Like in real-life, computers interact in complex interconnected ecosystems, where each element of the system can constrain the behavior of many others. Data is fast, changes often and is in motion. Data and application behavior and enhancements are often tightly coupled, consequently it’s hard to change either independently.
Semantic technologies attempt to solve this by decoupling applications from data by use of an abstract model for knowledge representation, releasing the mutual constraints on applications and the data consumed, allowing the developer to focus on the behavior of the application rather than on data processing.
Representing the expression and meaning of unstructured data is hard. Both NOSQL or SQL databases have opaque or rigid schema limitations. Enhancing existing tables or combining data across collections is difficult, and more often than not data is only useful once processed and manipulated by code in the application itself.
In this meetup, you will learn…
– The mechanics of a microservice  that consumes semantic data deployed on RedHat Kubernetes OpenShift
– How Semantic data allows users to combine data in new ways and allows users to make connections and relationships that were previously hidden – like plotting crime statistics on a map or finding nearby restaurants within walking distance of a movie you want watch.
– How to combine and query semantic data with SPARQL or Prolog to extract useful facts. For example, `list all dinosaurs that eat plants.
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