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构建开放政府数据的知识图谱:以新斯科舍省疾病数据集为例。

Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets.

机构信息

Shannon School of Business, Cape Breton University, Grand Lake Dr., B1M 1A2, Sydney, Canada.

Department of Computer Science, Federal University of Juiz de Fora, Juiz de Fora, Brazil.

出版信息

J Biomed Semantics. 2023 Apr 18;14(1):4. doi: 10.1186/s13326-023-00284-w.

Abstract

The majority of available datasets in open government data are statistical. They are widely published by various governments to be used by the public and data consumers. However, most open government data portals do not provide the five-star Linked Data standard datasets. The published datasets are isolated from one another while conceptually connected. This paper constructs a knowledge graph for the disease-related datasets of a Canadian government data portal, Nova Scotia Open Data. We leveraged the Semantic Web technologies to transform the disease-related datasets into Resource Description Framework (RDF) and enriched them with semantic rules. An RDF data model using the RDF Cube vocabulary was designed in this work to develop a graph that adheres to best practices and standards, allowing for expansion, modification and flexible re-use. The study also discusses the lessons learned during the cross-dimensional knowledge graph construction and integration of open statistical datasets from multiple sources.

摘要

大多数开放政府数据中的可用数据集都是统计数据。它们由各国政府广泛发布,供公众和数据使用者使用。然而,大多数开放政府数据门户并未提供五星链接数据标准数据集。发布的数据集在概念上相互连接,但彼此孤立。本文构建了加拿大政府数据门户 Nova Scotia Open Data 中与疾病相关的数据集的知识图。我们利用语义网技术将疾病相关数据集转换为资源描述框架 (RDF),并使用语义规则对其进行丰富。本工作设计了一个使用 RDF 立方词汇表的 RDF 数据模型,以开发一个符合最佳实践和标准的图形,允许扩展、修改和灵活重用。该研究还讨论了在跨维度知识图构建和集成来自多个来源的开放统计数据集过程中获得的经验教训。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da90/10111831/1d7be88ec4cd/13326_2023_284_Fig1_HTML.jpg

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