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Creating knowledge graphs from literature [Webinar]

Organizations 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 utilized 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.

Joe Mullen
Director of Data Science & Professional Services, SciBite

Leading SciBite’s data science and professional services team, Joe is dedicated to helping customers unlock the full potential of their data using SciBite’s semantic stack. Spearheading R&D initiatives within the team and pushing the boundaries of the possible. Joe’s expertise is rooted in a PhD from Newcastle University, focussing on novel computational approaches to drug repositioning; building atop semantic data integration, knowledge graph & data mining.

Since joining SciBite in 2017, Joe has been enthused by the rapid advancements in technology, particularly within AI. Recognizing the immense potential of AI, Joe combines this cutting-edge technology with SciBite’s core technologies to craft tailored, bespoke solutions that cater to diverse customer needs.

Other articles by Joe

  1. Are ontologies still relevant in the age of LLMs? read more
  2. What is Retrieval Augmented Generation, and why is the data you feed it so important? read more
  3. Large language models (LLMs) and search; it’s a FAIR game, read more
  4. Revolutionizing Life Sciences: The incredible impact of AI in Life Science [Part 1], read more
  5. Why use your ontology management platform as a central ontology server? read more
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