Giving knowledge back to Wikipedia: Towards a Systematic Approach to Sync Factual Data across Wikipedia, Wikidata and External Data Sources

Wed, 03 Feb 2021 15:15:00 +0000

Since the beginning of DBpedia, there was always a strong consensus in the community, that one of the goals of DBpedia was to feed semantic knowledge back into Wikipedia again to improve its structure and data quality. It was a topic of many discussions over the years how to achieve this goal. No progress was made — not for the lack of motivation, but for lack of an effective AND efficient approach.

When DBpedia started over 13 years ago, two major impacts were made:

It was the first showcase of the potential of open knowledge graphs through the semantification of Wikipieda’s knowledge which proved useful for the development of thousands of Semantic Web applications and technologies (such as DBpedia Mobile from 2008, long before any knowledge-rich map viewers existed).
DBpedia played a major role as a nucleus, glueing the de-central web of data together into what has grown into the largest (de-centrally-stored, constantly updated) knowledge graph on earth – the linked data web.

Giving knowledge back to Wikipedia

Wikimedia Grant

We received a Wikimedia Grant for our project GlobalFactSyncRE and re-iterated the issue again. After almost two years of working on the topic, we would like to announce our final report. We submitted a summary of this report to the Qurator conference:

Towards a Systematic Approach to Sync Factual Data across Wikipedia, Wikidata and External Data Sources. Sebastian Hellmann, Johannes Frey, Marvin Hofer, Milan Dojchinovski, Krzysztof Wecel and Włodzimierz Lewoniewski.
Please find our self-archived e-print here.

Upcoming Presentation

Don’t miss the talk: Thur, Feb 11th, 2021 @ 10:45 a.m. CET/UTC + 1 as part of the Qurator Conference. Advance registration (for the Scientific Workshop I) necessary.

Highlights of the paper

In sum, we laid a good foundation, but also have many things unfinished. The good thing about the paper is that it brings together many aspects that require attention and drafts a roadmap to bring external data into Wikipedia from Linked Data via DBpedia.
Wikipedia’s infoboxes are still growing a lot. Overall, 150 % in the largest 140 Wikipedias and 200 % for English over the last 3 years.
We could extract and analyse 725 million infobox facts from the largest 140 Wikipedias and 8.8 million references from the largest 11 Wikipedias.
We compared existing data in Wikidata with infoboxes from 40 Wikipedias for ~200 infobox parameters and only found a 20% overlap. Wikidata needs to grow quite a lot in the right direction to be fit to replace the rich and growing infoboxes in Wikipedia, it seems.

Read the submitted paper here.

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Yours,

DBpedia Association

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Chaudron, chawdron , cauldron and DBpedia

Tue, 30 Oct 2018 09:29:56 +0000

Meet Chaudron

Before getting into the technical details of, did you know the term Chaudron derives from Old French and denotes a large metal cooking pot? The word was used as an alternative form of chawdron which means entrails. Entrails and cauldron – a combo that seems quite fitting with Halloween coming along.

And now for something completely different

To begin with, Chaudron is a dataset of more than two million triples. It complements DBpedia with physical measures. The triples are automatically extracted from Wikipedia infoboxes using a pattern-matching and a formal grammar approaches. This dataset adds triples to the existing DBpedia resources. Additionally, it includes measures on various resources such as chemical elements, railway, people places, aircrafts, dams and many other types of resources.

Chaudron was published on wiki.dbpedia.org and is one of many other projects and applications featuring DBpedia.

Want to find out more about our DBpedia Applications? Why not read about the DBpedia Chatbot, DBpedia Entity or the NLI-Go DBpedia Demo.?

Happy reading & happy Halloween!

Yours DBpedia Association

PS: In case you want your DBpedia tool, demo or any kind of application published on our Website and the DBpedia Blog, fill out this form and submit your information.

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