#dbpedia — Public Fediverse posts

#KDAI2026 lecture no 11. This time it's interrogation tactics: FILTER, REGEX, OPTIONAL, UNION, negation, BIND, and GROUP BY aggregates in SPARQL.

Then a bounty comparison: DBpedia (1.32B triples, built from Wikipedia infoboxes) vs Wikidata (17.6B triples, ~29K editors)

Closing out with OWL: Description Logic SROIQ(D), etc.

See you space cowboy…

#SemanticWeb #KnowledgeGraphs #SPARQL #DBpedia #Wikidata #OWL #LinkedData #AIeducation @fiz_karlsruhe @KIT_Karlsruhe @fizise #AI #cowboybebop

#KDAI2026 lecture no 11. This time it's interrogation tactics: FILTER, REGEX, OPTIONAL, UNION, negation, BIND, and GROUP BY aggregates in SPARQL.

Then a bounty comparison: DBpedia (1.32B triples, built from Wikipedia infoboxes) vs Wikidata (17.6B triples, ~29K editors)

Closing out with OWL: Description Logic SROIQ(D), etc.

See you space cowboy…

#SemanticWeb #KnowledgeGraphs #SPARQL #DBpedia #Wikidata #OWL #LinkedData #AIeducation @fiz_karlsruhe @KIT_Karlsruhe @fizise #AI #cowboybebop

J'ai trouvé deux sites d'archives départementales qui réutilisent Wikimédia pour enrichir les pages sur les communes. #wikimedia #wikidata #dbpedia #Archives #Archivistodons

J'ai trouvé deux sites d'archives départementales qui réutilisent Wikimédia pour enrichir les pages sur les communes. #wikimedia #wikidata #dbpedia #Archives #Archivistodons

#DBPEDIA aepiot.com?lang=hy&q=DB... #LONG #BLOCKCHAIN aepiot.com?lang=hy&q=LO... aepiot.com

MultiSearch Tag Explorer

⏰ Reminder: HMC FAIR Friday Seminar

How can FAIR infrastructures actually help researchers instead of increasing complexity?

Join Sebastian Hellmann and Jan Forberg for a pragmatic discussion on FAIR data practices and open-source infrastructure.

📅 27 March 2026 | Online
🔗 Register here: https://events.hifis.net/event/3754

#FAIR #ResearchData #OpenScience #Databus #MOSS #DBpedia

@dbpedia @helmholtz

⏰ Reminder: HMC FAIR Friday Seminar

How can FAIR infrastructures actually help researchers instead of increasing complexity?

Join Sebastian Hellmann and Jan Forberg for a pragmatic discussion on FAIR data practices and open-source infrastructure.

📅 27 March 2026 | Online
🔗 Register here: https://events.hifis.net/event/3754

#FAIR #ResearchData #OpenScience #Databus #MOSS #DBpedia

@dbpedia @helmholtz

📢 HMC FAIR Friday Seminar

More than a decade after the FAIR Principles were introduced, a key question remains:

👉 What value has FAIR actually delivered to researchers?

In this talk, Sebastian Hellmann and Jan Forberg explore the microeconomics of FAIR adoption and present open-source tools #Databus and #MOSS from the #DBpedia Association ecosystem.

📅 27 March 2026 | Online
🔗 Register here: https://helmholtz-metadaten.de/events/fair-reality-check

#HMC_FAIRfriday #KnowledgeGraphs #LinkedData

@dbpedia
@helmholtz

📢 HMC FAIR Friday Seminar

More than a decade after the FAIR Principles were introduced, a key question remains:

👉 What value has FAIR actually delivered to researchers?

In this talk, Sebastian Hellmann and Jan Forberg explore the microeconomics of FAIR adoption and present open-source tools #Databus and #MOSS from the #DBpedia Association ecosystem.

📅 27 March 2026 | Online
🔗 Register here: https://helmholtz-metadaten.de/events/fair-reality-check

#HMC_FAIRfriday #KnowledgeGraphs #LinkedData

@dbpedia
@helmholtz

The current activities on the #DBpedia issue board (https://github.com/dbpedia/extraction-framework/issues) are curious: While there is no reaction by the maintainers on (mine and other) issues, there are a lot responses by enthusiastic users volunteering to work on the issues. Even if each of these comments looks valid on its own, the accumulation and similarity of them makes me doubt these users are all actual humans.

The current activities on the #DBpedia issue board (https://github.com/dbpedia/extraction-framework/issues) are curious: While there is no reaction by the maintainers on (mine and other) issues, there are a lot responses by enthusiastic users volunteering to work on the issues. Even if each of these comments looks valid on its own, the accumulation and similarity of them makes me doubt these users are all actual humans.

Added a hotfix to the #ABECTO space data comparison project: https://github.com/fusion-jena/abecto-space-travel-comparison/commit/4ec43c8e317e5f0535e82d85e217795894ed7751
Ironically, the hotfix is to use #Wikidata classes to locally query the fetched #DBpedia data. At the next regular refresh, on 2026-01-10, mismatches based on properly aligned data will be available in https://mismatch-finder.toolforge.org/. Unfortunately, I can not invalidate the current mismatches before.
@nightrose @wikidata

Added a hotfix to the #ABECTO space data comparison project: https://github.com/fusion-jena/abecto-space-travel-comparison/commit/4ec43c8e317e5f0535e82d85e217795894ed7751
Ironically, the hotfix is to use #Wikidata classes to locally query the fetched #DBpedia data. At the next regular refresh, on 2026-01-10, mismatches based on properly aligned data will be available in https://mismatch-finder.toolforge.org/. Unfortunately, I can not invalidate the current mismatches before.
@nightrose @wikidata

Surprisingly, I could not find an Issue about this #DBpedia problem. Now there is one: https://github.com/dbpedia/extraction-framework/issues/820

Contrary to my initial guess of an extractor bug, further investigations made an SPARQL endpoint (#openlinksw #virtuoso) bug seem more likely.

Surprisingly, I could not find an Issue about this #DBpedia problem. Now there is one: https://github.com/dbpedia/extraction-framework/issues/820

Contrary to my initial guess of an extractor bug, further investigations made an SPARQL endpoint (#openlinksw #virtuoso) bug seem more likely.

Remarkably:
➡️ Despite the lack of #DBpedia types, equivalent #Wikidata types are present in DBpedia.
➡️ Not all resources are affected: e.g. https://dbpedia.org/page/John_Young_(astronaut) is typed as http://dbpedia.org/ontology/Astronaut.
➡️ Right and wrong typed astronauts have the astronaut infobox (which is properly mapped https://mappings.dbpedia.org/index.php/Mapping_en:Infobox_astronaut) on #Wikipedia.

I guess an extractor bug 🪲.

Side effect: Many astronauts are displayed as "animals". Although on might consider this as ontologically correct, it is quiet odd.

@dbpedia

Remarkably:
➡️ Despite the lack of #DBpedia types, equivalent #Wikidata types are present in DBpedia.
➡️ Not all resources are affected: e.g. https://dbpedia.org/page/John_Young_(astronaut) is typed as http://dbpedia.org/ontology/Astronaut.
➡️ Right and wrong typed astronauts have the astronaut infobox (which is properly mapped https://mappings.dbpedia.org/index.php/Mapping_en:Infobox_astronaut) on #Wikipedia.

I guess an extractor bug 🪲.

Side effect: Many astronauts are displayed as "animals". Although on might consider this as ontologically correct, it is quiet odd.

@dbpedia

With ABECTO 3.1.5, I restored regular pushes of space travel data deviations between #Wikidata and #DBpedia to https://mismatch-finder.toolforge.org @nightrose. But it provides (at first glance) strange results (🔗 https://mismatch-finder.toolforge.org/results?ids=Q107667|Q115651852), like:
➡️ John Young member of the crew of Apollo 16 mismatches http://dbpedia.org/resource/Apollo_16
➡️ SpaceX Crew-10 crew member Anne McClain mismatches http://dbpedia.org/resource/Anne_McClain

Reason: Missing http://dbpedia.org/ontology/SpaceMission, http://dbpedia.org/ontology/Astronaut, … type statements in @dbpedia.

With ABECTO 3.1.5, I restored regular pushes of space travel data deviations between #Wikidata and #DBpedia to https://mismatch-finder.toolforge.org @nightrose. But it provides (at first glance) strange results (🔗 https://mismatch-finder.toolforge.org/results?ids=Q107667|Q115651852), like:
➡️ John Young member of the crew of Apollo 16 mismatches http://dbpedia.org/resource/Apollo_16
➡️ SpaceX Crew-10 crew member Anne McClain mismatches http://dbpedia.org/resource/Anne_McClain

Reason: Missing http://dbpedia.org/ontology/SpaceMission, http://dbpedia.org/ontology/Astronaut, … type statements in @dbpedia.

An unconventional approach to avoid providing an email address in the User-Agent was chosen in #DBpedia by reusing the user agent of #curl: https://github.com/dbpedia/extraction-framework/commit/de3ca70694f347db84a2daeb88d8218506075f81
I proposed an alternative: https://github.com/dbpedia/extraction-framework/issues/819

@dbpedia @wikidata

An unconventional approach to avoid providing an email address in the User-Agent was chosen in #DBpedia by reusing the user agent of #curl: https://github.com/dbpedia/extraction-framework/commit/de3ca70694f347db84a2daeb88d8218506075f81
I proposed an alternative: https://github.com/dbpedia/extraction-framework/issues/819

@dbpedia @wikidata

@awinkler @DNB_Aktuelles Bei "Examples" das aktuell letzte Beispiel: "Welche Titel von anderen Autoren gehören zur gleichen literarischen Gattung wie Friedrich Schiller?" https://sparql.dnb.de/dnbgnd/tRteun zeigt die Federated Query mit dbpedia
#dbpedia

@awinkler @DNB_Aktuelles Bei "Examples" das aktuell letzte Beispiel: "Welche Titel von anderen Autoren gehören zur gleichen literarischen Gattung wie Friedrich Schiller?" https://sparql.dnb.de/dnbgnd/tRteun zeigt die Federated Query mit dbpedia
#dbpedia

Slides for first #DBpedia talk by Sebastian Hellmann at #SemanticsConf sit at https://docs.google.com/presentation/d/1EDl3Yc3nicA_a9HYYqC1BEC7OTb8cXDmga0xRwwvI7c/edit?usp=drivesdk .

Slides for first #DBpedia talk by Sebastian Hellmann at #SemanticsConf sit at https://docs.google.com/presentation/d/1EDl3Yc3nicA_a9HYYqC1BEC7OTb8cXDmga0xRwwvI7c/edit?usp=drivesdk .

@naturzukunft
Actually, this is WIkipedia and only structured data, i.e. no RDF.
However, use this SPARQL query on DBpedia to get vitamins and minerals of a cucumber ;-)

https://dbpedia.org/sparql?default-graph-uri=http%3A%2F%2Fdbpedia.org&qtxt=SELECT%20*%20WHERE%20%7B%0A%20dbr%3ACucumber%20%3Fp%20%3Fo%20.%20FILTER%20regex%20(%3Fp%2C%20%22%5BMU%5Dg%22).%0A%7D%0A%0A%0A&format=text%2Fhtml&timeout=30000&signal_void=on&signal_unconnected=on

#sparql #rdf #dbpedia #wikidata #cucumber #dbpedia @dbpedia #semanticweb #knowledgegraphs

@naturzukunft
Actually, this is WIkipedia and only structured data, i.e. no RDF.
However, use this SPARQL query on DBpedia to get vitamins and minerals of a cucumber ;-)

https://dbpedia.org/sparql?default-graph-uri=http%3A%2F%2Fdbpedia.org&qtxt=SELECT%20*%20WHERE%20%7B%0A%20dbr%3ACucumber%20%3Fp%20%3Fo%20.%20FILTER%20regex%20(%3Fp%2C%20%22%5BMU%5Dg%22).%0A%7D%0A%0A%0A&format=text%2Fhtml&timeout=30000&signal_void=on&signal_unconnected=on

#sparql #rdf #dbpedia #wikidata #cucumber #dbpedia @dbpedia #semanticweb #knowledgegraphs

https://www.dbpedia-spotlight.org/ a tool for automatically annotating mentions of DBpedia resources in text, providing a solution for linking unstructured information sources to the Linked Open Data cloud through DBpedia. #wikipedia #semanticweb #dbpedia

https://www.dbpedia-spotlight.org/ a tool for automatically annotating mentions of DBpedia resources in text, providing a solution for linking unstructured information sources to the Linked Open Data cloud through DBpedia. #wikipedia #semanticweb #dbpedia

#Google Gemini 2.0 now passes my “deceptively simple” test: generating #SPARQL queries against the #DBpedia #KnowledgeGraph.

This marks the first time Gemini LLMs have succeeded in my testing. Ironically, it’s less about core #LLM capability and more about overcoming strange safeguards and link aversion.

#AI #GenAI #LLMs

#Google Gemini 2.0 now passes my “deceptively simple” test: generating #SPARQL queries against the #DBpedia #KnowledgeGraph.

This marks the first time Gemini LLMs have succeeded in my testing. Ironically, it’s less about core #LLM capability and more about overcoming strange safeguards and link aversion.

#AI #GenAI #LLMs

Boom!

The OpenLink Software #AI Layer (#OPAL) now supports AnthropicAI's #Claude language models.

See comments for a #DataTwingler AI Agent demo executing #SPARQL and #SQL queries via a live #VirtuosoRDBMS instance.

Remember, query scope is SPARQL, #ODBC, or #JDBC accessible data sources.

#GenAI #UseCase #DBpedia #KnowledgeGraph #LinkedData #LODCloud

Boom!

The OpenLink Software #AI Layer (#OPAL) now supports AnthropicAI's #Claude language models.

See comments for a #DataTwingler AI Agent demo executing #SPARQL and #SQL queries via a live #VirtuosoRDBMS instance.

Remember, query scope is SPARQL, #ODBC, or #JDBC accessible data sources.

#GenAI #UseCase #DBpedia #KnowledgeGraph #LinkedData #LODCloud

Here's the #screencast demo of Grok generating a #SPARQL query results page for a #DBpedia #KnowledgeGraph query.

Here's the #screencast demo of Grok generating a #SPARQL query results page for a #DBpedia #KnowledgeGraph query.

#Grok (v2) just passed my #SPARQL query generation test on the #DBpedia #KnowledgeGraph! It can now generate a link resolving to all movies directed by Spike Lee from my test prompt. x.com/i/grok/share... Links are shareable too—this is HUGE for #GenAI & #SocialMedia posts! #AI #LinkeData

@Grok (v2) just passed my #SPARQL query generation test on the #DBpedia #KnowledgeGraph! It can now generate a link resolving to all movies directed by Spike Lee from my test prompt.

https://x.com/i/grok/share/mnGYuedRFavNWaQk4XxjUPVm1

Links are shareable too—this is HUGE for #GenAI & #SocialMedia posts!

@Grok (v2) just passed my #SPARQL query generation test on the #DBpedia #KnowledgeGraph! It can now generate a link resolving to all movies directed by Spike Lee from my test prompt.

https://x.com/i/grok/share/mnGYuedRFavNWaQk4XxjUPVm1

Links are shareable too—this is HUGE for #GenAI & #SocialMedia posts!

New Qwen-QwQ-32 LLM passes my tricky
#DBpedia #SPARQL query results link test.

Prompt:
Using the DBpedia endpoint, list all movies directed by Spike Lee and encode the sparql query in a clickable link.

Result:
https://dbpedia.org/sparql?query=SELECT%20%3Fmovie%20WHERE%20%7B%20%3Fmovie%20%3Chttp%3A%2F%2Fdbpedia.org%2Fontology%2Fdirector%3E%20%3Chttp%3A%2F%2Fdbpedia.org%2Fresource%2FSpike_Lee%3E%20.%20%7D&format=text%2Fhtml

Chat:
https://huggingface.co/spaces/Qwen/QwQ-32B-preview

New Qwen-QwQ-32 LLM passes my tricky
#DBpedia #SPARQL query results link test.

Prompt:
Using the DBpedia endpoint, list all movies directed by Spike Lee and encode the sparql query in a clickable link.

Result:
https://dbpedia.org/sparql?query=SELECT%20%3Fmovie%20WHERE%20%7B%20%3Fmovie%20%3Chttp%3A%2F%2Fdbpedia.org%2Fontology%2Fdirector%3E%20%3Chttp%3A%2F%2Fdbpedia.org%2Fresource%2FSpike_Lee%3E%20.%20%7D&format=text%2Fhtml

Chat:
https://huggingface.co/spaces/Qwen/QwQ-32B-preview

The release of #ABECTO v3.1.1 also allowed me to reactivate the regular mismatch uploading to the #Wikidata Mismatch Finder by an example project that compares space travel 🚀 data in Wikidata and #DBpedia (https://github.com/fusion-jena/abecto-space-travel-comparison). Reported mismatches wait on https://mismatch-finder.toolforge.org/ to be fixed in Wikidata or #Wikipedia 🔍.

@wikipedia @wikidata @dbpedia @nightrose

The release of #ABECTO v3.1.1 also allowed me to reactivate the regular mismatch uploading to the #Wikidata Mismatch Finder by an example project that compares space travel 🚀 data in Wikidata and #DBpedia (https://github.com/fusion-jena/abecto-space-travel-comparison). Reported mismatches wait on https://mismatch-finder.toolforge.org/ to be fixed in Wikidata or #Wikipedia 🔍.

@wikipedia @wikidata @dbpedia @nightrose

@wdscholia @jerven, I just remembered this morning early efforts for making SPARQL queries primary, citable, FAIR research output with MyExperiment.org (2009!): https://www.myexperiment.org/workflows/962.html

#sparql #dbpedia #semweb

@wdscholia @jerven, I just remembered this morning early efforts for making SPARQL queries primary, citable, FAIR research output with MyExperiment.org (2009!): https://www.myexperiment.org/workflows/962.html

#sparql #dbpedia #semweb

Как принудительно уронить MS SQL Server чтобы он ушёл на перезагрузку

При чтении логов из базы данных, а именно, из LDF данных, в большинстве случаев вы наткнётесь на такие функции в запросе sys.fn_dblog(null, null), sys.fn_dblog_xtp(null, null) Читать из LDF Вы захотите по различным причинам, но так или иначе основная проблема будет "у нас откуда-то списались деньги остатки, пропал товар, упал прод, разберитесь". Допустим, Вы захотите воскресить удалённый, дропнутый объект из базы. Типичный скрипт Посмотреть код

https://habr.com/ru/articles/828178/

#sql #sql_server #dba #dbms #dbpedia #db #dbs

SPARQL federated queries were also on our list at last week's #ISE2024 lecture, combining #DBpedia and #wikidata, asking the question "which 'planetary romance' scifi novels are dealing with Mars” ?" ...would you know?

slides: https://drive.google.com/file/d/17gEglymV3_feQrkxGRw7XslxRxpGhD4b/view?usp=drive_link
SPARQL query: https://w.wiki/AY2S
SPARQL result: https://w.wiki/AY2T

#SPARQL #semanticweb #knowledgegraphs @wikidata @dbpedia @sourisnumerique @enorouzi @shufan @fizise #scifi #mars #lecture

SPARQL federated queries were also on our list at last week's #ISE2024 lecture, combining #DBpedia and #wikidata, asking the question "which 'planetary romance' scifi novels are dealing with Mars” ?" ...would you know?

slides: https://drive.google.com/file/d/17gEglymV3_feQrkxGRw7XslxRxpGhD4b/view?usp=drive_link
SPARQL query: https://w.wiki/AY2S
SPARQL result: https://w.wiki/AY2T

#SPARQL #semanticweb #knowledgegraphs @wikidata @dbpedia @sourisnumerique @enorouzi @shufan @fizise #scifi #mars #lecture

In a brief excursion we've introduced the #DBpedia #knowledgegraph to our students in this week's #ISE2024 lecture. This is one of the two playgrounds for our subsequent #SPARQL adventures :)

slides: https://drive.google.com/file/d/17gEglymV3_feQrkxGRw7XslxRxpGhD4b/view?usp=drive_link

#semanticweb @dbpedia @fizise @enorouzi @sourisnumerique @shufan #aiart #lecture @nfdi4culture

In a brief excursion we've introduced the #DBpedia #knowledgegraph to our students in this week's #ISE2024 lecture. This is one of the two playgrounds for our subsequent #SPARQL adventures :)

slides: https://drive.google.com/file/d/17gEglymV3_feQrkxGRw7XslxRxpGhD4b/view?usp=drive_link

#semanticweb @dbpedia @fizise @enorouzi @sourisnumerique @shufan #aiart #lecture @nfdi4culture

Yesterday after the successful PhD defense of Nicolas Heist at University of Mannheim together with Chris Bizer and Heiko Paulheim. Congratulations Dr. Nico!

Thesis title: Exploiting semi-structured information in Wikipedia for Knowledge Graph Construction
https://www.uni-mannheim.de/dws/news/nicolas-heist-defended-his-thesis/

#knowledgegraphs #wikipedia #dbpedia #informationextraction #llms @fiz_karlsruhe @fizise @KIT_Karlsruhe

Yesterday after the successful PhD defense of Nicolas Heist at University of Mannheim together with Chris Bizer and Heiko Paulheim. Congratulations Dr. Nico!

Thesis title: Exploiting semi-structured information in Wikipedia for Knowledge Graph Construction
https://www.uni-mannheim.de/dws/news/nicolas-heist-defended-his-thesis/

#knowledgegraphs #wikipedia #dbpedia #informationextraction #llms @fiz_karlsruhe @fizise @KIT_Karlsruhe

Exploratory Search and Recommendation Systems are the topics of the very last section of our #kg2023 lecture. Learn how to create a simple similarity-based recommender system for books based on SPARQL and #dbpedia. .. but we have 2 more hands-on to come ;-)
OpenHPI video: https://open.hpi.de/courses/knowledgegraphs2023/items/34xP0k99EEweSJmbUqi5lQ
youtube video: https://www.youtube.com/watch?v=CbBtM05IBWE&list=PLNXdQl4kBgzubTOfY5cbtxZCgg9UTe-uF&index=66
slides: https://zenodo.org/records/10185305
#knowledgegraphs #exploratorysearch #scifi #sparql #recommendersystems @tabea @sashabruns @MahsaVafaie @fiz_karlsruhe @fizise

Which "planetary romance" scifi novels are dealing with "Mars"? A fancy question which we will answer via federated SPARQL queries via #DBpedia and #Wikidata in this section of the free #kg2023 lecture
video lecture: https://open.hpi.de/courses/knowledgegraphs2023/items/Vz149hHvQqOCqz3rlI6xH

#Mars #scifi #sparql #knowledgegraphs #semanticweb #aiart #MOOC #OpenHPI @fiz_karlsruhe @fizise @tabea @sashabruns @enorouzi