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.

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.