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ARS Home » Northeast Area » Beltsville, Maryland (BHNRC) » Beltsville Human Nutrition Research Center » Methods and Application of Food Composition Laboratory » Research » Research Project #441024

Research Project: USDA FoodData Central: Integration of Food Science and Technology

Location: Methods and Application of Food Composition Laboratory

Project Number: 8040-10700-004-014-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 15, 2021
End Date: Sep 14, 2024

FoodData Central (FDC) is at the center of the U.S. Department of Agriculture (USDA)-based food information web. It serves as an integrated data system that presently provides—in one place—five distinct types of data containing information on food and nutrient profiles. FDC is USDA’s answer to the challenge of providing reliable, web-based, transparent, and easily accessible information about the nutrients and other components of foods and food products to meet the increasingly diverse needs of many audiences, including public health professionals, agricultural and environmental researchers, policy makers, nutrition professionals, healthcare providers, product developers, and consumers. Data have two components: their value and the metadata that describe the value, but even within a single discipline metadata may be complex and confusing. For example, in the food industry, the common yellow food dye has almost 2,000 different descriptors. Similarly, food processing terms may vary based on the recipe, formulation, tools and goals. The confusion becomes orders of magnitude greater between disciplines where the same terms may be used with different meanings and similar concepts may have completely unrelated terminology. The values in datasets can be standardized by scientific convention (e.g. moles, grams, wavelength etc.) and IT approaches can link multiple and diverse datasets. However, without a common metadata ‘language’ and semantic infrastructure, it may be completely impossible to relate and integrate the data. The science that seeks to understand how to ‘talk’ to diverse datasets in the same language is “computational ontology”. The objective will be to incorporate principles of food processing, food science and technology into the ontology of FDC.

The cooperator will collaborate with ARS scientists to integrate food science and technology principles and terminology into the development of an ontology for FDC to enable interconnectivity between different data sets focused on profiles of food composition across the supply chain. Food domain-specific ontology development will include agricultural field study factor terminology, food phenotypes including food physical structure, food molecular composition, food biological components and activities, and food production/transformation processes. The efforts will include extension of FoodOn to support USDA databases.