  Cultures around the world have acquired unique culinary practices reflected
in traditional recipe compositions. Data-driven analysis has the potential to
provide interesting insights into the structure of recipes and organizational
principles of cuisines. We provide a curated compilation of 45772 traditional
recipes from over 22 regions across the world. Using this resource in
conjunction with data of flavor molecules from natural ingredients, we
implement data-driven investigations for probing flavor pairing patterns in
these recipes. Our analysis reveals non-random recipe compositions
characterized with either 'uniform' or 'contrasting' flavor blending and
identifies popularity of ingredients as a key contributing factor across all
cuisines. Thus we provide a framework for data-driven investigations of
culinary patterns in recipes which can be leveraged for applications aimed at
food design, generating novel flavor pairings and tweaking recipes for better
nutrition and health.
