Advanced search
1 file | 503.59 KB Add to list

An ontology to standardize research output of nutritional epidemiology : from paper-based standards to linked content

(2019) NUTRIENTS. 11(6).
Author
Organization
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 food and nutrition (n = 37), disease and specific population (n = 100), data description (n = 21), research description (n = 35), and supplementary (meta) data description (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.
Keywords
ontology, nutritional epidemiology, minimal data information, data quality descriptors, study reporting guidelines, Semantic Web, STROBE STATEMENT, REDUCING WASTE, QUALITY, TRIALS, CONSUMPTION, DIET

Downloads

  • nutrients-11-01300 3 .pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 503.59 KB

Citation

Please use this url to cite or link to this publication:

MLA
Yang, Chen, et al. “An Ontology to Standardize Research Output of Nutritional Epidemiology : From Paper-Based Standards to Linked Content.” NUTRIENTS, vol. 11, no. 6, 2019, doi:10.3390/nu11061300.
APA
Yang, C., Ambayo, H., De Baets, B., Kolsteren, P., Thanintorn, N., Hawwash, D., … Lachat, C. (2019). An ontology to standardize research output of nutritional epidemiology : from paper-based standards to linked content. NUTRIENTS, 11(6). https://doi.org/10.3390/nu11061300
Chicago author-date
Yang, Chen, Henry Ambayo, Bernard De Baets, Patrick Kolsteren, Nattapon Thanintorn, Dana Hawwash, Jildau Bouwman, Antoon Bronselaer, Filip Pattyn, and Carl Lachat. 2019. “An Ontology to Standardize Research Output of Nutritional Epidemiology : From Paper-Based Standards to Linked Content.” NUTRIENTS 11 (6). https://doi.org/10.3390/nu11061300.
Chicago author-date (all authors)
Yang, Chen, Henry Ambayo, Bernard De Baets, Patrick Kolsteren, Nattapon Thanintorn, Dana Hawwash, Jildau Bouwman, Antoon Bronselaer, Filip Pattyn, and Carl Lachat. 2019. “An Ontology to Standardize Research Output of Nutritional Epidemiology : From Paper-Based Standards to Linked Content.” NUTRIENTS 11 (6). doi:10.3390/nu11061300.
Vancouver
1.
Yang C, Ambayo H, De Baets B, Kolsteren P, Thanintorn N, Hawwash D, et al. An ontology to standardize research output of nutritional epidemiology : from paper-based standards to linked content. NUTRIENTS. 2019;11(6).
IEEE
[1]
C. Yang et al., “An ontology to standardize research output of nutritional epidemiology : from paper-based standards to linked content,” NUTRIENTS, vol. 11, no. 6, 2019.
@article{8621928,
  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 food and nutrition (n = 37), disease and specific population (n = 100), data description (n = 21), research description (n = 35), and supplementary (meta) data description (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.}},
  articleno    = {{1300}},
  author       = {{Yang, Chen and Ambayo, Henry and De Baets, Bernard and Kolsteren, Patrick and Thanintorn, Nattapon and Hawwash, Dana and Bouwman, Jildau and Bronselaer, Antoon and Pattyn, Filip and Lachat, Carl}},
  issn         = {{2072-6643}},
  journal      = {{NUTRIENTS}},
  keywords     = {{ontology,nutritional epidemiology,minimal data information,data quality descriptors,study reporting guidelines,Semantic Web,STROBE STATEMENT,REDUCING WASTE,QUALITY,TRIALS,CONSUMPTION,DIET}},
  language     = {{eng}},
  number       = {{6}},
  pages        = {{35}},
  title        = {{An ontology to standardize research output of nutritional epidemiology : from paper-based standards to linked content}},
  url          = {{http://doi.org/10.3390/nu11061300}},
  volume       = {{11}},
  year         = {{2019}},
}

Altmetric
View in Altmetric
Web of Science
Times cited: