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.
In this blog post on the Linked Data Benchmark Council website, the Semantic Publishing Benchmark is utilized to determine the most efficient AWS instances for meta-data based content publishing as measured by the number of queries and updates executed per $1 paid to Amazon. Using GraphDB™ Standard 6.1, the team tested five different server types with varying vCPU configurations. View the results and the full blog post on LDBCouncil.org.
For more information, contact Doug Kimball, Chief Marketing Officer at Ontotext