Provide consistent unified access to data across different systems by using the flexible and semantically precise structure of the knowledge graph model
Implement a Connected Inventory of enterprise data assets, based on a knowledge graph, to get business insights about the current status and trends, risk and opportunities, based on a holistic interrelated view of all enterprise assets.
Quick and easy discovery in clinical trials, medical coding of patients’ records, advanced drug safety analytics, knowledge graph powered drug discovery, regulatory intelligence and many more
Make better sense of enterprise data and assets for competitive investment market intelligence, efficient connected inventory management, enhanced regulatory compliance and more
Connect and model industry systems and processes for deeper data-driven insights in:
Improve engagement, discoverability and personalized recommendations for Financial and Business Media, Market Intelligence and Investment Information Agencies, Science, Technology and Medicine Publishers, etc.
Ontotext’s Chief Data Architect, Vladimir Alexiev demonstrates a simple way to access Industry 4.0 standards using GraphQL through the Ontotext Platform. The latter features GraphQL interfaces to make it easier for application developers to access knowledge graphs without tedious development of back-end APIs or complex SPARQL.
The underlying Semantic Object service implements an efficient GraphQL to SPARQL translation optimized for GraphDB, as well as a generic configurable security model. The talk was presented at Semantics Online 2020.