Visualizing Data Interoperability for Food Systems Sustainability Research-From Spider Webs to Neural Networks.
USDA FoodData Central
agriculture
climate change
food prices
interoperability
nutrition
ontologies
population health
Journal
Current developments in nutrition
ISSN: 2475-2991
Titre abrégé: Curr Dev Nutr
Pays: United States
ID NLM: 101717957
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
received:
08
06
2023
revised:
11
09
2023
accepted:
18
09
2023
medline:
2
11
2023
pubmed:
2
11
2023
entrez:
2
11
2023
Statut:
epublish
Résumé
Food systems represent all elements and activities needed to feed the growing global population. Research on sustainable food systems is transdisciplinary, relying on the interconnected domains of health, nutrition, economics, society, and environment. The current lack of interoperability across databases poses a challenge to advancing research on food systems transformation. Crosswalks among largely siloed data on climate change, soils, agricultural practices, nutrient composition of foods, food processing, prices, dietary intakes, and population health are not fully developed. Starting with US Department of Agriculture FoodData Central, we assessed the interoperability of databases from multiple disciplines by identifying existing crosswalks and corresponding visualizations. Our visual demonstration serves as proof of concept, identifying databases in need of expansion, integration, and harmonization for use by researchers, policymakers, and the private sector. Interoperability is the key: ontologies and well-defined crosswalks are necessary to connect siloed data, transcend organizational barriers, and draw pathways from agriculture to nutrition and health.
Identifiants
pubmed: 37915997
doi: 10.1016/j.cdnut.2023.102006
pii: S2475-2991(23)26590-7
pmc: PMC10616130
doi:
Types de publication
Journal Article
Langues
eng
Pagination
102006Informations de copyright
© 2023 The Author(s).
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