Food Composition Data and Tools Online and Their Use in Research and Policy: EuroFIR AISBL Contribution in 2022.

Food, nutrition, and health are linked, and detailed knowledge of nutrient compositions and bioactive characteristics is needed to understand these relationships. Additionally, increasingly these data are required by database systems and applications. This communication aims to describe the contribution to databases and nutrition fields as well as the activities of EuroFIR AISBL; this member-based, non-profit association was founded to ensure sustained advocacy for food information in Europe and facilitate improved data quality, storage, and access as well as encouraging wider exploitation of food composition data for both research and commercial purposes. In addition to the description of its role and main objectives, a snapshot of EuroFIR AISBL's activities over the years is also given using a quantitative research literature analysis approach. The focus of this communication is to provide descriptions and updates of EuroFIR's online tools, i.e., FoodEXplorer, eBASIS, and PlantLIBRA, by highlighting the main uses and applications. Integrating food-related infrastructures and databases, following standardized and harmonized approaches, and considering interoperability and metrological principles are significant challenges. Ongoing activities and future plans of EuroFIR AISBL are highlighted, including, for instance, work within the Food Nutrition Security Cloud (FNS-Cloud) to make food, nutrition, and (food) security data more findable, accessible, interoperable, and ultimately reusable.

A Search Engine Concept to Improve Food Traceability and Transparency: Preliminary Results.

In recent years, the digital revolution has involved the agrifood sector. However, the use of the most recent technologies is still limited due to poor data management. The integration, organisation and optimised use of smart data provides the basis for intelligent systems, services, solutions and applications for food chain management. With the purpose of integrating data on food quality, safety, traceability, transparency and authenticity, an EOSC-compatible (European Open Science Cloud) traceability search engine concept for data standardisation, interoperability, knowledge extraction, and data reuse, was developed within the framework of the FNS-Cloud project (GA No. 863059). For the developed model, three specific food supply chains were examined (olive oil, milk, and fishery products) in order to collect, integrate, organise and make available data relating to each step of each chain. For every step of each chain, parameters of interest and parameters of influence-related to nutritional quality, food safety, transparency and authenticity-were identified together with their monitoring systems. The developed model can be very useful for all actors involved in the food supply chain, both to have a quick graphical visualisation of the entire supply chain and for searching, finding and re-using available food data and information.

Importance and use of reliable food composition data generation by nutrition/dietetic professionals towards solving Africa's nutrition problem: constraints and the role of FAO/INFOODS/AFROFOODS and other stakeholders in future initiatives.

Despite the rich biodiversity of the African continent and the tremendous progress so far made in food production, Africa is still struggling with the problems of food insecurity, hunger and malnutrition. To combat these problems, the production and consumption of nutritious and safe foods need to be promoted. This cannot be achieved without reliable data on the quantity and quality of nutrients and other components provided through these foods. Food composition data (FCD) are compiled as food composition tables (FCT) or food composition databases (FCDB). These are subsequently used for a variety of purposes, ranging from clinical practice, research, public health/education, food industry to planning and policy, as well as nutrition monitoring and surveillance. To perform these functions effectively, the importance of reliable FCT/FCDB cannot be overemphasised. Poor quality FCT/FCDB have serious consequences on the health of the population, and provide skew evidence towards developing nutrition and health-related policies. The present paper reviews different methods to generate FCT/FCDB, their importance and use in assisting nutrition/dietetic professionals in solving Africa's nutrition problems; current status of FCT/FCDB generation, compilation and dissemination in Africa, constraint to their use by professionals and the role of FAO/INFOODS/AFROFOODS and other stakeholders towards improvement and future initiatives. The information provided will create awareness on the need for up-to-date and high-quality FCT/FCDB and facilitate the identification of data gaps and prioritisation of future efforts in FCD generation, compilation and dissemination in Africa and subsequent strategies for the alleviation of the food and nutrition problems in Africa.

Ensuring Food Integrity by Metrology and FAIR Data Principles.

Food integrity is a general term for sound, nutritive, healthy, tasty, safe, authentic, traceable, as well as ethically, safely, environment-friendly, and sustainably produced foods. In order to verify these properties, analytical methods with a higher degree of accuracy, sensitivity, standardization and harmonization and a harmonized system for their application in analytical laboratories are required. In this view, metrology offers the opportunity to achieve these goals. In this perspective article the current global challenges in food analysis and the principles of metrology to fill these gaps are presented. Therefore, the pan-European project METROFOOD-RI within the framework of the European Strategy Forum on Research Infrastructures (ESFRI) was developed to establish a strategy to allow reliable and comparable analytical measurements in foods along the whole process line starting from primary producers until consumers and to make all data findable, accessible, interoperable, and re-usable according to the FAIR data principles. The initiative currently consists of 48 partners from 18 European Countries and concluded its "Early Phase" as research infrastructure by organizing its future structure and presenting a proof of concept by preparing, distributing and comprehensively analyzing three candidate Reference Materials (rice grain, rice flour, and oyster tissue) and establishing a system how to compile, process, and store the generated data and how to exchange, compare them and make them accessible in data bases.

A conceptual framework for the collection of food products in a Total Diet Study.

A total diet study (TDS) provides representative and realistic data for assessing the dietary intake of chemicals, such as contaminants and residues, and nutrients, at a population level. Reproducing the diet through collection of customarily consumed foods and their preparation as habitually eaten is crucial to ensure representativeness, i.e., all relevant foods are included and all potential dietary sources of the substances investigated are captured. Having this in mind, a conceptual framework for building a relevant food-shopping list was developed as a research task in the European Union's 7th Framework Program project, 'Total Diet Study Exposure' (TDS-Exposure), aimed at standardising methods for food sampling, analyses, exposure assessment calculations and modelling, priority foods, and selection of chemical contaminants. A stepwise approach following the knowledge translation (KT) model for concept analysis is proposed to set up a general protocol for the collection of food products in a TDS in terms of steps (characterisation of the food list, development of the food-shopping list, food products collection) and pillars (background documentation, procedures, and tools). A simple model for structuring the information in a way to support the implementation of the process, by presenting relevant datasets, forms to store inherent information, and folders to record the results is also proposed. Reproducibility of the process and possibility to exploit the gathered information are two main features of such a system for future applications.

FoodCASE: A system to manage food composition, consumption and TDS data.

Food and nutrition scientists, nowadays, need to manage an increasing amount of data regarding food composition, food consumption and Total Diet Studies (TDS). The corresponding datasets can contain information about several thousand different foods, in different versions from different studies. FoodCASE is a system that has been developed to manage these different datasets. It also support flexible means of linking between datasets and generally provide support for the different processes involved in the acquisition, management and processing of data. In this paper, the most important concepts to implement existing guidelines and standards for proper food data management are presented, as well as different use cases of data import and proofs of concepts demonstrating the ability to manage data in FoodCASE.

Implementing the EuroFIR Document and Data Repositories as accessible resources of food composition information.

The EuroFIR Document and Data Repositories are being developed as accessible collections of source documents, including grey literature, and the food composition data reported in them. These Repositories will contain source information available to food composition database compilers when selecting their nutritional data. The Document Repository was implemented as searchable bibliographic records in the Europe PubMed Central database, which links to the documents online. The Data Repository will contain original data from source documents in the Document Repository. Testing confirmed the FoodCASE food database management system as a suitable tool for the input, documentation and quality assessment of Data Repository information. Data management requirements for the input and documentation of reported analytical results were established, including record identification and method documentation specifications. Document access and data preparation using the Repositories will provide information resources for compilers, eliminating duplicated work and supporting unambiguous referencing of data contributing to their compiled data.

A scope classification of data quality requirements for food composition data.

Data quality is an important issue when managing food composition data since the usage of the data can have a significant influence on policy making and further research. Although several frameworks for data quality have been proposed, general tools and measures are still lacking. As a first step in this direction, we investigated data quality requirements for an information system to manage food composition data, called FoodCASE. The objective of our investigation was to find out if different requirements have different impacts on the intrinsic data quality that must be regarded during data quality assessment and how these impacts can be described. We refer to the resulting classification with its categories as the scope classification of data quality requirements. As proof of feasibility, the scope classification has been implemented in the FoodCASE system.