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Gartner® How to calculate business value and cost for generative AI use cases
Explore expert insights, articles, and thought leadership on scientific data challenges.
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Explore SciBite’s full suite of solutions to unlock the potential of your data.
Explore SciBite’s full suite of solutions to unlock the potential of your data.
Discover how SciBite’s powerful solutions are supporting scientists and researchers.
Gartner® How to calculate business value and cost for generative AI use cases
Explore expert insights, articles, and thought leadership on scientific data challenges.
Discover our whitepapers, spec sheets, and webinars for in-depth product knowledge.
Explore SciBite’s full suite of solutions to unlock the potential of your data.
SciBite / Knowledge Hub / Resources / Building a new, robust domain-specific vocabulary [Use Case]
A global bioscience company wanted to standardise its use of scientific terminology. However, they found that most publicly available ontologies focused on pharmaceutical terminology and did not provide appropriate coverage relevant to their business, which is to develop solutions for the food, nutritional and agricultural industries. The manual development and review of a new vocabulary would have consumed significant internal resource.
We started with several existing ontologies, including publicly available bacterial species names, which were enriched using internal terminology commonly used within the client’s organization, including bacterial strain names and biosafety terms. We also leveraged machine learning techniques to support the enrichment process in a controlled way. For example, to suggest terms that are similar to a word of interest because they are used in a similar context, and to fill gaps not covered by a public ontology.
Find out more about how our Ontology Services can benefit your business.