Development of a quality evaluation framework for consumer generated food consumption data: D7.3

Maringer, Marcus, Klepacz, Naomi, Ekman, Susanne, Normann, A., Raats, Monique M., Verain, Muriel and Geelen, Anouk (2016) Development of a quality evaluation framework for consumer generated food consumption data: D7.3 European Commission 26pp.

Abstract

RICHFIELDS is a design project of a research infrastructure (RI) and data platform which aims to collect, integrate, analyse and share food consumption and associated lifestyle data for the better understanding about what people eat and why they make their choices. One important source of data RICHFIELDS is focusing on is data generated by a vast amount of consumers and users of wearables and software applications, which are accessible to the general public. For the design phase of this RI it is crucial to provide an overview and characterization (Deliverable 7.1) and an evaluation (Deliverable 7.5) of consumer generated food consumption and associated lifestyle data. For the creation of these deliverables the current deliverable (Deliverable 7.3) plays a key role. Aim of this deliverable is to define a set of quality criteria which forms the basis of the evaluation of consumer generated food consumption and lifestyle data and which supports the identification of relevant opportunities as well as possible gaps and needs regarding data integration and sharing. In addition, the quality framework created in this deliverable should provide structure and guidance for data collection and characterization, which is needed for the inventory of consumer generated food consumption and lifestyle data collection tools. More specifically the framework will provide operationalisations for each quality criterion in the form of a set of relevant questions that should be answered for each tool included in the inventory of deliverable 7.1. Based on the needs of Phase 3 as they have been identified in the DOA, a quality assessment framework has been created for the evaluation of data in terms of scientific relevance, data management and legal governance. Data quality related to these three dimensions were considered important, because they can provide indications about: 1) what we can learn from such consumer generated data about peoples’ food consumption behavior, 2) the legal limitations, organizational restrictions, confidentiality and privacy concerns related to collection, integration and dissemination of consumer generated data and 3) the technical protocols and standards for data access and data processing. A literature search has been conducted and existing quality frameworks of eHealth and mHealth applications have been summarized. Quality criteria related to the dimensions of scientific relevance, data management and legal governance where characterized and based on expert opinions and overall feasibility included in the final quality assessment framework. Since the summarized existing quality frameworks were found to be too unspecific regarding scientific relevance of food consumption and lifestyledata we additionally relied on the current literature on dietary intake assessments and the determinants of food consumption behaviour for the creation of the quality criteria related to the dimension of scientific relevance. Since a large number of quality criteria have beenexcluded from the quality framework the scope of quality assessment by the current framework will be limited, however, we believe that the selected quality criteria are relevant and comprehensive across the needs and requirements of the various disciplines involved in designing the blueprint of the RI and data platform.

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Contributors

Author: Naomi Klepacz

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