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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

Techniques that both enable (contribute to) and benefit from smart content are content discovery, machine learning, knowledge graphs, semantic linked data, semantic data integration, knowledge discovery, and knowledge management. Collect, curate, and catalog (i.e.,

Strategy 266
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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Ontotext

Seen through the three days of Ontotext’s Knowledge Graph Forum (KGF) this year, complexity was not only empowering but key to the growth of knowledge and innovation. Sumit started his talk by laying out the problems in today’s data landscapes. Abstract art and knowledge graphs: embracing your mess!

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Bridging the Gap Between Industries: The Power of Knowledge Graphs – Part I

Ontotext

It can apply automated reasoning to extract further knowledge and make new connections between different pieces of data. This model is used in various industries to enable seamless data integration, unification, analysis and sharing. To learn more, check out our post: An Integrated System for Global Tracking!

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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

This multiplicity of data leads to the growth silos, which in turns increases the cost of integration. The purpose of weaving a Data Fabric is to remove the friction and cost from accessing and sharing data in the distributed ICT environment that is the norm. Maximize the usability of your data.

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The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Ontotext

We rather see it as a new paradigm that is revolutionizing enterprise data integration and knowledge discovery. It is these two important types of data, which, taken together, implement the Semantic Web vision bringing forward innovative ways of tackling data management and data integration challenges.