- Wikidata has 40k organisations: 
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. 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 <hellmann@informatik.uni-leipzig.de>:

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 %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loading it into wikidata, as the data can be retrieved from the official source directly, however, here this data will not be published in a decent format.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:wikidata-bounces@lists.wikimedia.org] Im Auftrag von Sebastian Hellmann
Gesendet: Sonntag, 15.
Oktober 2017 09:45
An:
wikidata@lists.wikimedia.org
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

 

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

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
Homepage:
http://aksw.org/SebastianHellmann
Research Group:
http://aksw.org



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--
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
Homepage: http://aksw.org/SebastianHellmann
Research Group: http://aksw.org

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