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How to define constraints on rdf:Lists using SHACL

RDF lists are a rather weak spot of the semantic technology stack. Their design is basically a linked structure of intermediate list nodes using dedicated properties rdf:rest and rdf:first. So a simple list of string literals “red”, “yellow” and “green” … Read More »

How to use TopBraid as a data validation server

RDF data validation is the process of checking a (data) graph against constraints from a schema definition. In the Shapes Constraint Language (SHACL), constraints are themselves expressed in a RDF syntax, in so-called shapes graphs. SHACL-based validation engines can (among … Read More »

An Overview of SHACL Features and Specifications

After two and half years of collaboration and discussions, the W3C Data Shapes Working Group has produced a collection of specifications that define the features of the Shapes Constraint Language (SHACL): SHACL (Official W3C Standard Recommendation) is the main document, … Read More »

Technology and Your GDPR journey

Since you’ve reached this page, GDPR (General Data Protection Regulation) must mean something to you or you need to find out if it does! In this blog, we will quickly review GDPR and its importance and then focus on the … Read More »

Insights from Enterprise Data World

It was another year of productive exchange of experience, insights and ideas at EDW 2017! As it grown in importance for most enterprises, data governance has become a key focus and high-priority of the conference program. So, not surprisingly, we … Read More »

Using SHACL Data Constraints in the TopBraid Web Products EVN and EDG

(original posted on September 6, 2016) What is SHACL? The RDF Shapes Constraint Language (SHACL) is a new W3C standard for specifying rich data constraints as part of semantic data models. It can be used with RDFS/OWL ontologies or, alternatively, an … Read More »

Using the TopBraid EDG Platform to Support Semantic Search

Many organizations come to us looking for a search capability to better enable their business and eliminate the data stovepipe syndrome (think isolated, disparate and yet related data). One customer example is a large, public financial institution that we are … Read More »

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