Kim Hyeoneui, Jung Jinsun, Choi Jisung
The Research Institute of Nursing Science, College of Nursing, Seoul National University, Seoul, Republic of Korea.
Samsung Medical Center, Seoul, Republic of Korea.
JMIR Form Res. 2022 Apr 21;6(4):e34962. doi: 10.2196/34962.
Dietary habits offer crucial information on one's health and form a considerable part of the patient-generated health data. Dietary data are collected through various channels and formats; thus, interoperability is a significant challenge to reusing this type of data. The vast scope of dietary concepts and the colloquial expression style add difficulty to standardizing the data. The interoperability issues of dietary data can be addressed through Common Data Elements with metadata annotation to some extent. However, making culture-specific dietary habits and questionnaire-based dietary assessment data interoperable still requires substantial efforts.
The main goal of this study was to address the interoperability challenge of questionnaire-based dietary data from different cultural backgrounds by combining ontological curation and metadata annotation of dietary concepts. Specifically, this study aimed to develop a Dietary Lifestyle Ontology (DILON) and demonstrate the improved interoperability of questionnaire-based dietary data by annotating its main semantics with DILON.
By analyzing 1158 dietary assessment data elements (367 in Korean and 791 in English), 515 dietary concepts were extracted and used to construct DILON. To demonstrate the utility of DILON in addressing the interoperability challenges of questionnaire-based multicultural dietary data, we developed 10 competency questions that asked to identify data elements sharing the same dietary topics and assessment properties. We instantiated 68 data elements on dietary habits selected from Korean and English questionnaires and annotated them with DILON to answer the competency questions. We translated the competency questions into Semantic Query-Enhanced Web Rule Language and reviewed the query results for accuracy.
DILON was built with 262 concept classes and validated with ontology validation tools. A small overlap (72 concepts) in the concepts extracted from the questionnaires in 2 languages indicates that we need to pay closer attention to representing culture-specific dietary concepts. The Semantic Query-Enhanced Web Rule Language queries reflecting the 10 competency questions yielded correct results.
Ensuring the interoperability of dietary lifestyle data is a demanding task due to its vast scope and variations in expression. This study demonstrated that we could improve the interoperability of dietary data generated in different cultural contexts and expressed in various styles by annotating their core semantics with DILON.
饮食习惯提供了有关个人健康的关键信息，并且构成了患者生成的健康数据的重要组成部分。饮食数据通过各种渠道和格式收集；因此，互操作性是重用此类数据的一项重大挑战。饮食概念的广泛范围和口语化表达风格增加了数据标准化的难度。饮食数据的互操作性问题可以通过带有元数据注释的通用数据元素在一定程度上得到解决。然而，使特定文化的饮食习惯和基于问卷的饮食评估数据具有互操作性仍需要付出巨大努力。
本研究的主要目标是通过结合饮食概念的本体管理和元数据注释，解决来自不同文化背景的基于问卷的饮食数据的互操作性挑战。具体而言，本研究旨在开发一种饮食生活方式本体（DILON），并通过用DILON注释其主要语义来证明基于问卷的饮食数据的互操作性得到改善。
通过分析1158个饮食评估数据元素（韩语367个，英语791个），提取了515个饮食概念并用于构建DILON。为了证明DILON在解决基于问卷的多文化饮食数据的互操作性挑战方面的效用，我们提出了10个能力问题，要求识别共享相同饮食主题和评估属性的数据元素。我们实例化了从韩语和英语问卷中选择的68个饮食习惯数据元素，并用DILON对其进行注释以回答能力问题。我们将能力问题翻译成语义查询增强网络规则语言，并审查查询结果的准确性。
DILON由262个概念类构建而成，并用本体验证工具进行了验证。从两种语言的问卷中提取的概念有少量重叠（72个概念），这表明我们需要更加关注特定文化饮食概念的表示。反映10个能力问题的语义查询增强网络规则语言查询产生了正确的结果。
由于饮食生活方式数据的范围广泛和表达方式多样，确保其互操作性是一项艰巨的任务。本研究表明，我们可以通过用DILON注释其核心语义来提高在不同文化背景下生成并以各种方式表达的饮食数据的互操作性。
