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Creating knowledge graphs from literature

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Organisations produce data and ingest externally generated data at a rapid pace. Holistic views of multiple data sources allow for inferences to be made that would otherwise remain unseen. In order to take holistic views of this data, it is critical that they are aligned to standards and that intuitive data structures are utilised to enable complex querying of the integrated dataset.

During this short webinar our Lead Technical Consultant Joe Mullen will explain how SciBite’s semantic enrichment technology is being used to facilitate the production of Knowledge Graphs.

We will explain how the SciBite stack can be used for the extraction of semantic triples from literature as well as the harmonisation and integration of these with data from both external and internal structured data sources.

Related articles

  1. What is a Semantic Knowledge Graph?

    At a time where more and more of our customer projects revolve around knowledge graph creation, we thought it was about time we blogged on what exactly a knowledge graph is and explain a bit more about how our semantic enrichment technology is being used to facilitate the production of such a powerful data model.

  2. The Relationship Game – Knowledge Graphs

    Scientific knowledge can be represented as relationships between things. Thousands or millions of such relationships make a knowledge graph or network analysis. SciBite technology enables extraction of these relationships, and in doing so, can uncover knowledge that might otherwise have remained hidden


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