#shacl — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #shacl, aggregated by home.social.
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Standards work is slow: mailing lists, issue threads, meetings where one property name takes three sessions. My latest post explains why I still spend so much time on it.
I want RDF to cover the range of use cases people actually show up with. Not just the range it handles well today. A W3C discussion about SHACL UI on a smartwatch showed how easily we scope those cases out by reflex.
Read more: https://www.bergnet.org/2026/08/why-rdf-standards/
#RDF #SHACL #W3C #AI -
Standards work is slow: mailing lists, issue threads, meetings where one property name takes three sessions. My latest post explains why I still spend so much time on it.
I want RDF to cover the range of use cases people actually show up with. Not just the range it handles well today. A W3C discussion about SHACL UI on a smartwatch showed how easily we scope those cases out by reflex.
Read more: https://www.bergnet.org/2026/08/why-rdf-standards/
#RDF #SHACL #W3C #AI -
Standards work is slow: mailing lists, issue threads, meetings where one property name takes three sessions. My latest post explains why I still spend so much time on it.
I want RDF to cover the range of use cases people actually show up with. Not just the range it handles well today. A W3C discussion about SHACL UI on a smartwatch showed how easily we scope those cases out by reflex.
Read more: https://www.bergnet.org/2026/08/why-rdf-standards/
#RDF #SHACL #W3C #AI -
Standards work is slow: mailing lists, issue threads, meetings where one property name takes three sessions. My latest post explains why I still spend so much time on it.
I want RDF to cover the range of use cases people actually show up with. Not just the range it handles well today. A W3C discussion about SHACL UI on a smartwatch showed how easily we scope those cases out by reflex.
Read more: https://www.bergnet.org/2026/08/why-rdf-standards/
#RDF #SHACL #W3C #AI -
Standards work is slow: mailing lists, issue threads, meetings where one property name takes three sessions. My latest post explains why I still spend so much time on it.
I want RDF to cover the range of use cases people actually show up with. Not just the range it handles well today. A W3C discussion about SHACL UI on a smartwatch showed how easily we scope those cases out by reflex.
Read more: https://www.bergnet.org/2026/08/why-rdf-standards/
#RDF #SHACL #W3C #AI -
🤠 #KDAI2026 final lecture on #KnowledgeGraphs 04 & #NeurosymbolicAI
The final graph session, then the leap to hybrid AI:
▸ OWL — complex classes & property restrictions
▸ SHACL Shapes
▸ Neurosymbolic AI with KG embeddings, RAG,
▸ AI limits revisited (ELIZA, Clever Hans, Chinese Room, Turing Test, the paperclip maximiser & the singularity).Neither symbols nor learning alone get us there. 📡 SEE YOU SPACE COWBOY…
#SemanticWeb #OWL #SHACL #RAG #Ontologies #LLM @fiz_karlsruhe @KIT_Karlsruhe #AI
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🤠 #KDAI2026 final lecture on #KnowledgeGraphs 04 & #NeurosymbolicAI
The final graph session, then the leap to hybrid AI:
▸ OWL — complex classes & property restrictions
▸ SHACL Shapes
▸ Neurosymbolic AI with KG embeddings, RAG,
▸ AI limits revisited (ELIZA, Clever Hans, Chinese Room, Turing Test, the paperclip maximiser & the singularity).Neither symbols nor learning alone get us there. 📡 SEE YOU SPACE COWBOY…
#SemanticWeb #OWL #SHACL #RAG #Ontologies #LLM @fiz_karlsruhe @KIT_Karlsruhe #AI
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🤠 #KDAI2026 final lecture on #KnowledgeGraphs 04 & #NeurosymbolicAI
The final graph session, then the leap to hybrid AI:
▸ OWL — complex classes & property restrictions
▸ SHACL Shapes
▸ Neurosymbolic AI with KG embeddings, RAG,
▸ AI limits revisited (ELIZA, Clever Hans, Chinese Room, Turing Test, the paperclip maximiser & the singularity).Neither symbols nor learning alone get us there. 📡 SEE YOU SPACE COWBOY…
#SemanticWeb #OWL #SHACL #RAG #Ontologies #LLM @fiz_karlsruhe @KIT_Karlsruhe #AI
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🤠 #KDAI2026 final lecture on #KnowledgeGraphs 04 & #NeurosymbolicAI
The final graph session, then the leap to hybrid AI:
▸ OWL — complex classes & property restrictions
▸ SHACL Shapes
▸ Neurosymbolic AI with KG embeddings, RAG,
▸ AI limits revisited (ELIZA, Clever Hans, Chinese Room, Turing Test, the paperclip maximiser & the singularity).Neither symbols nor learning alone get us there. 📡 SEE YOU SPACE COWBOY…
#SemanticWeb #OWL #SHACL #RAG #Ontologies #LLM @fiz_karlsruhe @KIT_Karlsruhe #AI
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🤠 #KDAI2026 final lecture on #KnowledgeGraphs 04 & #NeurosymbolicAI
The final graph session, then the leap to hybrid AI:
▸ OWL — complex classes & property restrictions
▸ SHACL Shapes
▸ Neurosymbolic AI with KG embeddings, RAG,
▸ AI limits revisited (ELIZA, Clever Hans, Chinese Room, Turing Test, the paperclip maximiser & the singularity).Neither symbols nor learning alone get us there. 📡 SEE YOU SPACE COWBOY…
#SemanticWeb #OWL #SHACL #RAG #Ontologies #LLM @fiz_karlsruhe @KIT_Karlsruhe #AI
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The new #KDAI2026 lecture is out. How to get from a sentence to something a machine can actually reason?
The greenhouse effect was discovered by Fourier, explained by Eunice Newton Foote. 3 words, 1 triple: subject, predicate, object. Stack enough of them and you get a graph. Add an ontology and the machine starts to infer.
This session:
▸ Graphs & triples
▸ #KnowledgeGraphs & #ontologies
▸ #SemanticWeb & #LinkedData
▸ #RDF, RDFS, #SPARQL, #OWL, #SHACL
CU space cowboy… -
The new #KDAI2026 lecture is out. How to get from a sentence to something a machine can actually reason?
The greenhouse effect was discovered by Fourier, explained by Eunice Newton Foote. 3 words, 1 triple: subject, predicate, object. Stack enough of them and you get a graph. Add an ontology and the machine starts to infer.
This session:
▸ Graphs & triples
▸ #KnowledgeGraphs & #ontologies
▸ #SemanticWeb & #LinkedData
▸ #RDF, RDFS, #SPARQL, #OWL, #SHACL
CU space cowboy… -
The new #KDAI2026 lecture is out. How to get from a sentence to something a machine can actually reason?
The greenhouse effect was discovered by Fourier, explained by Eunice Newton Foote. 3 words, 1 triple: subject, predicate, object. Stack enough of them and you get a graph. Add an ontology and the machine starts to infer.
This session:
▸ Graphs & triples
▸ #KnowledgeGraphs & #ontologies
▸ #SemanticWeb & #LinkedData
▸ #RDF, RDFS, #SPARQL, #OWL, #SHACL
CU space cowboy… -
The new #KDAI2026 lecture is out. How to get from a sentence to something a machine can actually reason?
The greenhouse effect was discovered by Fourier, explained by Eunice Newton Foote. 3 words, 1 triple: subject, predicate, object. Stack enough of them and you get a graph. Add an ontology and the machine starts to infer.
This session:
▸ Graphs & triples
▸ #KnowledgeGraphs & #ontologies
▸ #SemanticWeb & #LinkedData
▸ #RDF, RDFS, #SPARQL, #OWL, #SHACL
CU space cowboy… -
The new #KDAI2026 lecture is out. How to get from a sentence to something a machine can actually reason?
The greenhouse effect was discovered by Fourier, explained by Eunice Newton Foote. 3 words, 1 triple: subject, predicate, object. Stack enough of them and you get a graph. Add an ontology and the machine starts to infer.
This session:
▸ Graphs & triples
▸ #KnowledgeGraphs & #ontologies
▸ #SemanticWeb & #LinkedData
▸ #RDF, RDFS, #SPARQL, #OWL, #SHACL
CU space cowboy… -
Yesterday I pushed a major update to the experimental #SHACL 1.2 branch of shacl-engine.
It now supports most SHACL 1.2 Core, Node Expression, and SPARQL features. The implementation is still incomplete — reification, some constraint components, and several node expression functions are still missing — but those are coming soon.
You can already try it directly in the browser:
https://playground.rdf-ext.org/shacl-experimental/GitHub repo:
https://github.com/rdf-ext/shacl-engine/tree/experimental -
Yesterday I pushed a major update to the experimental #SHACL 1.2 branch of shacl-engine.
It now supports most SHACL 1.2 Core, Node Expression, and SPARQL features. The implementation is still incomplete — reification, some constraint components, and several node expression functions are still missing — but those are coming soon.
You can already try it directly in the browser:
https://playground.rdf-ext.org/shacl-experimental/GitHub repo:
https://github.com/rdf-ext/shacl-engine/tree/experimental -
Yesterday I pushed a major update to the experimental #SHACL 1.2 branch of shacl-engine.
It now supports most SHACL 1.2 Core, Node Expression, and SPARQL features. The implementation is still incomplete — reification, some constraint components, and several node expression functions are still missing — but those are coming soon.
You can already try it directly in the browser:
https://playground.rdf-ext.org/shacl-experimental/GitHub repo:
https://github.com/rdf-ext/shacl-engine/tree/experimental -
Yesterday I pushed a major update to the experimental #SHACL 1.2 branch of shacl-engine.
It now supports most SHACL 1.2 Core, Node Expression, and SPARQL features. The implementation is still incomplete — reification, some constraint components, and several node expression functions are still missing — but those are coming soon.
You can already try it directly in the browser:
https://playground.rdf-ext.org/shacl-experimental/GitHub repo:
https://github.com/rdf-ext/shacl-engine/tree/experimental -
Yesterday I pushed a major update to the experimental #SHACL 1.2 branch of shacl-engine.
It now supports most SHACL 1.2 Core, Node Expression, and SPARQL features. The implementation is still incomplete — reification, some constraint components, and several node expression functions are still missing — but those are coming soon.
You can already try it directly in the browser:
https://playground.rdf-ext.org/shacl-experimental/GitHub repo:
https://github.com/rdf-ext/shacl-engine/tree/experimental -
SemPER (https://sparna-git.github.io/semper/), un bel exemple de sémantisation et de déploiement d'un graphe de connaissances en Records-in-Contexts : modélisation du graphe en #SHACL, conversion des données en #rdf assignation d'identifiants #URI, chargement dans une base #SPARQL, interrogation avec #sparnatural
C'est l'échelle du projet qui est intéressante : c'est un fonds d'archives départementales, limité en taille, mais présentant un fort intérêt d'interopérabilité et de recherche.
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SemPER (https://sparna-git.github.io/semper/), un bel exemple de sémantisation et de déploiement d'un graphe de connaissances en Records-in-Contexts : modélisation du graphe en #SHACL, conversion des données en #rdf assignation d'identifiants #URI, chargement dans une base #SPARQL, interrogation avec #sparnatural
C'est l'échelle du projet qui est intéressante : c'est un fonds d'archives départementales, limité en taille, mais présentant un fort intérêt d'interopérabilité et de recherche.
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Good morning Dubrovnik! ESWC 2026 - the 23rd European Semantic Web Conference is starting today. Looking forward to visionary and inspiring keynotes, presentations, and posters, esp. addressing the question on how #SemanticWeb technologies will survive (or even prevail...) the current 3rd wave of #AI
https://2026.eswc-conferences.org/
#SemanticWeb #knowledgegraphs #ontologies #shacl #AI #llms #generativeAI #reliableAI #explainableAI #ESWC2026 #dubrovnik
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Good morning Dubrovnik! ESWC 2026 - the 23rd European Semantic Web Conference is starting today. Looking forward to visionary and inspiring keynotes, presentations, and posters, esp. addressing the question on how #SemanticWeb technologies will survive (or even prevail...) the current 3rd wave of #AI
https://2026.eswc-conferences.org/
#SemanticWeb #knowledgegraphs #ontologies #shacl #AI #llms #generativeAI #reliableAI #explainableAI #ESWC2026 #dubrovnik
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Good morning Dubrovnik! ESWC 2026 - the 23rd European Semantic Web Conference is starting today. Looking forward to visionary and inspiring keynotes, presentations, and posters, esp. addressing the question on how #SemanticWeb technologies will survive (or even prevail...) the current 3rd wave of #AI
https://2026.eswc-conferences.org/
#SemanticWeb #knowledgegraphs #ontologies #shacl #AI #llms #generativeAI #reliableAI #explainableAI #ESWC2026 #dubrovnik
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Good morning Dubrovnik! ESWC 2026 - the 23rd European Semantic Web Conference is starting today. Looking forward to visionary and inspiring keynotes, presentations, and posters, esp. addressing the question on how #SemanticWeb technologies will survive (or even prevail...) the current 3rd wave of #AI
https://2026.eswc-conferences.org/
#SemanticWeb #knowledgegraphs #ontologies #shacl #AI #llms #generativeAI #reliableAI #explainableAI #ESWC2026 #dubrovnik
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Good morning Dubrovnik! ESWC 2026 - the 23rd European Semantic Web Conference is starting today. Looking forward to visionary and inspiring keynotes, presentations, and posters, esp. addressing the question on how #SemanticWeb technologies will survive (or even prevail...) the current 3rd wave of #AI
https://2026.eswc-conferences.org/
#SemanticWeb #knowledgegraphs #ontologies #shacl #AI #llms #generativeAI #reliableAI #explainableAI #ESWC2026 #dubrovnik
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As interest in knowledge graphs grows by the day, @veronahe is busier than ever with her efforts to connect the #dataEngineering, #informationArchitecture, and #ontology practices that drive modern knowledge engineering.
Best known as an advanced #knowledgeGraph practitioner and a leading expert on the #SHACL standard, Veronika also regularly shares her knowledge by teaching and appearing on podcasts like this one.
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As interest in knowledge graphs grows by the day, @veronahe is busier than ever with her efforts to connect the #dataEngineering, #informationArchitecture, and #ontology practices that drive modern knowledge engineering.
Best known as an advanced #knowledgeGraph practitioner and a leading expert on the #SHACL standard, Veronika also regularly shares her knowledge by teaching and appearing on podcasts like this one.
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As interest in knowledge graphs grows by the day, @veronahe is busier than ever with her efforts to connect the #dataEngineering, #informationArchitecture, and #ontology practices that drive modern knowledge engineering.
Best known as an advanced #knowledgeGraph practitioner and a leading expert on the #SHACL standard, Veronika also regularly shares her knowledge by teaching and appearing on podcasts like this one.
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Nouvelle version de l'outil de documentation pour la structure des graphes de connaissances en #SHACL : https://shacl-play.sparna.fr/play/doc - basé sur ReSpec. Une doc encore plus propre et plein d'améliorations, meilleure table des matières, meilleure accessibilité, table de propriétés plus lisible, encadrés plus lisible, métadonnées du doc plus propres, etc.
En copie d'écran un exemple sur un des modèles du portail open data du Parlement Européen (https://data.europarl.europa.eu/fr/developer-corner)
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Nouvelle version de l'outil de documentation pour la structure des graphes de connaissances en #SHACL : https://shacl-play.sparna.fr/play/doc - basé sur ReSpec. Une doc encore plus propre et plein d'améliorations, meilleure table des matières, meilleure accessibilité, table de propriétés plus lisible, encadrés plus lisible, métadonnées du doc plus propres, etc.
En copie d'écran un exemple sur un des modèles du portail open data du Parlement Européen (https://data.europarl.europa.eu/fr/developer-corner)
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This is Koblenz Hbf, the main train station in #Koblenz, #Germany. I am waiting for the train to Stuttgart. This is the third time @Ayenkantun and I visited Koblenz. This time we traveled to attend Philipp Seifer's PhD defense. I co-author several papers with him about #SPARQL #KnowledgeGraphs #SHACL #SemanticWeb He did a great defense! I am very happy!
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This is Koblenz Hbf, the main train station in #Koblenz, #Germany. I am waiting for the train to Stuttgart. This is the third time @Ayenkantun and I visited Koblenz. This time we traveled to attend Philipp Seifer's PhD defense. I co-author several papers with him about #SPARQL #KnowledgeGraphs #SHACL #SemanticWeb He did a great defense! I am very happy!
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This is Koblenz Hbf, the main train station in #Koblenz, #Germany. I am waiting for the train to Stuttgart. This is the third time @Ayenkantun and I visited Koblenz. This time we traveled to attend Philipp Seifer's PhD defense. I co-author several papers with him about #SPARQL #KnowledgeGraphs #SHACL #SemanticWeb He did a great defense! I am very happy!
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This is Koblenz Hbf, the main train station in #Koblenz, #Germany. I am waiting for the train to Stuttgart. This is the third time @Ayenkantun and I visited Koblenz. This time we traveled to attend Philipp Seifer's PhD defense. I co-author several papers with him about #SPARQL #KnowledgeGraphs #SHACL #SemanticWeb He did a great defense! I am very happy!
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This is Koblenz Hbf, the main train station in #Koblenz, #Germany. I am waiting for the train to Stuttgart. This is the third time @Ayenkantun and I visited Koblenz. This time we traveled to attend Philipp Seifer's PhD defense. I co-author several papers with him about #SPARQL #KnowledgeGraphs #SHACL #SemanticWeb He did a great defense! I am very happy!
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Most data comes from closed-world systems — forms, sensors, logs — with known schemas. Yet the RDF community often says: adopt the full semantic web stack or nothing.
My latest post explores practical RDF for closed-world systems:
- When closed-world makes sense
- Real examples: sensors, IoT, forms
- How Netflix uses RDF+SHACL at scale
- New SHACL 1.2 features
Read more: https://www.bergnet.org/2026/03/closed-world-systems/
#RDF #SHACL #JSON-LD #Ontop -
Most data comes from closed-world systems — forms, sensors, logs — with known schemas. Yet the RDF community often says: adopt the full semantic web stack or nothing.
My latest post explores practical RDF for closed-world systems:
- When closed-world makes sense
- Real examples: sensors, IoT, forms
- How Netflix uses RDF+SHACL at scale
- New SHACL 1.2 features
Read more: https://www.bergnet.org/2026/03/closed-world-systems/
#RDF #SHACL #JSON-LD #Ontop -
Most data comes from closed-world systems — forms, sensors, logs — with known schemas. Yet the RDF community often says: adopt the full semantic web stack or nothing.
My latest post explores practical RDF for closed-world systems:
- When closed-world makes sense
- Real examples: sensors, IoT, forms
- How Netflix uses RDF+SHACL at scale
- New SHACL 1.2 features
Read more: https://www.bergnet.org/2026/03/closed-world-systems/
#RDF #SHACL #JSON-LD #Ontop -
Most data comes from closed-world systems — forms, sensors, logs — with known schemas. Yet the RDF community often says: adopt the full semantic web stack or nothing.
My latest post explores practical RDF for closed-world systems:
- When closed-world makes sense
- Real examples: sensors, IoT, forms
- How Netflix uses RDF+SHACL at scale
- New SHACL 1.2 features
Read more: https://www.bergnet.org/2026/03/closed-world-systems/
#RDF #SHACL #JSON-LD #Ontop -
Most data comes from closed-world systems — forms, sensors, logs — with known schemas. Yet the RDF community often says: adopt the full semantic web stack or nothing.
My latest post explores practical RDF for closed-world systems:
- When closed-world makes sense
- Real examples: sensors, IoT, forms
- How Netflix uses RDF+SHACL at scale
- New SHACL 1.2 features
Read more: https://www.bergnet.org/2026/03/closed-world-systems/
#RDF #SHACL #JSON-LD #Ontop -
We are very pleased to announce the publication of our complet #RDF Data Model as Shapes (#SHACL)
https://shapes.performing-arts.ch/
Special Thanks to @sparna who guides us in this work
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We are very pleased to announce the publication of our complet #RDF Data Model as Shapes (#SHACL)
https://shapes.performing-arts.ch/
Special Thanks to @sparna who guides us in this work
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We are very pleased to announce the publication of our complet #RDF Data Model as Shapes (#SHACL)
https://shapes.performing-arts.ch/
Special Thanks to @sparna who guides us in this work
-
We are very pleased to announce the publication of our complet #RDF Data Model as Shapes (#SHACL)
https://shapes.performing-arts.ch/
Special Thanks to @sparna who guides us in this work
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We are very pleased to announce the publication of our complet #RDF Data Model as Shapes (#SHACL)
https://shapes.performing-arts.ch/
Special Thanks to @sparna who guides us in this work
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There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility
-
There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility
-
There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility
-
There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility
-
There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility
-
There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility. 👇📜
-
There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility. 👇📜
-
There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility. 👇📜
-
There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility. 👇📜
-
There are many benefits when the inference rules are included in the knowledge graph. One benefit is the decoupling of data and application. It lowers the cost of integration and the cost of change. Another is the improved data governance.
A third one is the gain in flexibility. 👇📜
-
📜 New essay on Link&Think
Rules are usually in the application layer.
With #SHACL rules, they can be part of the graph, and then, apart from simplicity and speed, they can bring other benefits coming from data-application decoupling.Part 1 is now available.
https://www.linkandth.ink/p/rules-on-graphs-in-graphs-of-rules
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📜 New essay on Link&Think
Rules are usually in the application layer.
With #SHACL rules, they can be part of the graph, and then, apart from simplicity and speed, they can bring other benefits coming from data-application decoupling.Part 1 is now available.
https://www.linkandth.ink/p/rules-on-graphs-in-graphs-of-rules
-
📜 New essay on Link&Think
Rules are usually in the application layer.
With #SHACL rules, they can be part of the graph, and then, apart from simplicity and speed, they can bring other benefits coming from data-application decoupling.Part 1 is now available.
https://www.linkandth.ink/p/rules-on-graphs-in-graphs-of-rules