SPHN Schema Forge——利用语义web技术将医疗保健语义从人类可读转换为机器可读。

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Vasundra Touré, Deepak Unni, Philip Krauss, Abdelhamid Abdelwahed, Jascha Buchhorn, Leon Hinderling, Thomas R Geiger, Sabine Österle
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引用次数: 0

摘要

背景:瑞士个性化健康网络(SPHN)采用了资源描述框架(RDF),这是语义Web技术栈的核心组件,用于医学知识图中医疗保健数据的正式编码和交换。SPHN RDF Schema定义了应该如何表示数据元素的语义。虽然RDF已被证明是机器可读和可解释的,但对于没有专门背景的个人来说,阅读和理解RDF中表示的知识可能是一项挑战。由于这个原因,SPHN RDF Schema中描述的语义在被转换为其RDF表示之前,主要以用户可访问的表格格式(SPHN Dataset)定义。然而,这种翻译过程以前是手工的,耗时且劳动密集。结果:为了自动化和简化从表格表示到RDF表示的转换,开发了SPHN Schema Forge web服务。只需单击几下,该工具就会自动将符合sphn的Dataset电子表格转换为RDF模式。此外,它还生成用于数据验证的SHACL规则、模式的HTML可视化和用于基本数据分析的SPARQL查询。结论:SPHN Schema Forge显著减少了模式生成所需的人工工作量和时间,使研究人员能够专注于更有意义的任务,如SPHN框架内的数据解释和分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The SPHN Schema Forge - transform healthcare semantics from human-readable to machine-readable by leveraging semantic web technologies.

Background: The Swiss Personalized Health Network (SPHN) adopted the Resource Description Framework (RDF), a core component of the Semantic Web technology stack, for the formal encoding and exchange of healthcare data in a medical knowledge graph. The SPHN RDF Schema defines the semantics on how data elements should be represented. While RDF is proven to be machine readable and interpretable, it can be challenging for individuals without specialized background to read and understand the knowledge represented in RDF. For this reason, the semantics described in the SPHN RDF Schema are primarily defined in a user-accessible tabular format, the SPHN Dataset, before being translated into its RDF representation. However, this translation process was previously manual, time-consuming and labor-intensive.

Result: To automate and streamline the translation from tabular to RDF representation, the SPHN Schema Forge web service was developed. With a few clicks, this tool automatically converts an SPHN-compliant Dataset spreadsheet into an RDF schema. Additionally, it generates SHACL rules for data validation, an HTML visualization of the schema and SPARQL queries for basic data analysis.

Conclusion: The SPHN Schema Forge significantly reduces the manual effort and time required for schema generation, enabling researchers to focus on more meaningful tasks such as data interpretation and analysis within the SPHN framework.

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来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
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