Working hypothesis:

The use of biomedical semantics data resources plays increasingly an important role to drive data analysis in the biomedical domain. This includes the development of standards and procedures exploiting the public data resources, but also enables the annotation and interpretation of data with human readable concepts and thus improves the categorization capabilities of ML approaches based on the developing semantic resources.  The more the semantic resources become integrated the more the use of automatic reasoning and the inferences across ontologies play an important role to derive conclusive results.


  • Measure the consistency and accuracy of annotation with semantic resources
  • Provide state of the art classification techniques for the interpretation of public and restricted data
  • Establish biomedical data analytics methods in the semantic Web and provide standardization solutions


The integration of ontological data resources in the scientific community is ongoing. Using the data for the processing and interpretation of genomics and patient data is ongoing, and exploiting such approaches in the Semantic Web would be a key achievement. The integrated data and the analytical methods can be provided to industrial project partners (= targeted projects).