  Measuring emotions is a real challenge for fundamental and applied research,
especially in ecological contexts. de Wijk and Noldus propose combining two
types of measures-explicit to characterize a specific food, and
implicit-physiological-to capture the whole experience of a meal in real-life
situations. This raises several challenges including development of new and
miniaturized sensors and devices but also developing new ways of data analysis.
We suggest a path to follow for future studies regarding data analysis: to
include Data Science in the game. This field of research may enable developing
predictive but also explicative models that link subjective experience of
emotions and physiological responses in real-life contexts. We suggest that
food scientists should go out of their comfort zone by collaborating with
computer scientists and then be trained with the new tools of Data Science,
which will undoubtedly enable them 1/ to better manage complex and
heterogeneous data sets, 2/ to extract knowledge that will be essential to this
field of research.
