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E-BOOK

  • Pages: 18

Linking data to unlock insights: the building blocks of semantic technology

An introduction to semantic technology for the life sciences industry

Our latest eBook has been written specifically for professionals in the life sciences industry. This comprehensive guide introduces the foundational concepts and modern applications of semantic technology, providing essential insights for organizations aiming to leverage this powerful tool.

 

  • Learn more about the history and development of semantic technology.
  • Understand the role of knowledge graphs and which contexts they excel in.
  • Get concrete advice on adopting and implementing these technologies effectively.

Whether you're looking to enhance data integration, improve research outcomes, or drive innovation in drug discovery, this eBook offers valuable guidance and expertise.

Register to download the eBook

What you will learn

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The origins of semantic technology

Discover the historical development of semantic technology, tracing back to early efforts in medical statistics and how these laid the groundwork for today’s advanced computational tools.

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Fundamentals of semantic technology

Explore the core components and methodologies of semantic technology, including knowledge graphs, ontologies, and natural language processing, and see how they can enhance data comprehension and usability.

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Applications in life sciences

Learn about the specific applications of semantic technology in life sciences, such as drug repurposing and patient data management, providing real-world examples of its impact on the industry.

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Adopting semantic technology

Gain practical guidance on the principles and strategies for successfully adopting and implementing semantic technologies within your organization to maximize data potential and innovation.

Linking data to unlock insights_ the building blocks of semantic technology An introduction to semantic technology for the life sciences industry (2)

An added value for ...

  • Data scientists 
  • Data analysts
  • Heads of IT


  • Developpers
  • Scientific researchers
  • Data directors
  • Data engineers
  • IT teams
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