FoodOntoMap: Linking Food Concepts across Different Food Ontologies

摘要

In the last decade, a great amount of work has been done in predictive modelling in healthcare. All this work is made possible by the existence of several available biomedical vocabularies and standards, which play a crucial role in understanding health information. Moreover, there are available systems, such as the Unified Medical Language System, that bring and link together all these biomedical vocabularies to enable interoperability between computer systems. However, in 2019, Lancet Planetary Health published that the year 2019 is going to be the year of nutrition, where the focus will be on the links between food systems, human health, and the environment. While there is a large number of available resources for the biomedical domain, only a limited number of resources can be utilized in the food domain. There is still no annotated corpus with food concepts, and there are only a few rule-based food named-entity recognition systems for food concepts extraction. There are also several food ontologies that exist, each developed for a specific application scenario. However there are no links between these ontologies. For this reason, we have created a FoodOntoMap resource that consists of food concepts extracted from recipes. For each food concept, semantic tags from four food ontologies are assigned. With this, we have created a resource that provides a link between different food ontologies that can be further reused to develop applications for understanding the relation between food systems, human health, and the environment.