  Metabolomics is becoming a mature part of analytical chemistry as evidenced
by the growing number of publications and attendees of international
conferences dedicated to this topic. Yet, a systematic treatment of the
fundamental structure and properties of metabolomics data is lagging behind. We
want to fill this gap by introducing two fundamental theories concerning
metabolomics data: data theory and measurement theory. Our approach is to ask
simple questions, the answers of which require applying these theories to
metabolomics. We show that we can distinguish at least four different levels of
metabolomics data with different properties and warn against confusing data
with numbers.
