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An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content
- Source :
- Nutrients, Volume 11, Issue 6, Nutrients, 6, 11, 8 June, Nutrients, Vol 11, Iss 6, p 1300 (2019), NUTRIENTS
- Publication Year :
- 2019
- Publisher :
- MDPI AG, 2019.
-
Abstract
- Background: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiology. Methods: Firstly, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Secondly, existing data standards and reporting guidelines for nutritional epidemiology were converted into an ontology. The terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Thirdly, the ontologies of the nutritional epidemiologic standards, reporting guidelines, and the core concepts were gathered in ONE. Three case studies were included to illustrate potential applications: (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts. Results: Ontologies for &ldquo<br />food and nutrition&rdquo<br />(n = 37), &ldquo<br />disease and specific population&rdquo<br />(n = 100), &ldquo<br />data description&rdquo<br />(n = 21), &ldquo<br />research description&rdquo<br />(n = 35), and &ldquo<br />supplementary (meta) data description&rdquo<br />(n = 44) were reviewed and listed. ONE consists of 339 classes: 79 new classes to describe data and 24 new classes to describe the content of manuscripts. Conclusion: ONE is a resource to automate data integration, searching, and browsing, and can be used to assess reporting completeness in nutritional epidemiology.
- Subjects :
- Agriculture and Food Sciences
Data Analysis
0301 basic medicine
Biomedical Research
Nutritional Sciences
Computer science
Inference
Ontology (information science)
computer.software_genre
0302 clinical medicine
Data quality descriptors
Medicine and Health Sciences
ontology
030212 general & internal medicine
Taxonomic rank
STROBE STATEMENT
Nutrition and Dietetics
Ontology
Linked data
Data Accuracy
study reporting guidelines
TRIALS
InformationSystems_MISCELLANEOUS
lcsh:Nutrition. Foods and food supply
Data integration
Technology and Engineering
REDUCING WASTE
data quality descriptors
lcsh:TX341-641
Article
DIET
Study reporting guidelines
03 medical and health sciences
Annotation
Terminology as Topic
QUALITY
Humans
minimal data information
Semantic Web
030109 nutrition & dietetics
Information retrieval
Nutritional epidemiology
Information Dissemination
CONSUMPTION
Minimal data information
Diet
nutritional epidemiology
Biological Ontologies
Epidemiologic Methods
computer
Food Science
Subjects
Details
- ISSN :
- 20726643
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Nutrients
- Accession number :
- edsair.doi.dedup.....823b070d6e0d8a3b1a2ac5f52e173a70