Data representations based on complex point-to-point representations that can enable decision0making and drive AI components came to be known as Knowledge Graphs – though technologists and information science experts have had slightly varying definitions. According to the nomenclature and the technology taxonomy, knowledge graphs fall under the category of semantics or semantic web or intelligent app development.
These Knowledge Graphs are made up of semantic middleware layers and database components on top, which essentially resides as part of the middleware. The systems must be stable and futuristic – running on powerful algorithms that can not only enable smart decisions, but can act as the foundation for capabilities around which powerful AI frameworks that are also scalable with future requirements. In essence, they should be extendable yet manageable.
NYGCI (Knowledge Graph as a Service provider) partners with clients in terms of technology as well as resources to build functional and consistent models of knowledge graphs. Our multi-industry semantics suite has helped firms to achieve reusability of data and web-based semantics and resulting graphs by going around their enterprise-level needs. This will enhance re-use if industry data for maximum efficiency and throughput based on well-built ontologies and underlying frameworks.
