Semantic Data 2024: Taxonomy, Ontology, and Knowledge Graphs

The challenge
In life sciences, vast amounts of complex data are generated. Turning those data into meaningful discoveries is the real challenge.

Tackling the problem

Ontologies and knowledge graphs are transforming the way data are handled, helping researchers gain faster, more accurate insights to drive innovation.

Case studies of success

SciBite will share some real-world success stories—from projects such as ARCH to cutting-edge work at AstraZeneca. Stories that illustrate the tangible benefits of using semantic technologies and knowledge graphs.

Just as Google connected the dots with search and Facebook brought people together, we can break down the barriers that exist in life sciences - overcoming the often major roadblocks of complex terminology, data privacy, and governance.

We’ve already seen what’s possible when data is truly connected, but the key question is: How do we get there?

At SciBite, we believe the answer lies in implementing the FAIR data principles - making data Findable, Accessible, Interoperable, and Reusable.

SciBite’s team of expert ontologists, scientists, and data gurus has developed powerful AI-driven solutions to help make this a reality. They are keen to share their insights by:

• Explaining how SciBite is advancing semantic intelligence to enable our customers to enhance their FAIR data practices with greater ease and efficiency.
• Demonstrating cutting-edge technology as it undertakes real-time implementation.