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Transform the scientific search experience using customised ontologies [SciBite + Sinequa webinar]

Search + business intelligence

Unstructured scientific textual information presents a unique challenge for search and analytics platforms. Scientific terminology is often unstandardized, making keyword searching ineffective for finding insights from internal and external scientific documents. In contrast, robust ontologies and controlled vocabularies can help with the inherent synonymy and ambiguity in scientific text and substantially improve the scientific search experience.

In this webinar, we will demonstrate the unique value gained by pairing SciBite’s expertise in creating, managing, and disseminating biopharmaceutical ontologies with Sinequa’s advanced cognitive search capabilities. Using the rapidly evolving domain of COVID-19 symptoms and therapeutics as an example, we will demonstrate an end-to-end workflow for curating new terminology and rapidly deploying updates to Sinequa to maintain an up-to-date search platform.

You will learn about:

  • The collaborative ontology management capabilities of SciBite’s ontology management platform CENtree
  • SciBite’s scientific named entity recognition (NER)
  • The search and analytics capabilities of Sinequa’s Insight platform in providing relevant and accurate search results

Presenters:

  • Adam Brown, Director of Professional Services, NA at SciBite
  • Rachael Huntley, Senior Scientific Curator at SciBite
  • Jeff Evernham, VP of Product Strategy at Sinequa
  • Nick Gogan, Sales Engineer at Sinequa

Related articles

  1. Using ontologies to unlock the full potential of your scientific data – Part 1

    In the first of this two-part blog, I describe what ontologies are and how you can use them to make the best use of scientific data within your organisation.

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  2. Using ontologies to unlock the full potential of your scientific data – Part 2

    This blog post focuses on mapping, building, and managing ontologies. In my previous blog, I described what ontologies are and how you can use them to make the best use of scientific data within your organization. Here I’ll expand upon this and focus on mapping, building, and managing ontologies.

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