Challenges:

Recognize and rename fields to concept references automatically, via ML.

1. Create a large number of these normalization templates for a lot of data sources.
2. Machine-learn the field-names, and corresponding concepts, so that the data gets normalized automatically, and ready for analysts.
3. Result:
   • we shall have a universal data normalizer, which given any data, is able to automatically:
     • assign proper fields and value types to it.
     • identify their position in the nested hierarchies
     • understand their ontological meaning in contexts of their positions