CovKG: A Covid-19 Knowledge Graph for enabling multidimensional analytics on Covid-19 epidemiological data considering spatiotemporal, environmental, health, and socioeconomic aspects

International Journal of Information Management Data Insights Pub Date : 2025-02-27 DOI:10.1016/j.jjimei.2025.100325

Rudra Pratap Deb Nath , S.M. Shafkat Raihan , Tonmoy Chandro Das , Torben Bach Pedersen , Debasish Ghose

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引用次数: 0

Abstract

The Covid-19 pandemic is influenced by many environmental, health, and socioeconomic aspects such as air pollution, comorbidity, occupation, etc. To better manage future pandemics, decision-makers need comprehensive data on Covid-19 mortality and morbidity. Most Covid-19 data sources focus on spatiotemporal aspects, and existing research often overlook the combined impact of multiple interconnected factors. This study introduces a Covid-19 Knowledge Graph (CovKG) derived from 20 data sources, enabling multidimensional analysis of epidemiological data, including time, location, temperature, comorbidity, occupation, and others. CovKG is modeled using RDF, connected to 10,951 external resources, and semantically enriched with Data Cube (QB) and QB for OLAP (QB4OLAP) vocabularies to adhere to the FAIR principles and ensure OLAP compatibility. Finally, we perform a qualitative and comparative evaluation and extract statistical insights across multiple dimensions of Covid-19 epidemiology. When assessed, CovKG answers 100% of competency queries, outperforming other data stores that only answer 39%. CovKG and its analytical interface are available at https://bike-csecu.com/datasets/CovKG/.

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CovKG：一个Covid-19知识图谱，用于从时空、环境、健康和社会经济方面对Covid-19流行病学数据进行多维分析

2019冠状病毒病大流行受到许多环境、健康和社会经济方面的影响，如空气污染、合并症、职业等。为了更好地管理未来的大流行，决策者需要有关Covid-19死亡率和发病率的全面数据。大多数Covid-19数据来源侧重于时空方面，现有研究往往忽视了多个相互关联因素的综合影响。本研究引入了基于20个数据源的Covid-19知识图谱（CovKG），可对流行病学数据进行多维度分析，包括时间、地点、温度、合并症、职业等。CovKG使用RDF建模，连接到10,951个外部资源，并使用Data Cube （QB）和QB for OLAP （QB4OLAP）词汇表进行语义丰富，以遵循FAIR原则并确保OLAP兼容性。最后，我们进行了定性和比较评估，并从Covid-19流行病学的多个维度提取了统计见解。评估时，CovKG回答了100%的能力问题，优于其他仅回答39%的数据存储。CovKG及其分析界面可在https://bike-csecu.com/datasets/CovKG/上获得。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Information Management Data Insights

CiteScore

19.20

自引率

0.00%

发文量