An exploration of SHACL 1.2 UI and its potential for creating forms and views, drawing parallels to the earlier XForms technology. The article discusses the benefits of declarative UI generation, dynamic properties, and security features.
The article explores SHACL 1.2 UI as a powerful, declarative approach to building forms and views for RDF data, drawing parallels to the earlier (and ultimately unsuccessful) XForms standard. The author argues that SHACL 1.2 UI offers benefits like consistent data presentation, automated form generation, dynamic property computation, and enhanced security, potentially revolutionizing how we interact with data on the web. While current tooling is limited, existing DASH-compatible tools can be adapted, and the author envisions a future where data itself dictates its presentation, reducing the need for costly and inconsistent manual form creation.
The article explores SHACL 1.2 UI as a powerful, declarative approach to building forms and views for RDF data, drawing parallels to the earlier (and ultimately unsuccessful) XForms standard. The author argues that SHACL 1.2 UI offers benefits like consistent data presentation, automated form generation, dynamic property computation, and enhanced security, potentially revolutionizing how we interact with data on the web. While current tooling is limited, existing DASH-compatible tools can be adapted, and the author envisions a future where data itself dictates its presentation, reducing the need for costly and inconsistent manual form creation.
An exploration of the role of an ontologist, covering skills, tasks, differences from taxonomists, training resources, and the future of the field.
This article details a step-by-step guide on building a knowledge graph from plain text using an LLM-powered pipeline. It covers concepts like Subject-Predicate-Object triples, text chunking, and LLM prompting to extract structured information.
The article explores how Retrieval-Augmented Generation (RAG) and knowledge graphs can be used together to break down data silos and enable more accurate, context-aware, and insightful AI systems.
python ./ontology_viz.py -o test.dot test.ttl -O ontology.ttl
