The development and evaluation of a quality assessment framework for reuse of dietary intake data: an FNS-Cloud study
Laura A. Bardon, Grace Bennett, Michelle Weech, Faustina Hwang, Eve F. A. Kelly, Julie A. Lovegrove, Panče Panov, Siân Astley, Paul Finglas, Eileen R. Gibney

TL;DR
This paper introduces a tool to assess the quality of dietary intake data for reuse, aiming to help researchers decide if datasets are suitable for their studies.
Contribution
The paper presents a novel quality assessment framework and online tool for evaluating dietary intake datasets to support informed reuse decisions.
Findings
The quality assessment framework was positively rated by users for its format and feedback messages.
Participants found the tool potentially useful for training students and inexperienced researchers.
The tool is openly accessible and intended to guide researchers in determining dataset suitability for reuse.
Abstract
A key aim of the FNS-Cloud project (grant agreement no. 863059) was to overcome fragmentation within food, nutrition and health data through development of tools and services facilitating matching and merging of data to promote increased reuse. However, in an era of increasing data reuse, it is imperative that the scientific quality of data analysis is maintained. Whilst it is true that many datasets can be reused, questions remain regarding whether they should be, thus, there is a need to support researchers making such a decision. This paper describes the development and evaluation of the FNS-Cloud data quality assessment tool for dietary intake datasets. Markers of quality were identified from the literature for dietary intake, lifestyle, demographic, anthropometric, and consumer behavior data at all levels of data generation (data collection, underlying data sources used, dataset…
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Taxonomy
TopicsNutritional Studies and Diet · Nutrition, Genetics, and Disease · Biomedical Text Mining and Ontologies
