Knowledge Hub
Data Fabric is the new addition to the growing alphabet soup of new IT vocabulary terms. DIve into the what, why, when and how of data fabric
LLMs are deep learning models that learn patterns and relationships from large volumes of textual data. They can be used for generating new text, based on inputs, by predicting the most probable sequence of words to follow
Diving into SHACL – what it is, what a SHACL shape looks like and what kinds of data quality constraints you can specify with it
Data mesh is still in its infancy and it’s important to be aware of the Why and What of data mesh and the role that knowledge graphs should play
RDF-star (also known as RDF*) allows descriptions to be added to edges in a graph such as scores, weights, temporal aspects and provenance to edges in a graph.
Dive in this SlideShare presentation discussing the RDF and Property Graphs models in informative detail and comparing their features.
A how-to guide describing SPARQL editing and data visualization features available in GraphDB Workbench or other features that can be added with little programming.
How to build knowledge graphs for better enterprise knowledge management, data and content analytics? Here is a short list showing the 10 steps of creating knowledge graphs based on Ontotext’s extensive experience.
Knowledge graphs represent a collection of interlinked descriptions of entities that put data in context via linking and semantic metadata and this way provide a framework for data integration, unification, analytics and sharing.