ah, ok, sorry, I was assuming that Blazegraph would transitively resolve
this automatically.
Ok, so let's divide the problem:
# Task 1:
Connect all existing organisations with the data from the
handelsregister. (No new identifiers added, we can start right now)
Add a constraint that all German organisations should be connected to a
court, i.e. the registering organisation as well as the id assigned by
the court.
@all: any properties I can reuse for this?
I will focus on this as it seems quite easy. We can first filter orgs by
other criteria, i.e. country as a blocking key and then string match the
rest.
# Task 2:
Add all missing identifiers for the remaining orgs in Handelsregister.
Whereas 2 can be rediscussed and decided, if 1 is finished sufficiently.
# regarding maintenance:
I find Wikidata as such very hard to maintain as all data is copied from
somewhere else eventually, but Wikipedia has the same problem. In the
case of the German Business register, maintenance is especially easy as
the orgs are stable and uniquely identifiable. Even the fact that a
company gets shut down should still be in Wikidata, so you have
historical information. I mean, you also keep the Roman Empire, the
Hanse and even finished projects in Wikidata. So even if an org ceases
to exist, the entry in Wikidata should stay.
# regarding Opencorporates
I have a critical opinion with Opencorporates. It appears to be open,
but you actually can not get the data. If somebody has a data dump,
please forward to me. Thanks.
More on top, I consider Opencorporates a danger to open data. It appears
to push open availability of data, but then it is limited to open
licenses. Usefulness is limited as there are no free dumps and no
possibility to duplicate it effectlively. Wikipedia and Wikidata provide
dumps and an API for exactly this reason. Everytime somebody wants to
create an open organisation dataset with no barriers, the existence of
Opencorporates is blocking this.
Cheers,
Sebastian
On 16.10.2017 15:34, Antonin Delpeuch (lists) wrote:
And… my own count was wrong too, because I forgot to add DISTINCT in my
query (if there are multiple paths from the class to "organization
(Q43229)", items will appear multiple times).
So, I get 1 168 084 now.
http://tinyurl.com/yaeqlsnl
It's easy to get these things wrong!
Antonin
On 16/10/2017 14:16, Antonin Delpeuch (lists) wrote:
Thanks Ettore for spotting that!
Wikidata types (P31) only make sense when you consider the "subclass of"
(P279) property that we use to build the ontology (except in a few cases
where the community has decided not to use any subclass for a particular
type).
So, to retrieve all items of a certain type in SPARQL, you need to use
something like this:
?item wdt:P31/wdt:P279* ?type
You can also have other variants to accept non-truthy statements.
Just with this truthy version, I currently get 1 208 227 items. But note
that there are still a lot of items where P31 is not provided, or
subclasses which have not been connected to "organization (Q43229)"…
So in general, it's very hard to have any "guarantees that there are no
duplicates", just because you don't have any guarantees that the
information currently in Wikidata is complete or correct.
I would recommend trying to import something a bit smaller to get
acquainted with how Wikidata works and what the matching process looks
like in practice. And beyond a one-off import, as Ettore said it is
important to think how the data will be maintained in the future…
Antonin
On 16/10/2017 13:46, Ettore RIZZA wrote:
- Wikidata has 40k organisations:
https://query.wikidata.org/#SELECT
<https://query.wikidata.org/#SELECT> %3Fitem %3FitemLabel %0AWHERE
%0A{%0A %3Fitem wdt%3AP31 wd%3AQ43229.%0A SERVICE wikibase%3Alabel {
bd%3AserviceParam wikibase%3Alanguage "[AUTO_LANGUAGE]%2Cen". }%0A}
Hi,
I think Wikidata contains many more organizations than that. If we
choose the "instance of Business enterprise", we get 135570 results. And
I imagine there are many other categories that bring together commercial
companies.
https://query.wikidata.org/#SELECT%20%3Fitem%20%3FitemLabel%20WHERE%20%7B%0A%20%20%3Fitem%20wdt%3AP31%20wd%3AQ4830453.%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%7D%0A%7D
On the substance, the project to add all companies of a country would
make Wikidata a kind of totally free clone of Open Corporates
<https://opencorporates.com/>. I would of course be delighted to see
that, but is it not a challenge to maintain such a database? Companies
are like humans, it appears and disappears every day.
2017-10-16 13:41 GMT+02:00 Sebastian Hellmann
<[email protected]
<mailto:[email protected]>>:
Hi all,
the technical challenges are not so difficult.
- 2.2 million are the exact number of German organisations, i.e.
associations and companies. They are also unique.
- Wikidata has 40k organisations:
https://query.wikidata.org/#SELECT
<https://query.wikidata.org/#SELECT> %3Fitem %3FitemLabel %0AWHERE
%0A{%0A %3Fitem wdt%3AP31 wd%3AQ43229.%0A SERVICE wikibase%3Alabel {
bd%3AserviceParam wikibase%3Alanguage "[AUTO_LANGUAGE]%2Cen". }%0A}
so there would be a maximum of 40k duplicates These are easy to find
and deduplicate
- The crawl can be done easily, a colleague has done so before.
The issues here are:
- Do you want to upload the data in Wikidata? It would be a real big
extension. Can I go ahead
- If the data were available externally as structured data under
open license, I would probably not suggest loading it into wikidata,
as the data can be retrieved from the official source directly,
however, here this data will not be published in a decent format.
I thought that the way data is copied from coyrighted sources, i.e.
only facts is ok for wikidata. This done in a lot of places, I
guess. Same for Wikipedia, i.e. News articles and copyrighted books
are referenced. So Wikimedia or the Wikimedia community are experts
on this.
All the best,
Sebastian
On 16.10.2017 10:18, Neubert, Joachim wrote:
Hi Sebastian,____
__ __
This is huge! It will cover almost all currently existing German
companies. Many of these will have similar names, so preparing for
disambiguation is a concern.____
__ __
A good way for such an approach would be proposing a property for
an external identifier, loading the data into Mix-n-match,
creating links for companies already in Wikidata, and adding the
rest (or perhaps only parts of them - I’m not sure if having all
of them in Wikidata makes sense, but that’s another discussion),
preferably with location and/or sector of trade in the description
field.____
__ __
I’ve tried to figure out what could be used as key for a external
identifier property. However, it looks like the registry does not
offer any (persistent) URL to its entries. So for looking up a
company, apparently there are two options:____
__ __
- conducting an extended search for the exact string “A&A
Dienstleistungsgesellschaft mbH“____
- copying the register number “32853” plus selecting the
court (Leipzig) from the according dropdown list and search that____
__ __
Both ways are not very intuitive, even if we can provide a link to
the search form. This would make a weak connection to the source
of information. Much more important, it makes disambiguation in
Mix-n-match difficult. This applies for the preparation of your
initial load (you would not want to create duplicates). But much
more so for everybody else who wants to match his or her data
later on. Being forced to search for entries manually in a
cumbersome way for disambiguation of a new, possibly large and
rich dataset is, in my eyes, not something we want to impose on
future contributors. And often, the free information they find in
the registry (formal name, register number, legal form, address)
will not easily match with the information they have (common name,
location, perhaps founding date, and most important sector of
trade), so disambiguation may still be difficult.____
__ __
Have you checked which parts of the accessible information as
below can be crawled and added legally to external databases such
as Wikidata?____
__ __
Cheers, Joachim____
__ __
--____
Joachim Neubert____
__ __
ZBW – German National Library of Economics____
Leibniz Information Centre for Economics____
Neuer Jungfernstieg 21
20354 Hamburg____
Phone +49-42834-462____
__ __
__ __
__ __
*Von:*Wikidata [mailto:[email protected]
<mailto:[email protected]>] *Im Auftrag von
*Sebastian Hellmann
*Gesendet:* Sonntag, 15. Oktober 2017 09:45
*An:* [email protected]
<mailto:[email protected]>
*Betreff:* [Wikidata] Kickstartet: Adding 2.2 million German
organisations to Wikidata____
__ __
Hi all,____
the German business registry contains roughly 2.2 million
organisations. Some information is paid, but other is public, i.e.
the info you are searching for at and clicking on UT (see example
below):____
https://www.handelsregister.de/rp_web/mask.do?Typ=e
<https://www.handelsregister.de/rp_web/mask.do?Typ=e>____
__ __
I would like to add this to Wikidata, either by crawling or by
raising money to use crowdsourcing concepts like crowdflour or
amazon turk. ____
__ __
It should meet notability criteria 2:
https://www.wikidata.org/wiki/Wikidata:Notability
<https://www.wikidata.org/wiki/Wikidata:Notability>____
2. It refers to an instance of a *clearly identifiable
conceptual or material entity*. The entity must be notable, in
the sense that it *can be described using serious and publicly
available references*. If there is no item about you yet, you
are probably not notable.____
The reference is the official German business registry, which is
serious and public. Orgs are also per definition clearly
identifiable legal entities.
How can I get clearance to proceed on this?
All the best,
Sebastian____
__ __
__ __
Entity data____
__ __
Saxony District court *Leipzig HRB 32853 * – A&A
Dienstleistungsgesellschaft mbH ____
Legal status:____
Gesellschaft mit beschränkter Haftung ____
Capital:____
25.000,00 EUR ____
Date of entry:____
29/08/2016
(When entering date of entry, wrong data input can occur due to
system failures!) ____
Date of removal:____
- ____
Balance sheet available: ____
- ____
Address (subject to correction):____
A&A Dienstleistungsgesellschaft mbH
Prager Straße 38-40____
04317 Leipzig ____
__ __
--
All the best,
Sebastian Hellmann
Director of Knowledge Integration and Linked Data Technologies
(KILT) Competence Center
at the Institute for Applied Informatics (InfAI) at Leipzig University
Executive Director of the DBpedia Association
Projects: http://dbpedia.org, http://nlp2rdf.org,
http://linguistics.okfn.org, https://www.w3.org/community/ld4lt
<http://www.w3.org/community/ld4lt>
Homepage: http://aksw.org/SebastianHellmann
<http://aksw.org/SebastianHellmann>
Research Group: http://aksw.org____
_______________________________________________
Wikidata mailing list
[email protected] <mailto:[email protected]>
https://lists.wikimedia.org/mailman/listinfo/wikidata
<https://lists.wikimedia.org/mailman/listinfo/wikidata>
--
All the best,
Sebastian Hellmann
Director of Knowledge Integration and Linked Data Technologies
(KILT) Competence Center
at the Institute for Applied Informatics (InfAI) at Leipzig University
Executive Director of the DBpedia Association
Projects: http://dbpedia.org, http://nlp2rdf.org,
http://linguistics.okfn.org, https://www.w3.org/community/ld4lt
<http://www.w3.org/community/ld4lt>
Homepage: http://aksw.org/SebastianHellmann
<http://aksw.org/SebastianHellmann>
Research Group: http://aksw.org
_______________________________________________
Wikidata mailing list
[email protected] <mailto:[email protected]>
https://lists.wikimedia.org/mailman/listinfo/wikidata
<https://lists.wikimedia.org/mailman/listinfo/wikidata>
_______________________________________________
Wikidata mailing list
[email protected]
https://lists.wikimedia.org/mailman/listinfo/wikidata
_______________________________________________
Wikidata mailing list
[email protected]
https://lists.wikimedia.org/mailman/listinfo/wikidata
_______________________________________________
Wikidata mailing list
[email protected]
https://lists.wikimedia.org/mailman/listinfo/wikidata
--
All the best,
Sebastian Hellmann
Director of Knowledge Integration and Linked Data Technologies (KILT)
Competence Center
at the Institute for Applied Informatics (InfAI) at Leipzig University
Executive Director of the DBpedia Association
Projects: http://dbpedia.org, http://nlp2rdf.org,
http://linguistics.okfn.org, https://www.w3.org/community/ld4lt
<http://www.w3.org/community/ld4lt>
Homepage: http://aksw.org/SebastianHellmann
Research Group: http://aksw.org
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Wikidata mailing list
[email protected]
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