foreign
[Music]
and welcome back to the second Talk of
the
day
um this time around we have Peter Niche
and he's able to help our Alex lamb
um Peter is from he's a data nerd
describes himself as darned who works in
higher education
he's a Committee Member of the Wikimedia
Australia committee
and today he's going to give you a talk
about the wiki data which organizes the
infrastructure behind Wikipedia please
um
introduce him thank you
[Applause]
foreign thank you yes and Alex Lam is
also from Wikimedia Australia he's
currently our secretary so
um yeah today we're going to talk about
wikidata the way we'll do this is
um basically I'll give you a quick
outline of Wiki data what it is how it
works
um just a little bit of a general
introduction and then Alex who's
probably the real expert we'll take you
through just some examples and dive into
stuff in a bit more depth and we'll have
some time at the end for questions so
very happy to take those
so what is wikidata
wikidata.org is the place to go but
wikidata is an open free
multi-lingual database and that supports
Wiki media projects so it was launched
in 2012 so it's over 10 years old now
this is an example of a page that you'll
see but I'll go through in a bit more
detail about how wikidata is structured
how how it's organized
what all these things mean so
um
just briefly the origins of Wiki data so
a bit like Wikipedia
in Wikipedia we have many wikipedias
most people will be familiar with the
English Wikipedia But there are many
many different wikipedias and initially
when it was set up if you wanted to put
a photo up you had to actually put that
photo
repeatedly in each of those different
wikipedias and so
um
the way this was solved or to address
this problem this kind of redundancy was
that we create they created our Wiki
media Commons
which acts as a repository of media that
all different languaged
wikipedias could draw on
so there's a similar problem with data
so you will have seen these data boxes
in Wikipedia and these had to be done
again individually in each different
language of Wikipedia so wikidata was
created to help with that so it's really
a central data repository that all the
languages could draw on you could change
it in one place it would propagate to
all the different wikipedias quite
sensible
so and the way it's structured is very
much around linked open data principles
so and I'll talk a bit more about that
as we go in but basically all of Wiki
data is public domain cc0 freely
searchable we'll have a look at that
unique permanent identifiers and they
link out to other other databases
so in terms of identifiers the basis of
this in wikidata is the qid Q doesn't
really have any great meaning it's just
it's just what it's called but each item
or each entity in wikidata has a qid and
here are some examples
the way the information is constructed
is around like a a triple store it's a
it's a database of
relating entities together so in Wiki
day we talk about them in terms of items
properties and values so things like you
know Perth is the capital of Western
Australia Perth was you know came into
being in 1829 in terms of that entity
and also Perth was named after Perth so
that's not a particularly helpful
statement but we have
um
in terms of Wiki data we talk about that
in terms of using those IDs so they have
an ID and then the property of that ID
so
um is the capital of and then
the thing that is the value is actually
another item itself so it could be
something literal it could be a date or
a string but in this case it's another
item itself
and in terms of Perth being named after
Perth well you've got the identifier to
disambiguate things you also have
descriptions and aliases that are behind
that so
you can see that one is capital Western
Australia another one is Perth in
Scotland and they have those different
IDs
and those description and aliases are
also available in different languages
all in the one place so when that data
is pulled it can be pulled in any of
those different languages hugely hugely
time saving and quite valuable in terms
of creating a Global Knowledge base
in terms of
those identifiers
properties and values they can be
qualified so for example
Grace Hopper of pioneer computer
scientist
her given name
do I have a pointer can you see it
yeah so give a name over there
is Grace and
um so you can also
um
her family name change so there is a
qualifier here of a start time so
properties and values can be qualified
in different ways and we'll probably see
other examples of that as well so
another example you know it's just
educated at these different places and
they have a start time an end time a
major so
properties and statements can be
qualified in that way
another really powerful thing about
wikidata is that
um
although each each item has an
identifier in this case grasshopper is
q11641 we also bring in other
identifiers from other well-known
reputable sources so
[Music]
um
via VIA Disney all different identifiers
there are if you go to a Wiki P Wiki
Data Page there are you know often
dozens you know of these different
identifiers and it's a really good way
of being able to disambiguate and
connect up those identifiers in a real
linked data manner
so yeah so they're the um virtual
International Authority file and the
biblio technician Elder France they can
be both connected through this um
through this qualifier through this
property
just like Wikipedia these things can be
referenced so that reference can be a
URL it can be just like Wikipedia
um
things in Wiki day to get reference and
there can be more than one reference as
well so in this case
where Grace was educated yeah there's
three references there so again
just like Wikipedia collaboratively done
all by volunteers people putting this in
um we talk about
um instances and subclasses so the data
model is
um again it's it's
um it's been discussed and built up in a
community-based way so here's an example
of the big Merino if anyone's seen it
but it's an instance of a big thing
and an instance
also an instance of a sculpture so you
can have you know you don't have to
restrict things to us a central kind of
taxonomy but giving things instances and
subclasses allows you to do quite
interesting kind of modules so and
querying so a big thing being a subclass
of a Roadside Attraction and a sculpture
is a subclass of a visual artwork so
um
yeah
so I just probably wanted to talk about
just before I hand over to Alex
um just a little bit about
sustainability because I think this is
one of the real
um real selling points of Wiki data I
suppose is
um it's it's having an actual you know
we've all seen kind of Wikipedia and how
that works but having Wiki data as a
very powerful database the Wikimedia
Foundation
um you know sits behind all these
different projects so not just Wikipedia
there's
um you know dozens of different projects
that they support and as Wikimedia
Australia we do a small part to kind of
promote this as well and and help but
there are um many many different Wiki
Wikimedia projects
they're funded they're run by volunteers
they're collaborative so in terms of um
you know putting together knowledge
about entities it's a very it's a very
good place to put things if you want
um that information to persist into the
future so if you're kind of um you know
if your thing is
um you know Botanical illustrations or
it's
um you know ancient relics or something
and you want to create a website about
that that's great but if you put it into
Wiki data as well you can do that
communally with other people it's backed
by wikidata people can work on it I
think yeah it's it's a really good thing
to consider if
um you're kind of dealing that sort of
information
so I will hand over to Alex who's going
to kind of run through a few actual
practical demonstrations about wikidata
thanks
Peter
so as Peter mentioned
wikiwikidata.org is the uh the site the
main web interface of wikidata and um
you know it looks looks quite similar to
Wikipedia same colors uh you know
sidebar of all the the links you can go
to uh and a search search box at the top
and and your you know if you set up an
account like Wikipedia you don't have to
set up an account but it's recommended
that you do just means you can you're
what you do is is logged and uh and
tracked in your your history of
contributions and people can contact you
if they need to if you don't log in you
can still make changes but it will log
to IP address
and um that you're that you're working
on so you can set up an account it can
be anonymous like Wikipedia uh it can be
completely Anonymous you can see them
some main numbers there one 102 million
and nearly two hundred thousand data
items so obviously that's way bigger
than Wikipedia and and I think that's
one thing that it's key to point out
although Wiki data started as a
um I guess a way of structuring or
structuring data for Wikipedia as Peter
mentioned it also ties into all those
other projects that of the the Wikimedia
Foundation runs Wikimedia Commons and
and all the language editions of
Wikipedia
and so that means that wikidata is
becoming
um you know sort of kind of outgrowing
its wiki Wikipedia Origins
um and it's actually you know becoming a
really um sort of amazing and useful
um
uh tool in the whole linked open data
um in the world of linked open data
and like Wikipedia anyone can edit it as
I said you can you know just create an
account or you can even edit anonymously
so as I said this is the web interface
there's a search box here it's quite
powerful it uses elasticsearch I believe
as Peter mentioned you can have
um
several items with the same name such as
the examples of the Perth in Western
Australia and the Perth in Scotland
and but as you saw when Peter showed you
there that each item or it's page in
wikidata or item has a description and
that description can be used to
disambiguate and that's quite different
to how Wikipedia does it Wikipedia you
can't have two articles on Wikipedia
with the same name and so you have to do
disambiguation so you might have to have
Perth comma Western Australia or Perth
in bracket City in Scotland or something
like that however Wicked out is quite
different you can have two items with
the same name or multiple items with the
same name but um it's the description
which which tells them apart so let's
have a look at that Perth example I'll
type Perth in and you can see there's a
whole lot of results come up
the wa West Perth is the first one the
Scottish ones the second one and there's
also some other
parishes and places called Perth and
including the suburb which I guess is
the Central City CBD suburb
so you just click on the one that you
want there's there's more if uh if
there's something with if there's a lot
more examples
so Peter showed you the the label which
is what appears at the top there it is a
speed Dimension completely multilingual
there's about 300 languages that you can
potentially put in labels and
descriptions for it can be used for
translation you could if you can you can
use the API the search tools to actually
translate terms or place names or from
from one kind of text to another or
another language
as you can see the Korean there's no
description there so there are there are
quite a few gaps and it's all you know
being built as Peter mentioned this is
all being done by volunteers so uh
people are sort of filling in these um
these gaps as they as they find them
um so as I mentioned there's four
languages there English Korean Russian
and Maori but there's as I said there's
about 300 other 300 languages in total
and you can you can click on that to see
all the ones that have information put
in or you can click on the uh the word
English up there next to your account
name and you can actually go to it and
see the um
um yeah the list of all the languages
that there are
this is a gadget that I've installed
um Peter mentioned there that there are
tools to to reconcile Wiki data to other
data sets this is called mix and match
so it just means that it does a it
doesn't match on the name as you can see
a lot of these aren't the the Western
Australia Perth except for the second
last one there
and so that's a way that you can um that
you can link wikidata to other data sets
based on the name that you're doing that
human touch and you're taking you're
saying yes these are the same thing but
this is this is not the same thing as I
said that's an optional Gadget that I
have installed so you generally won't
see that
but here's what you will say as Peter
mentioned statements
consisting of a property and a value and
that property that value could be
another Wiki data item that it's linking
to or it could be a a string or a number
such as a year or something like that so
let's just go through it you can see you
can have an image that images from
Wikimedia Commons
and can be used to to illustrate the
item you can run queries when you I'll
show you a bit about running queries
later
uh but you can actually sort of do
queries on photos and uh and I'll tell
you a bit more about structured data in
images
there's even a map of the coordinates of
Perth
um populations locator Maps the coat of
arms
so on so and so on and many many dialing
codes and down the bottom they'll be
identifiers so identifiers can be for
people but they can also be for places
organizations
Concepts all sorts of things and it's
just really useful to have these links
to to other data sets
if you just have all those data sets
separately
uh you know they'll have sort of they'll
contain different data they might have
different people with the same name
being confused and this is this is a
really good way wikidata is a really
good way to to make sure that you know
that that
item refers to that person and there's
no duplicates I mean of course there are
some duplicates because sometimes an
import is done and a duplicate is made
but one that's one of the things that
the volunteers are working on and sort
of you know cleaning that up merging
duplicated items
so I've talked a bit about querying so
this is the wikidata query service it
uses a query language called the
delightfully named Sparkle s-p-a-r-ql
it's a bit like SQL or SQL but not quite
so you'll see some familiar terms in
there like select distinct
order by and so on but then it is a
quite it is a bit different and it's
quite different because it's not looking
at a relational database wikidat is kind
of a rdf database so it's more like a
graph
graph system with nodes and it's all
about linking one item to another item
or a value
so yeah it's I'm not going to explain or
teach you how to do Sparkle which is a
bit complicated if you do know SQL it's
a bit it's a little bit easier what I
would recommend if you're interested in
in using it there's a query Builder you
can see it at the top bar there
so it's sort of a visual query Builder
you can use a web form to to sort of
build a query and it will actually
translate that into the sparkle language
so that you can and you can actually
paste a permanent link it'll generate a
short spots for Link Link shortcut URL
and you can use that and go back to your
query anytime
it'll also translate it into Sparkle So
if you want to you know tweak that query
later you can do it what I'd also
recommend you look at is these examples
there's hundreds of examples of of
queries that other people have written
and if you can find one that does
something similar to what you want to do
it'll bring up the sparkle code for you
and you can edit it and make changes so
you might want to say uh
so I had a look at one before
a list of computer file formats
so that's the the sparkle code for this
query
play
around the query and you've got about
thirteen thousand
file extensions
media types the on the left is the qid
next column is the extension the my
media type and then the the full full
name of that
um and it's fairly quick that was like
about five seconds
um to bring up 13 000 results there are
some um issues with the the query engine
it is it can be a bit slow and it can
time out with very very complicated
queries in as you can imagine with a
data set of this size or a database of
this size that can be quite slow if you
do want to do something that's really
really really
uh complicated and requires a lot of
data you can actually download dumps of
the whole wikidata Corpus and you can
you can read it in and process that how
you want it
and there's just some exciting projects
that are
um that are using wikidata obviously
there's all the wikipedias the many
language editions of Wikipedia
structured data on Commons so Peter
showed you about Commons as a central
image Library uh contains millions and
millions of photographs diagrams and so
on
and a new project that has been put in
using wikidata is structured data so
that you can actually use these triples
that you'd use in wikidata of what
something depicts or where it was taken
where a photo was taken for example who
who took the photo or painted the
painting and so on you can you can build
up
structured data about an image
in Wikimedia Commons and that's using
the the wiki data or the wikibase engine
that's really useful for all sorts of
things obviously it makes searching for
images easier than just searching for
names or descriptions you can actually
do structured and complex queries for
images it could also be used for for
training image models in machine
learning so you can you can use that
that structured data that's sitting
behind all those images there's a new
project that's not complete yet it's
still a work in progress called abstract
Wikipedia
that's using
um
so I mentioned that there's the
multilingual aspect of wikidata where it
you have all those languages for
for everything
so languages for the labels and
descriptions but there's also a new type
you can see here lexographical data
create a new lexime so there's a whole
section of wikidata which is about
leximes which is about creating tensors
and sensors of terms and and words in in
as many languages as possible and where
that's going to become useful is that
the Wikimedia Foundation is working on a
project called abstract Wikipedia and
Wiki functions and that is uh will allow
wikipedias and Wikipedia articles to be
generated using wikidata and using the
leximes and using Wiki functions to
generate articles sort of Wikipedia
style articles in in any language even
in small languages with not many
articles on on their Wikipedia
there's also Wiki site Wiki site is a
project Creator bibliographic database
and actually if you click on random item
in wikidata they'll deserve that you'll
you'll come across pretty quickly a um
a scientific article or academic Journal
article
um because uh there's a lot of work done
on this and it's quite a that's a huge
task to to bring in every uh academic
scientific scholarly article to link
those articles to the authors the
scientists or the the um the academics
who wrote them the University or the
organization those those people work for
the authors work for and so on
um so about half of wikidata is probably
uh these sort of Articles and uh
academic and bibliographic information
that allows a really amazing this tool
called scolia which allows you to to
produce a to you know you can put an
academic or a scientist or someone who
writes articles in and it will produce
dozens of visualizations of uh of their
work and what they've they've written
about
speaking of visualizations in the query
service so I've bought a to run that
query here and there's it's brought up a
a tabular list of what I asked it for
but built in there's also a huge number
of visualizations so it's got table
there by by default but you can also do
a grid of images if you're searching
doing a search for particular types of
images or images to depict a particular
thing like you might do flags with a
lion or flags with the the um the Union
Jack on it or something like that and it
will bring all those up but the whole
you know line charts bar charts scatter
charts bubble charts Maps so Geographic
Maps if the items that you're coming up
in your query have Geographic
coordinates
or even boundary data that's loaded into
Wikimedia Commons
you can you can actually bring up maps
and display those on a on a map of the
world using openstreetmap
an openstreetmap links very well to to
wikidata wikidata links to openstreetmap
relations and also and nodes lines and
so on but also openstreetmap very widely
uses Wiki data for for many purposes
um including you know just for for
showing logos of companies or
um and for linking to the the Wikipedia
articles
me
and so you can download the the results
of your queries as some
Json
tsv tabs operated values CSV or an HTML
table
and best of all there's a code
option so you have all these options to
um
generate code in HTML PHP JavaScript
Java Perl python Ruby R Matlab
listeria is a um is a particular module
for Wikipedia projects to generate
tables
and and map frames so
um yeah that's uh I'll show you a
example and say python
so you might have to install
um you know some some libraries and
plugins to to
communicate with the the wiki data API
but yeah once you've done that you can
you can run your query in Sparkle which
you said you can generate it and uh and
um and then we'll get this you can
download put this code into your
software and load that as a data frame
and as I said you can generate a
permanent link to your query so if you
want to
post it you don't it can be on Wikimedia
but you can post it on a you know if you
want to put it on a blog or email it to
someone and just say here's a query I've
done
for this topic
um yeah so
that's
the demo
the types of tools a heap number tools
so the tools use the wiki data and
wikibase API if you want to build your
own tools like I said you can become
okay with that API but there's dozens
and dozens of tools I've been using
wikidata for years and every even every
time I meet meet someone who is also
interested in this they they find that
they haven't uh
um you know they tell me about tools
that I haven't heard of and
yeah the wikidata is amazing for doing
research on Wikipedia like I said
because it kind of forms the backbone of
Wikipedia a lot of researchers and
academics doing work about how Wikipedia
works can use wikidata to do queries of
of things like um you know how many
edits an article has got or when it was
started when it was created or when it
when it got to the most edits
the whole Community there that Peter
mentioned the the Wikimedia Community is
always willing to help you and if you do
have a
not sure how to write a query and you
can't find an example in the those
examples or
it's too complicated for the query
visual query Builder you can absolutely
ask click on that help
and it will take you to a page where you
can you can ask for someone to develop a
query for you and they'll usually get
back to you within a day or two
in the instance instances and subclasses
on a on an article
um
what makes this really powerful is it's
uh the subclasses could be can be
recursive and that means that you can
you can actually
um
do a query that uh you know sort of goes
as more as detailed or as or as far back
as you like and it can sort of actually
recurse into that so Peter showed you
the big things and there are subclass of
sculpture or a subclass of tourist
attraction you could sort of do a query
for tourist attractions and it would
find things that are an instance of
something that is a type of tourist
attraction
um it just means you can use it as a to
build up ontologies and vocabularies
um uh so you know and and that can be
that can be searched and scanned
um in the in the graph that it's uh
stored in
okay so um that's all to show you today
um
is there any questions
anything else
um
song
hello uh hello
um thank you that was very interesting
um you mentioned Imports and an API and
I was just wondering about some
information about if I assume people are
from that automatically importing data
into this system and I just wanted uh
kind of how that happened technically
and also socially as well yeah yeah it's
a good good question
um so
there are ways to I didn't show it to
you but there's a there's a system
called quick statements where where you
can generate a sort of table or sort of
tab delimited table of these triples
that the wikidata is stored in so you
you have one queue number and then the
property and then another queue number
and so on so it just runs those and
that's a way to sort of do Imports but
yeah you're right socially there there
is an issue if you're just grabbing a
data set you know
importing a huge data set and as I said
it's very important that you have these
things as you know that there's only
sort of one instance of a particular
person or a particular company or a
particular town or you know Village or
something
um in the the system so uh yeah there
are tools to
um so there's a tool called mix and
match
um
which is um I can show you that's on one
of those slides as well
so mix and match uses these uh sort of
has a huge number of thousands of
catalogs so these are essentially data
sets
the system uh so you know you've got a
lot of ones about video games
and uh what it does basically is it
loads the data set in tries to match it
to a wikidata item and uh and then if
the name matches and it's pretty sure
it's the same thing it'll preliminarily
match it but what it wants is a human to
come in you know with someone one of the
volunteers to come in and look at that
and go no that's definitely not the same
person in
wikidata in the data set
um so or you know yes it definitely is
so there's a lot of these there's as I
said there's thousands of these catalogs
for all sorts of data sets from all
sorts of from all over the web
um and uh you know the various levels of
matching so these video games yeah I'll
show you a quick example let's look at
some unmatched ones
90s arcade racer
uh and so so yeah it'll check check
Wikipedia it'll check um Wiki data it'll
um and it'll check other other catalogs
and uh if I go oh well I'm pretty sure
this this item isn't already in Wiki
data I can create a new item and it will
automatically match it to this catalog
so yeah you're right it's very important
that not to just dump a whole data set
in there
um it's good to use tools like this to
to sort of reconcile what is already in
wikidata and Wikipedia with um the the
data set that you're uploading so yeah
excellent questions
used is open refine as well so there's a
plug-in like built into that so it
allows you to query Wiki data directly
and do that reconciliation as well and
it'll generate those quick statements
for you to then then upload as well so
it's a very common way what how people
can look at data and match it up as well
so maybe a sort of follow-on question
from that the there's a lot of data in
Wikipedia itself that isn't in Wiki data
so you mentioned Perth and if you look
at Wikipedia itself if you go to the
language drop down it's got perf as an
article in 100 other languages which
isn't in Wiki data
um so maybe there is an API to copy that
across but to me it seems like that's
duplicating data as well and Wikipedia
is kind of a related projects that have
have been like considerations in
actually just store the data in
Wikipedia and then extract it to Wiki
data
yeah um
that's true there's not um I mean not
everything everything in Wikipedia is in
wikidata the languages like where
there's an article in one language in
another that's that's how it is managed
on Wikipedia is using wikidata so
um I could bring back Perth
so all the um
right down the bottom I should have
chosen a shorter one
so these are all the the language
editions of Wikipedia with an article
about this this item
but yeah not everything uh in all of
those languages or in all bits of data
even sort of relevant bits of data are
necessarily in those languages and yeah
that's that's you know something that
can be built up um as I mentioned there
is a Wikimedia API so it's not just
using wikidata but there's a tool called
pet scan and that actually can use
um all sorts of aspects of uh and
metadata about Wikipedia articles
Wikimedia Commons and Wiki data will all
combined so it's very powerful tool it's
not just doing a query but you can
include queries from wikidata and
combine them with with information so as
she said if you're doing you know if you
do want information about the Wikipedia
article when it was created and you know
how many page views it got and so on you
can use these tools to sort of
um to sort of combine all those
resources and tools together
um this is more of a comment but this
conference doesn't have a Wiki data
entry
what if people want to go and create one
it'd probably be useful
excellent point and I did I did you're
right I did find that five minutes ago
uh we got about to you know 10 minutes
before I was just going to going to edit
and then so it wasn't on it so yes we
can definitely do something about that
thanks for pointing it out
yeah anyone can add that yeah
I can't see any questions so I'll pop
one in
um one of the things that I sometimes
consult on Wikipedia is the edit history
and discussion page because there are
some things that not settled and
obviously reading them
reveals what's silver and what's not
like this is a repository a facts I
presume the same sort of disputes arise
is is it have a similar mechanism you
can consult over what's in dispute and
what's certain yeah it's very similar
it's almost you know exactly the same
here so which item has a talk page but I
guess they're not as widely used as
was on Wikipedia and meant that's why
maybe that's a good thing they probably
don't the the discussions don't get as
heated as they may on Wikipedia I think
that's one thing I do like about
wikidata it's a lot less uh you know
there's a very collaborative Community
but it's uh you know not not as uh I
guess um prone to to edit Wars and
arguments uh you know it is Data it's
supposed to be factual so
um and but just like Wikipedia every
there's a history edit history and you
can put you know edit comments in and so
on so it's very similar in that regard
everything's logged uh if you did say
import something and and it was wrong
like I once imported all these Heritage
items in Perth in Fremantle and and uh I
got the coordinates I rounded the off
the coordinates too much and so you know
but it's very easy to if it's easy to
put it in it's also easy to
um remove it or remove sort of bits of
data like that too so
and yeah as I said it's all it's all
logged and you can roll things back and
revert them to to where they were if
someone does do do any vandalism
vandalism yeah
um the other part of that is the whole
entire ontology and information model is
also Community built as well so there's
a lot of discussion around what are the
classes what are the subclasses um how
does that actually work so you know it's
it's not kind of designed perfectly from
from the top down so you know there may
be issues but they're they're worked out
in that same way they're discussed and
talked about and agreed upon so you end
up with something that ultimately should
be should be really useful for the
community so anyone could add an item
like an object or a thing or a concept
but for the properties those are the you
know the things that the middle of the
triple
um they're they're sort of I guess
proposed to the community and the
community discusses whether they're is
it needed is it is there another one
that can be used or in you know yes this
one sounds good we can bring it in so
that's uh yeah that's one of the many
things the community sort of does so
there's a balance between anyone can
edit and can doing anything but some
things are I do have discussions and uh
and the community deciding if that's
appropriate
people you'll get another boring
question from me
it's a smoking gift I might actually ask
one
um speaking of community and consensus
this is a tool comprised of many many
many sophisticated tools could you give
us an overview of
how the community reached consensus to
say create the qid
a lot of effort I'm sure went into that
well that's interesting the qid is um
like um people saying you know why is it
queue who knows it was actually
um
uh a the developer who was who kind of
built the the wikibase software that
wikidata uses
um his girlfriend's name started with Q
so that's why he chose the letter Q
so so there is a reason for it
um yeah it's I
I guess not in terms of that initial
development it was developed uh by you
know probably of quite a small number of
developers at Wikimedia Deutschland
which is the the German
chapter of the Wikimedia Foundation
um and yeah I think that was it was just
kind of they they produced it as a sort
of proof of concept and then and then
kind of handed it over to the community
so I think there's a lot of things like
you know qids and so on that aren't
necessarily
you know build up for built from the
ground up by the community but uh but
you know there were sort of handed over
to and managed by the community but but
it was probably just yeah it's developed
by some by you know some
Foss developers in Germany
and Wikimedia Deutschland in Germany
still sort of manages I guess a lot of
the the administration and so on of that
project
um you are of any major projects not
managed by the Wikimedia Foundation that
make use of this wikidata database and
what sorts of use cases are you aware of
for this thing that likewise aren't
managed by the Wikipedia Foundation
yeah that aren't
um
so I guess the wiki site one that I
mentioned that was that was I mean it's
kind of community it was a completely
Community Driven thing it's actually I
think I think it's kind of wound up now
like it's not it did get some funding
from the Wikimedia Foundation that um
uh but but you know simply still got
ongoing on a volunteer basis
um can you think of any
incident Foundation
the other one I can think of is actually
that example how it showed of the file
formats there is um I know there's
um
a group who have extended that because
the wiki data didn't have quite enough
that they needed so they've gone and
created their own
um you know equivalent for file formats
that you can search
um yeah but they may well be others
because yeah it is all open source and
people are actually not just a typical
so the uh the info you know those info
boxes I mean Peter showed the ones that
were in Wikipedia articles but the uh
the ones that uh the knowledge graph or
knowledge boxes that are in Google and
um
uh you know iOS and so on you know the
the Siri knowledge boxes there they they
are generated from from wikidata so
um yeah there's some things I guess the
sort of you know big companies that uh
millions and millions of people use are
using it so yeah um
all right people will have to put a bit
of core close there if we come to the
end of the time
um I'd like you to thank Peter and Alex
uh it was you this is the sort of talks
I come to these conferences to hear
about something I've never heard about
before or
I knew about rdf but I had no idea that
it was put to this use so thank you very
much to both of you thanks
[Applause]