SHACL
PulseAugur coverage of SHACL — every cluster mentioning SHACL across labs, papers, and developer communities, ranked by signal.
- used by Resource Description Framework 70%
- uses Web Ontology Language 70%
- used by Gotit.pub 70%
- used by Apache Jena 70%
- used by Rdf Owl 70%
- used by Influence Flower 70%
- used by Web Ontology Language 70%
- affiliated with Resource Description Framework 50%
- other Resource Description Framework 50%
- affiliated with Web Ontology Language 50%
- affiliated with World Wide Web Consortium 50%
1 day(s) with sentiment data
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SHACL rule stops AI agent from approving $2.3M contract
A developer integrated SHACL constraints into a Graphrag AI agent pipeline, which successfully prevented the agent from automatically approving a $2.3 million contract. This intervention highlights the importance of imp…
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Automated Knowledge Graph Tracks Evolving MLIP Models
Researchers have developed an automated process to construct and maintain a knowledge graph for the rapidly advancing field of machine learning applied to interatomic potentials (MLIP). This LLM-based system extracts in…
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New QRAKEN pipeline enhances natural language querying of knowledge graphs
Researchers have developed QRAKEN, a novel neurosymbolic pipeline designed to improve natural language querying of RDF knowledge graphs. Unlike previous methods that rely heavily on schema expectations, QRAKEN grounds i…
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OntoInk streamlines ontology documentation with integrated visualization and validation
Researchers have developed OntoInk, an open-source MkDocs plugin designed to streamline the process of ontology documentation, visualization, and validation. This tool integrates these activities into a single documenta…
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New semantic model aims to improve genetic evidence representation for AI
Researchers have developed a new semantic model designed to represent scientific evidence, particularly in genetics, to bridge the gap between basic science and clinical applications. This model aims to capture the deta…
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New infrastructure enhances trust in manufacturing knowledge graphs
Researchers have developed a composable trust infrastructure designed to enhance the reliability of manufacturing knowledge graphs. This system integrates four key capabilities: SHACL validation, PROV-O provenance, doma…
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Author criticizes slow pace of RDF and SHACL standards development
The author argues that standards work, particularly for technologies like RDF and SHACL, is often too slow due to lengthy processes involving mailing lists, issue threads, and meetings. They emphasize the need for these…
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New framework integrates RDF with Differential Dynamic Logic for AI systems
Researchers have developed RDFdL, a novel framework that combines Resource Description Framework (RDF) with Differential Dynamic Logic (dL). This integration aims to bridge the gap in representing and reasoning about bo…
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New SC2R Framework Offers Semantically Validated Interventions for At-Risk Students
This paper introduces SC2R, a framework designed to provide actionable and constraint-aware interventions for students at risk of poor academic performance. SC2R integrates a predictive model with an integer-programming…
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New SC2R framework offers semantically feasible interventions for at-risk students
Researchers have developed SC2R, a new framework designed to provide actionable and constraint-aware interventions for students identified as at risk of poor academic performance. This system combines predictive modelin…
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Global AI Regulations Compared: EU, US, China Face Compliance Gaps
A new comparative review analyzes AI regulations across the EU, US, and China, focusing on high-risk use cases and the operationalization of FAIR principles. The study highlights recurring gaps in interoperability manda…
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New method integrates OWL axioms into SHACL constraints for efficient RDF graph validation
Researchers have developed a new method to integrate OWL axioms directly into SHACL constraints, simplifying the process of validating RDF graphs that incorporate OWL ontologies. This approach constructs a translation t…
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New pipeline automates industrial device configuration using LLMs and ontologies
Researchers have developed SysName, a pipeline designed to automate the configuration of industrial fieldbus devices. This system uses a hybrid retrieval index combined with an ontology graph derived from ECLASS, AAS, a…
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LLM pipeline translates institutional policies into machine-readable knowledge graphs
Researchers have developed PolicyKG, an agentic LLM pipeline designed to convert institutional policies from natural language into machine-readable SHACL knowledge graphs. This system classifies policy sentences into ob…
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New benchmark suite evaluates LLMs for translating natural language to SHACL
Researchers have introduced NL2SHACL-Bench, a new benchmark suite designed to evaluate the translation of natural language requirements into SHACL shapes for validating RDF knowledge graphs. The benchmark was used to as…
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SHACL shape learning formalized with tight complexity bounds
Researchers have developed a fitting approach for learning SHACL shapes, which are crucial for validating data graphs in knowledge graph applications. The study focuses on a core fragment of SHACL that aligns with the D…
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New PULSE language streamlines spatiotemporal knowledge graph engineering
Researchers have developed PULSE, a new executable contract language designed for spatiotemporal knowledge graph engineering. This language aims to consolidate operational roles, observations, and constraints into a sin…
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New SciSchema.org collection standardizes scientific process descriptions
Researchers have introduced SciSchema.org, a collection of 16 schemas designed to standardize the description of scientific processes across various disciplines. These schemas, developed using a human-in-the-loop approa…
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KDAI2026 lecture covers Knowledge Graphs, Neurosymbolic AI, and AI limits
The KDAI2026 final lecture focused on Knowledge Graphs and Neurosymbolic AI, exploring topics such as OWL, SHACL, and hybrid AI approaches. The session also revisited the limitations of AI, discussing concepts like the …
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AI-generated knowledge graphs can be validated using SHACL
This article discusses methods for ensuring the quality of AI-generated knowledge graphs, particularly those using RDF triples. It highlights the challenge of scaling manual human review and proposes using SHACL (Shapes…