Publishing and Interlinking COVID-19 Data Using Linked Open Data Principles: Toward Effective Healthcare Planning and Decision-Making

Abstract

The COVID-19 data is critical to support countries and healthcare organizations for effective planning and evidence-based practices to counter the pressures of cost reduction, improved coordination, and outcome and produce more with less. Several COVID-19 datasets are published on the web to support stakeholders in gaining valuable insights for better planning and decision-making in healthcare. However, the datasets are produced in heterogeneous proprietary formats, which create data silos and make data discovery and reuse difficult. Further, the data integration for analysis is difficult and is usually performed by the domain experts manually, which is time-consuming and error-prone. Therefore, an explicit, flexible, and widely acceptable methodology to represent, store, query, and visualize COVID-19 data is needed. In this paper, we have presented the design and development of the Linked Open COVID-19 Data system for structuring and transforming COVID-19 data into semantic format using explicitly developed ontology and publishing on the web using Linked Open Data (LOD) principles. The key motivation of this research is the evaluation of LOD technology as a potential option and application of the available Semantic Web tools (i.e., Protégé, Excel2RDF, Fuseki, Silk, and Sgvizler) for building LOD-based COVID-19 information systems. We have also underpinned several use-case scenarios exploiting the LOD format of the COVID-19 data, which could be used by applications and services for providing relevant information to the end-users. The effectiveness of the proposed methodology and system is evaluated using the system usability scale and descriptive statistical methods and results are found promising.

Systematizing Information Use to Address Determinants of Health Worker Health in South Africa: A Cross-sectional Mixed Method Study

“…However, conversely, as others have also noted, OHIS, if accessible and timely, can be used for monitoring and evaluating costing, outcomes and impacts related to OSH in the workplace [ 61 ]. The strong views expressed on the value of having access to COVID-19 data and the desire for OSH-related data more generally in this study support the conclusion that OHIS is feasible and can be critical for effective surveillance and planning [ 62 , 63 ]. Indeed, the reported higher utilisation of COVID-19 related information for decision-making documented in this study should strengthen the call for an upgraded and functional OHIS for other hazards as well.…”

OntoSuSD: Software engineering approaches integration ontology for sustainable software development

“…Some of the available ontologies are found providing matching set of definitions satisfying OntoSuSD data needs up to certain extant but not completely. Reusing existing ontologies could increase data interoperability but could increase complexity in retrieval by not efficiently modeling the new data needs 53 . The bespoke ontology could reduce data interoperability but could allow to model data in an efficient manner 53 .…”

“…Reusing existing ontologies could increase data interoperability but could increase complexity in retrieval by not efficiently modeling the new data needs 53 . The bespoke ontology could reduce data interoperability but could allow to model data in an efficient manner 53 . Therefore, a bespoke OntoSuSD ontology is developed in this research to provide semantic definitions to the terms (concepts and properties), which are not available in the existing ontologies.…”

Developing a Linked Open Data Platform for Folktales in the Greater Mekong Subregion

“…Using RDF and Silk-a LOD-based system developed and evaluated by the WHO health observatory dataset, these systems allowed flexible queries and visualizations, receiving positive usability feedback, with some users finding SPARQL queries challenging. Ali et al [6] also present the Linked Open COVID-19 Data System, utilizing LOD principles to structure and transform COVID-19 data into a semantic format to evaluate Semantic Web tools' efficacy in building LOD-based COVID-19 information systems, with promising results for providing valuable insights and information to stakeholders. Similar to D'Agostino et al [7], they discuss the intersection of open data and public health, emphasizing the need for open access to public health data during disease outbreaks, which highlights the lack of articulated policy guidelines for data collection and management in many countries, particularly in Latin American countries.…”