评估语义环境健康数据框架的可用性:方法与研究

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Semantic Web Pub Date : 2022-11-03 DOI:10.3233/sw-223212
Albert Navarro-Gallinad, F. Orlandi, Jennifer Scott, Mark Little, D. O’Sullivan
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引用次数: 0

摘要

通过空气、土地和水传播的环境暴露会影响我们的健康,使我们更容易患上疾病。因此,研究人员需要面对一个复杂的任务,即整合环境暴露,并将其与健康事件与相关的时空和健康背景联系起来。我们提出了一种可用性评估方法和语义框架(即知识图谱、方法论和用户界面)的研究,使健康数据研究人员(HDR)能够将特定的健康事件与罕见疾病研究的环境数据联系起来。可用性研究包括17名具有爱尔兰抗中性粒细胞细胞质抗体(ANCA)相关血管炎(AAV)和日本川崎病相关健康数据专业知识的hdr,并且以前没有使用语义网(SW)技术的实践经验。评估结果是有希望的,因为它们表明该框架在允许研究人员自己将健康和环境数据联系起来同时隐藏软件技术的复杂性方面是有用的。作为这项工作的结果,我们还讨论了该方法的局限性以及对其他领域的适用性。除了对环境健康研究的直接影响之外,对评估方法的描述可以指导研究人员通过可用性研究使领域专家更容易获得软件技术。
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Evaluating the usability of a semantic environmental health data framework: Approach and study
Environmental exposures transported across air, land and water can affect our health making us more susceptible to developing a disease. Therefore, researchers need to face the complex task of integrating environmental exposures and linking them to health events with the relevant spatiotemporal and health context for individuals or populations. We present a usability evaluation approach and study of a semantic framework (i.e. Knowledge Graph, Methodology and User Interface) to enable Health Data Researchers (HDR) to link particular health events with environmental data for rare disease research. The usability study includes 17 HDRs with expertise in health data related to Anti-Neutrophil Cytoplasmic Antibody (ANCA)-associated vasculitis (AAV) in Ireland and Kawasaki Disease in Japan, and with no previous practical experience in using Semantic Web (SW) technologies. The evaluation results are promising in that they indicate that the framework is useful in allowing researchers themselves to link health and environmental data whilst hiding the complexities of SW technologies. As a result of this work, we also discuss the limitations of the approach together with the applicability to other domains. Beyond the direct impact on environmental health studies, the description of the evaluation approach can guide researchers in making SW technologies more accessible to domain experts through usability studies.
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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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