The state of food composition databases: data attributes and FAIR data harmonization in the era of digital innovation Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.3389/fnut.2025.1552367
Introduction Food composition databases (FCDBs) are essential resources for characterizing, documenting, and advancing scientific understanding of food quality across the entire spectrum of edible biodiversity. This knowledge supports a wide range of applications with societal impact spanning the global food system. To maximize the utility of food composition data, FCDBs must adhere to criteria such as validated analytical methods, high-resolution metadata, and FAIR Data Principles (Findable, Accessible, Interoperable, and Reusable). However, complexity and variability in food data pose significant challenges to meeting these standards. Methods In this study, we conducted an integrative review of 35 data attributes across 101 FCDBs from 110 countries. The data attributes were categorized into three groups: general database information, foods and components, and FAIRness. Results Our findings reveal evaluated databases show substantial variability in scope and content, with the number of foods and components ranging from few to thousands. FCDBs with the highest numbers of food samples (≥1,102) and components (≥244) tend to rely on secondary data sourced from scientific articles or other FCDBs. In contrast, databases with fewer food samples and components predominantly feature primary analytical data generated in-house. Notably, only one-third of FCDBs reported data on more than 100 food components. FCDBs were infrequently updated, with web-based interfaces being updated more frequently than static tables. When assessed for FAIR compliance, all FCDBs met the criteria for Findability. However, aggregated scores for Accessibility, Interoperability, and Reusability for the reviewed FCDBs were 30, 69, and 43%, respectively. Discussion These scores reflect limitations in inadequate metadata, lack of scientific naming, and unclear data reuse notices. Notably, these results are associated with country economic classification, as databases from high-income countries showed greater inclusion of primary data, web-based interfaces, more regular updates, and strong adherence to FAIR principles. Our integrative review presents the current state of FCDBs highlighting emerging opportunities and recommendations. By fostering a deeper understanding of food composition, diverse stakeholders across food systems will be better equipped to address societal challenges, leveraging data-driven solutions to support human and planetary health.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fnut.2025.1552367
- https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1552367/pdf
- OA Status
- gold
- Cited By
- 1
- References
- 55
- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4408642826Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fnut.2025.1552367Digital Object Identifier
- Title
-
The state of food composition databases: data attributes and FAIR data harmonization in the era of digital innovationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-03-19Full publication date if available
- Authors
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Sarah Brinkley, Jenny Johana Gallo‐Franco, Natalia Vázquez-Manjarrez, Juliana Chaura, Naa Kwarley-Aba Quartey, Sahar B. Toulabi, Melanie T. Odenkirk, Éva Jermendi, Marie‐Angélique Laporte, Herman Erick Lutterodt, Reginald Adjetey Annan, Mariana Barboza, Endale Amare, Warangkana Srichamnong, Andrés Jaramillo-Botero, Gina Kennedy, Jaclyn Bertoldo, Jessica E. Prenni, Maya Rajasekharan, John de la Parra, Selena AhmedList of authors in order
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https://doi.org/10.3389/fnut.2025.1552367Publisher landing page
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https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1552367/pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1552367/pdfDirect OA link when available
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Metadata, Interoperability, Computer science, Harmonization, Database, Geospatial analysis, Data quality, Food composition data, Data science, World Wide Web, Geography, Business, Service (business), Food science, Orange (colour), Marketing, Cartography, Chemistry, Acoustics, PhysicsTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| publication_date | 2025-03-19 |
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