Print Email Facebook Twitter Perspective: Towards Automated Tracking of Content and Evidence Appraisal of Nutrition Research Title Perspective: Towards Automated Tracking of Content and Evidence Appraisal of Nutrition Research Author Yang, C. Hawwash, D. de Baets, B. Bouwman, J. Lachat, C. Publication year 2020 Abstract Robust recommendations for healthy diets and nutrition require careful synthesis of available evidence. Given the increasing volume of research articles generated, the retrieval and synthesis of evidence are increasingly becoming laborious and time-consuming. Information technology could help to reduce workload for humans. To guide supervised learning however, human identification of key study characteristics is necessary. Reporting guidelines recommend that authors include essential content in articles and could generate manually labeled training data for automated evidence retrieval and synthesis. Here, we present a semiautomated approach to annotate, link, and track the content of nutrition research manuscripts. We used the STROBE extension for nutritional epidemiology (STROBE-nut) reporting guidelines to manually annotate a sample of 15 articles and converted the semantic information into linked data in a Neo4j graph database through an automated process. Six summary statistics were computed to estimate the reporting completeness of the articles. The content structure, presence of essential study characteristics as well as the reporting completeness of the articles are visualized automatically from the graph database. The archived linked data are interoperable through their annotations and relations. A graph database with linked data on essential study characteristics can enable Natural Language Processing in nutrition. Copyright © The Author(s) on behalf of the American Society for Nutrition 2020. Subject Graph databaseReporting guidelinesResearch semanticsSTROBE-nutHumanHuman experimentIdentification keyInformation retrievalLearningNatural language processingNutritionOntologyPractice guidelineSemanticsStandardizationSynthesis To reference this document use: http://resolver.tudelft.nl/uuid:3faa41a1-8b8d-49ad-96ff-b6da02bc85f4 DOI https://doi.org/10.1093/advances/nmaa057 TNO identifier 881675 ISSN 2156-5376 Source Advances in nutrition, 11 (5), 1079-1088 Document type article Files To receive the publication files, please send an e-mail request to TNO Library.