikimedia.org/T216308> on 21 August at 2pm
Pacific/23:00 CEST/21:00 UTC in #wikimedia-office
* Hosted remote/in person meeting from Wikimania Hackathon
* Discussed: <https://phabricator.wikimedia.org/T227776> Generalize
ParserCache into a generic service class for large "current"
page-derived data.
* Summary:
* general support for the idea of having a generic store for
artifacts derived from page content ("cache" seems a misleading term)
* functionality should be implemented internally to MW core
for now, based on the storage infrastructure of the existing
ParserCache
* making such functionality available to standalone services
raises concerns, e.g. about checking access permissions
* we may want a way to add access flags to the cached objects
* ParserCache can already store multiple variants. The new
system would just add the ability to add other things beyond variants,
and to store them for more than just the latest revision of a page.
You can also find our meeting minutes at
<https://www.mediawiki.org/wiki/Wikimedia_Technical_Committee/Minutes>
See also the TechCom RFC board
<https://phabricator.wikimedia.org/tag/mediawiki-rfcs/>.
If you prefer you can subscribe to our newsletter here
<https://www.mediawiki.org/wiki/Newsletter:TechCom_Radar>
Thanks,
Kate
--
Kate Chapman
Senior Program Manager, Core Platform
Wikimedia Foundation
kchapman(a)wikimedia.org
Dear all,
I thank you for your efforts. I invite you to our session about Wikidata and Health that will occur on 10.30 in Tu's Room. It will be an honour to see your opinions about this important area.
Yours Sincerely,
Houcemeddine Turki (he/him)
Medical Student, Faculty of Medicine of Sfax, University of Sfax, Tunisia
Undergraduate Researcher, UR12SP36
GLAM and Education Coordinator, Wikimedia TN User Group
Member, WikiResearch Tunisia
Member, Wiki Project Med
Member, WikiIndaba Steering Committee
Member, Wikimedia and Library User Group Steering Committee
Co-Founder, WikiLingua Maghreb
Founder, TunSci
____________________
+21629499418
Wikimedia-l,
Wikitech-l,
I would like to share a new project proposal: https://meta.wikimedia.org/wiki/Wikiwisdom . The project intends to provide a large-scale, crowdsourced collection of wisdom materials (anecdotes, proverbs, quotations, lyrics, poetry, narratives and humor). The project intends to increase the ease with which people can search for, discover and share wisdom materials. The project intends to advance scholarly and scientific research into wisdom, folklore, heritage, tradition, history and culture.
Thank you for taking a look at the project proposal. You may edit the project proposal page and add yourself as an interested person. The discussion page of the project proposal is also available for discussions.
Best regards,
Adam Sobieski
http://www.phoster.com/contents/
Dear all,
we would like to share consolidated updates for the GlobalFactSync (GFS)
project with you (copied from
https://meta.wikimedia.org/wiki/Grants:Project/DBpedia/GlobalFactSyncRE/News)
We polished everything for our presentation at Wikimania tomorrow:
https://wikimania.wikimedia.org/wiki/2019:Technology_outreach_%26_innovatio…
All feedback welcome!
-- Sebastian (with the team: Tina, Włodzimierz, Krzysztof, Johannes and
Marvin)
User Script, Data Browser, Reference web service (15. August 2019)
After the Kick-Off note end of July
<https://meta.wikimedia.org/wiki/Grants:Project/DBpedia/GlobalFactSyncRE/New…>,
which described our first edit and the concept better, we shaped the
technical microservices and data into more concise tools that are easier
to use and demo during our Wikimania presentation
<https://wikimania.wikimedia.org/wiki/2019:Technology_outreach_%26_innovatio…>:
1. User Script <https://en.wikipedia.org/wiki/User_scripts> available
at User:JohannesFre/global.js
<https://meta.wikimedia.org/wiki/User:JohannesFre/global.js> shows
links from each article and Wikidata to the Data Browser and
Reference Web Service
<https://meta.wikimedia.org/wiki/User:JohannesFre/global.js>
1.
User Script Linking to the GFS Data Browser
2. GFS Data Browser <https://global.dbpedia.org/> Github
<https://github.com/dbpedia/gfs> now accepts any URI in subject from
Wikipedia, DBpedia or Wikidata, see the Boys Don't Cry example from
Kick-Off Note
<https://global.dbpedia.org/?s=https%3A%2F%2Fglobal.dbpedia.org%2Fid%2F2nrbo…>,
Berlin/Geo-coords lat
<https://global.dbpedia.org/?s=https%3A%2F%2Fglobal.dbpedia.org%2Fid%2F4pafr…>
long
<https://global.dbpedia.org/?s=https%3A%2F%2Fglobal.dbpedia.org%2Fid%2F4pafr…>,
Albert Einstein's Religion
<https://global.dbpedia.org/?s=https%3A%2F%2Fglobal.dbpedia.org%2Fid%2F55LmB…>.
*Not Live yet, edits/fixes are not reflected*
3. Reference Web Service (Albert Einstein:
http://dbpedia.informatik.uni-leipzig.de:8111/infobox/references?article=ht…)
extracts (1) all references from a Wikipedia page, (2) matched to
the infobox parameter and (3) also extracts the fact from it. The
service will remain stable, so you can use it.
Furthermore, we are designing a friendly fork of HarvestTemplates
<https://github.com/Pascalco/harvesttemplates> to effectively import all
that data into Wikidata.
Kick-off note (25. Juli 2019)
*GlobalFactSync - Synchronizing Wikidata and Wikipedia's infoboxes*
How is data edited in Wikipedia/Wikidata? Where does it come from? And
how can we synchronize it globally?
The GlobalFactSync
<https://meta.wikimedia.org/wiki/Grants:Project/DBpedia/GlobalFactSyncRE>
(GFS) Project — funded by the Wikimedia Foundation — started in June
2019 and has two goals:
* Answer the above-mentioned three questions.
* Build an information system to synchronize facts between all
Wikipedia language-editions and Wikidata.
Now we are seven weeks into the project (10+ more months to go) and we
are releasing our first prototypes to gather feedback.
/How – Synchronization vs Consensus/
We follow an absolute *Human(s)-in-the-loop* approach when we talk about
synchronization. The final decision whether to synchronize a value or
not should rest with a human editor who understands consensus and the
implications. There will be no automatic imports. Our focus is to
drastically reduce the time to research all references for individual
facts.
A trivial example is the release date of the single “Boys Don’t Cry”
(March 16th, 1989) in the English
<https://en.wikipedia.org/wiki/Boys_Don%27t_Cry_(Moulin_Rouge_song)>,
Japanese
<https://ja.wikipedia.org/wiki/%E6%B6%99%E3%82%92%E3%81%BF%E3%81%9B%E3%81%AA…'t_Cry%E3%80%9C>,
and French
<https://fr.wikipedia.org/wiki/Namida_wo_Misenaide_(Boys_Don%27t_Cry)>
Wikipedia, Wikidata <https://www.wikidata.org/wiki/Q3020026#P577> and
finally in the external open database MusicBrainz
<https://musicbrainz.org/artist/e57182dc-2693-46fc-a739-a81c734a4326>. A
human editor might need 15-30 minutes finding and opening all different
sources, while our current prototype can spot differences and display
them in 5 seconds.
We already had our first successful edit where a Wikipedia editor fixed
the discrepancy with our prototype: “I’ve updated Wikidata so that all
five sources are in agreement.” We are now working on the following tasks:
* Scaling the system to all infoboxes, Wikidata and selected external
databases (see below on the difficulties there)
* Making the system:
o “live” without stale information
o “reliable” with less technical errors when extracting and
indexing data
o “better referenced” by not only synchronizing facts but also
references
/Contributions and Feedback/
To ensure that GlobalFactSync will serve and help the Wikiverse we
encourage everyone to try our data and micro-services and leave us some
feedback, either on our Meta-Wiki page
<https://meta.wikimedia.org/wiki/Grants_talk:Project/DBpedia/GlobalFactSyncRE>
or via gfs(a)infai.org <mailto:gfs@infai.org>. In the following 10+
months, we intend to improve and build upon these initial results. At
the same time, these microservices are available to every developer to
exploit it and hack useful applications. The most promising
contributions will be rewarded and receive the book “Engineering Agile
Big-Data Systems”. Please post feedback or any tool or GUI here. In case
you need changes to be made to the API, please let us know, too. For the
ambitious future developers among you, we have some budget left that we
will dedicate to an internship. In order to apply, just mention it in
your feedback post.
Finally, to talk to us and other GlobalfactSync-Users you may want to
visit WikidataCon and Wikimania, where we will present the latest
developments and the progress of our project.
/Data, APIs & Microservices (Technical prototypes)/
Data Processing and Infobox Extraction:
For GlobalFactSync we use data from Wikipedia infoboxes of different
languages, as well as Wikidata, and DBpedia and fuse them to receive one
big, consolidated dataset – a PreFusion dataset
<https://databus.dbpedia.org/dbpedia/prefusion> (in JSON-LD). More
information on the fusion process, which is the engine behind GFS, can
be found in the FlexiFusion paper
<https://svn.aksw.org/papers/2019/ISWC_FlexiFusion/public.pdf>. One of
our next steps is to integrate MusicBrainz into this process as an
external dataset. We hope to implement even more such external datasets
to increase the amount of available information and references.
*First microservices:*
We deployed a set of microservices to show the current state of our
toolchain.
* [Initial User Interface] The GFS Data Browser is our GlobalFactSync
UI prototype (available at http://global.dbpedia.org) which shows
all extracted information available for one entity for different
sources. It can be used to analyze the factual consensus between
different Wikipedia articles for the same thing. Example: Look at
the variety of population counts for Grimma
<https://global.dbpedia.org/?s=https%3A%2F%2Fglobal.dbpedia.org%2Fid%2F9QwA&…>.
* [PreFusion JSON API] While the UI allows simple, fast and easy
browsing for one entity at a time, we also provide raw access to the
underlying data (PreFusion dump). The query UI
(http://global.dbpedia.org:8990 (user: read, pw: gfs) can be
utilized to run simple analytical queries. Thus, we can determine
the number of locations having at least one population value
<http://global.dbpedia.org:8990/db/prefusion/provenance?query=%7B%0D%0A++++%…>
(1,194,007) but can also focus on examples with data quality
problems (e.g. one of the 4,268 locations with more than 10
population values
<http://global.dbpedia.org:8990/db/prefusion/provenance?query=%7B%0D%0A++++%…>).
Moreover, documentation about the PreFusion dataset and the download
link for the data are available on the Databus website
<https://databus.dbpedia.org/dbpedia/prefusion>.
* [Reference Data Download] We ran the Reference Extraction Service
over 10 Wikipedia languages. Download dumps here
<http://dbpedia.informatik.uni-leipzig.de/repo/lewoniewski/gfs/infobox-refs/…>.
* [Reference Extraction Service] Good references are crucial for an
import of facts from Wikipedia to Wikidata. We are currently working
with colleagues from Poznań University of Economics and Business on
reference extraction for facts from Wikipedia. A current development
reference extraction microservice
<http://dbpedia.informatik.uni-leipzig.de:8111/infobox/references?article=ht…>
shows all references and the location where they were spotted in the
Infobox – ad hoc – for a given article:
http://dbpedia.informatik.uni-leipzig.de:8111/infobox/references?article=ht…
( ‘&format=tsv’ also available)
* [Infobox Extraction Service] A similar ad hoc extraction of factual
information from infoboxes and other Wikipedia article information
is available here. This microservice displays information which can
be extracted with the help of DBpedia mappings from an infobox e.g.
from the German Facebook Wikipedia article:
http://dbpedia.informatik.uni-leipzig.de:9998/server/extraction/en/extract?….
See here for more options:
http://dbpedia.informatik.uni-leipzig.de:9999/server/extraction/.
* [ID service] Last but not least, we offer the Global ID Resolution
Service
<https://global.dbpedia.org/same-thing/lookup/?uri=http://dbpedia.org/resour…>.
It ties together all available identifiers for one thing (i.e. at
the moment all DBpedia/Wikipedia and Wikidata identifiers –
MusicBrainz coming soon…) and shows their stable DBpedia Global ID.
/Finding sync targets/
In order to test out our algorithms, we started by looking at various
groups of subjects, our so-called sync targets. Based on the different
subjects a set of problems were identified with varying layers of
complexity:
* identity check/check for ambiguity — Are we talking about the same
entity?
* fixed vs. varying property — Some properties vary depending on
nationality (e.g., release dates), or point in time (e.g.,
population count).
* reference — Depending on the entity’s identity check and the
property’s fixed or varying state the reference might vary. Also,
for some targets, no query-able online reference might be available.
* normalization/conversion of values — Depending on
language/nationality of the article properties can have varying
units (e.g., currency, metric vs imperial system).
The check for ambiguity is the most crucial step to ensure that the
infoboxes that are being compared do refer to the same entity. We found,
instances where the Wikipedia page and the infobox shown on that page
were presenting information about different subjects (e.g., see here
<https://en.wikipedia.org/wiki/Boys_Don%27t_Cry_(Moulin_Rouge_song)>).
/Examples/
As a good sync target to start with the group ‘NBA players’ was
identified. There are no ambiguity issues, it is a clearly defined group
of persons, and the amount of varying properties is very limited.
Information seems to be derived from mainly two web sites (nba.com and
basketball-reference.com) and normalization is only a minor issue.
‘Video games’ also proved to be an easy sync target, with the main
problem being varying properties such as different release dates for
different platforms (Microsoft Windows, Linux, MacOS X, XBox) and
different regions (NA vs EU).
More difficult topics, such as ‘cars’, ’music albums’, and ‘music
singles’ showed more potential for ambiguity as well as property
variability. A major concern we found was Wikipedia pages that contain
multiple infoboxes (often seen for pages referring to a certain type of
car, such as this one <https://en.wikipedia.org/wiki/Volkswagen_Polo>).
Reference and fact extraction can be done for each infobox, but
currently, we run into trouble once we fuse this data.
Further information about sync targets and their challenges can be found
on our Meta-Wiki discussion page
<https://meta.wikimedia.org/wiki/Grants_talk:Project/DBpedia/GlobalFactSyncR…>,
where Wikipedians that deal with infoboxes on a regular basis can also
share their insights on the matter. Some issues were also found
regarding the mapping of properties. In order to make GlobalFactSync as
applicable as possible, we rely on the DBpedia community to help us
improve the mappings. If you are interested in participating, we will
connect with you at http://mappings.dbpedia.org and in the DBpedia forum
<https://forum.dbpedia.org/>.
Bottomline – We value your feedback!
Hi All,
Here are the minutes from this week's TechCom meeting (and sorry for the delay):
* RFC approved after last call: Heredoc arguments for templates (aka "hygienic"
or "long" arguments). Implementation will probably have to wait until Parsoid
has been ported to PHP, so we don't have to implement it three times.
<https://phabricator.wikimedia.org/T99268>
* RFC approved after last call: Abstract schemas and schema changes. This allows
database updates to be written in a form agnostic to the underlying RDBMS, using
the DBAL library. We will be dropping support for Oracle and MSSQL for core to
make this feasible. The maintainers of the Oracle and MSSQL backends have
expressed interested in adding support back as extensions.
<https://phabricator.wikimedia.org/T191231>
* RFC approved after last call: Create a proper command-line runner for
MediaWiki maintenance tasks. Implementation is pending priorization by the Core
Platform Team. <https://phabricator.wikimedia.org/T99268>.
* RFC under discussion: Set explicit PHP support target for MediaWiki.
<https://phabricator.wikimedia.org/T228342>
* The TechCom meeting on August 14 will be a public meeting held as a session at
the Wikimania Hackathon, at 15:00 Sweden time (6am in California).
* There is no RFC discussion scheduled, and no last calls ongoing.
You can also find our meeting minutes at
<https://www.mediawiki.org/wiki/Wikimedia_Technical_Committee/Minutes>
See also the TechCom RFC board
<https://phabricator.wikimedia.org/tag/mediawiki-rfcs/>.
If you prefer you can subscribe to our newsletter here
<https://www.mediawiki.org/wiki/Newsletter:TechCom_Radar>
Cheers,
Daniel
