Back in the lecture hall again after two exciting weeks of #ESWC2025 and #ISWS2025. This morning, we introduced our students to RDF, RDFS, RDF Inferencing, and RDF Reification.
#ise2025 #semanticweb #semweb #knowledgegraphs #rdf #reasoning #reification #lecture @fiz_karlsruhe @fizise @KIT_Karlsruhe @sourisnumerique @tabea @enorouzi
I just released version 0.1.0 of #Trinja, the #RDF-based static site generator and RDFS-to-HTML-renderer:
https://codeberg.org/Taganak/trinja
It can build working static websites from #LinkedData on a graph (in a somewhat limited fashion for the moment).
The README shows what it is supposed to do. I promise it will become more usefull in the medium run ;).
#TIL Netflix is actually using #RDF for their Unified Data Architecture
https://netflixtechblog.com/uda-unified-data-architecture-6a6aee261d8d
However, there is another way:
publishing a SPARQL endpoint for RDF data that conforms to commonly used ontologies and which is self documenting using VoID.
Here's a list of very common ontologies, so much so they are part of the RDFa Core Initial Context: https://www.w3.org/2011/rdfa-context/rdfa-1.1
And here's a description of how to use VoID: https://www.w3.org/TR/void/
Bonus— @bobdc 's post on exploring unknown sparql endpoints: https://www.bobdc.com/blog/exploring-a-sparql-endpoint/
Hey do you know things about RDF and/or have references to work on building machine-usable ontologies? Cause I'd like to talk to you! (And if you don't could you give a boost?)
I'm looking into it because for media-thing I'm wanting to identify ways to give people meta-descriptive power over their media metadata.
#rdf #ontology #ontologies #mediathing
The #PRISMS Digital Scholarly Editions platform is built with open standards, ensuring citable and enduring editions.
#PRISMS embeds your edition in a network of primary sources and scholarship, and includes tools for annotation and analysis:
As Heiko Paulheim is referring in his tutorial at ISWS 2025, his presentation on RDF2vec is not an individual contribution, but an effort of a great team of PhDs, PostDocs & students from his research group at University of Mannheim.
#isws2025 #summerschool #tutorial #rdf2vec #rdf #knowledgegraphs #ML #AI #summerschool
Double award! 🏆 🏆 Best Poster and the Dieter Fensel Visionary Award at European Semantic Web Conference went to the work "Representing and querying data tensors in #RDF and #SPARQL", done by Piotr Marciniak, our CTO Piotr Sowiński, and Maria Ganzha.
We are deeply thankful for this distinction! The work is absolutely key to #neurosymbolic systems we are building.
Poster: https://ostrzyciel.eu/assets/pdf/poster_tensor_rdf_eswc_2025.pdf
Paper: http://arxiv.org/pdf/2504.19224
Website, code, datasets, and more: https://w3id.org/rdf-tensor
Cognee is an open-source AI memory engine and is the only knowledge graph generator (I am aware of) using actual RDF ontologies to structure knowledge.
While working on a graph partitioning strategy, I stumbled upon an interesting paper
https://jbiomedsem.biomedcentral.com/articles/10.1186/s13326-024-00310-5
So, let me ask, what successful strategies for multi-level partitioning with #RDF named graphs have you applied or know about?
(beyond this paper and what it cites)
I might be overdoing this whole #RDF and #LinkedData thing, but… here's the first steps with #Trinja, a RDF-to-HTML mapper and #SSG:
https://codeberg.org/Taganak/trinja/src/branch/main/example.ttl
The idea is: Use *any* resource described as RDF (e.g. from #Wikidata or an #ActivityPub action), link a #Jinja template to it or its rdf:type in your own set of statements, and there you got your visualisation!
Based on #TaganakNet, the #Rust #RDF development kit by @codecraft and me. We are collecting real-world examples at a good rate!
It turns out that using RDF's built-in mechanism for defining #RDF ontologies may be too limiting. Case in point: defining properties that are applicable in many different contexts is impossible using rdfs:domain and rdfs:range.
For instance, defining an ex:child property that applies both to human relations and to graphs is impossible with those. That's why the schema.org ontology defines schema:domainIncludes, and also schema:rangeIncludes.
Notre prochaine intervention à #LibreABC le 9 septembre prochain s'intitule "Comment gérer ses fonds d’archives sous forme de données liées au moyen de la plateforme libre ResearchSpace"
Cela sera l'occasion de promouvoir l'utilisation de #RDF natif pour gérer des collections et de plaider pour une mutualisation des coûts de développement dans ce domaine.
just spend 30 minutes trying to find the bug in my #knowledgegraph script generator. It was a space in the prefix. This website is gonna be my official #rdf #sparql monday #rant space, because it's monday and all my colleagues are in home office on monday, so i can't emotionally unload on them. I just need to write this and send it out there because the frustration is getting intense.
#KingCharles to stop controversial Portland #Incinerator https://www.dorsetecho.co.uk/news/25194849.portland-town-council-ask-king-charles-stop-incinerator/
🤔 Is this a little misleading?
#RDF
#BIBFRAME without BIBFRAME: The infrastructure of next-generation #cataloging workflows
https://www.tandfonline.com/doi/full/10.1080/07317131.2025.2512281#d1e172
#libraries #catalogs #LOD #linkeddata #Marc21 #MARC #metadata #RDF #standards
I have been thinking about how to combine RDF models when one of them is too large to load in to memory.
The answer will involve copying a connected subgraph into a temporary model, a "view" if you will. This will be centred on a start node and then use some specified number of breadth first search steps.
The problem is that if you hit a node with a large number of links, such as a class type, the process will crash just getting a count of the links (if that were possible).
I think the answer involves setting a boundary fence. A set of nodes, or tests that if reached will prevent the search from including that node in subsequent steps.
Some thoughts:
https://ocratato-sassy.sourceforge.io/pdf/views.pdf
The June 2025 release of the Between Our Worlds dataset with anime metadata is available now! https://betweenourworlds.org
#linkeddata #rdf #opendata #anime #metadata
Scrolling past the Royal Flying Doctor Service website for the 100th time as I Google for the RDF Schema documentation
@thibaultmol @nemobis the #WDQS database was recently split but this is not a sustainable solution because the two parts will eventually grow bigger. I’m not actually sure if the split is at least working as intended.
https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/WDQS_graph_split
