主动和被动环境暴露本体论

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Semantic Web Pub Date : 2024-03-01 DOI:10.3233/sw-243546
Csilla Vámos, Simon Scheider, Tabea Sonnenschein, R. Vermeulen
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引用次数: 0

摘要

暴露是健康和行为科学的核心概念,是研究空间环境对人们健康和行为的影响所必需的。尽管越来越多的研究测量了不同形式的暴露,包括空气质量、噪音和犯罪的影响,土地覆盖对体育活动的影响,或城市环境对食物摄入量的影响,但我们缺乏一个通用的环境暴露概念模型来捕捉所有这些不同暴露的主要结构。在这样一个模型的背景下,我们不仅可以系统地比较不同的方法,还可以更好地将有关这一主题的大量科学出版物的内容系统地联系起来并加以调整。例如,一个重要的方法论区别在于,将暴露作为某种活动的唯一结果的研究与环境作为直接独立原因的研究(主动暴露与被动暴露)。在此,我们提出了一种信息本体设计模式,可用于定义暴露及其变体模型。它是围绕人、活动、浓度、暴露、环境和健康风险等概念之间的因果关系建立的。我们使用描述逻辑学(DL)正式定义环境压力源和暴露变体,它允许从论文的 RDF 编码内容中自动推断。此外,还可将概念与研究中使用的数据模型和建模方法联系起来。为了测试这种模式,我们将能力问题转化为 SPARQL 查询,并在 RDF 编码的内容上运行这些查询。结果表明,研究特征可以通过反映重要方法差异的方式进行分类和总结。
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Ontology of active and passive environmental exposure
Exposure is a central concept of the health and behavioural sciences needed to study the influence of the environment on the health and behaviour of people within a spatial context. While an increasing number of studies measure different forms of exposure, including the influence of air quality, noise, and crime, the influence of land cover on physical activity, or of the urban environment on food intake, we lack a common conceptual model of environmental exposure that captures its main structure across all this variety. Against the background of such a model, it becomes possible not only to systematically compare different methodological approaches but also to better link and align the content of the vast amount of scientific publications on this topic in a systematic way. For example, an important methodical distinction is between studies that model exposure as an exclusive outcome of some activity versus ones where the environment acts as a direct independent cause (active vs. passive exposure). Here, we propose an information ontology design pattern that can be used to define exposure and to model its variants. It is built around causal relations between concepts including persons, activities, concentrations, exposures, environments and health risks. We formally define environmental stressors and variants of exposure using Description Logic (DL), which allows automatic inference from the RDF-encoded content of a paper. Furthermore, concepts can be linked with data models and modelling methods used in a study. To test the pattern, we translated competency questions into SPARQL queries and ran them over RDF-encoded content. Results show how study characteristics can be classified and summarized in a manner that reflects important methodical differences.
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来源期刊
Semantic Web
Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
8.30
自引率
6.70%
发文量
68
期刊介绍: The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.
期刊最新文献
Using Wikidata lexemes and items to generate text from abstract representations Editorial: Special issue on Interactive Semantic Web Empowering the SDM-RDFizer tool for scaling up to complex knowledge graph creation pipelines1 Special Issue on Semantic Web for Industrial Engineering: Research and Applications Declarative generation of RDF-star graphs from heterogeneous data
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