Knowledge Graph brings power to data management, and it can be used to solve many engineering and manufacturing problems. Conceptually, Product Lifecycle Management (PLM) systems are very close to the knowledge graph concepts. PLM is about connecting and managing various silos of data, including information about the product's lifecycle over time.
Consequently, the knowledge graph is a promising technology capable of boosting PLM performance and business value. However, PLM systems built using old architecture cannot deliver data management and scale models for Knowledge Graph. Hence, a special network platform architecture is required.
The need for a special network platform architecture is an opportunity for building PLM systems based on the concepts of polyglot persistence and Software as a Service (SaaS) multi-tenancy. The first allows creating a semantically oriented backend capable of storing all semantic information and scale horizontally using virtual computing resources. The second brings a new network layer capable of managing data from multiple organizations and providing data across various domains.
In conclusion, the opportunity behind knowledge graphs in manufacturing is enormous. However, the systems capable of delivering data management and scale models for knowledge graphs are not available yet. SaaS PLM systems can grow into knowledge graphs using proper data management architecture and leveraging cloud scale.
Brought to you by Scope e-Knowledge Center, an SPi Global Company, a trusted global partner for Digital Content Transformation Solutions, Knowledge Modeling (Taxonomies, Thesauri and Ontologies), Abstracting & Indexing (A&I), Metadata Enrichment and Entity Extraction.
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