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Enabling Health-Environmental Research Workflows with Knowledge Graphs
12 Pages Posted: 13 Feb 2024
More...Abstract
Background: Environmental factors contribute significantly to the global burden of disease. In epidemiology, researchers face the challenge of linking diverse health and environmental data sources initially generated for distinct purposes. This challenge becomes even more acute when studying the aetiology of rare diseases. In rare diseases, health events are infrequent, requiring efficient ways to link datasets beyond traditional approaches to harmonise the diverse data sources. To address this data linkage challenge and enable exploration of the complex relationships between environmental exposures and health outcomes, we present the Semantic Environmental and Rare Disease data Integration Framework (SERDIF).
Methods: SERDIF was evaluated through a usability study following a user-centred design. The study included health data researchers, including clinicians and epidemiologists, across three iterative phases. These researchers participated in remote usability testing sessions, completing tasks related to linking environmental and health data using SERDIF. Thematic analysis of qualitative and quantitative metrics was used to assess the framework's usability (effectiveness, efficiency and satisfaction) and potential usefulness for health data researchers.
Findings: SERDIF achieved interoperability through a Knowledge Graph approach based on Semantic Web technologies, enabling machine understanding and supporting complex queries with flexible templates. Usability testing reveals improved efficiency, effectiveness, and satisfaction metrics, while achieving the health data researcher requirements when linking health and environmental datasets. In addition, SERDIF adheres to FAIR principles generating a linked data output that is Findable, Accessible, Interoperable, and Reusable (FAIR), contributing to transparent and open science practices.
Interpretation: The framework addresses the specific challenge of linking health and environmental data, offering for the first time a design for health data linkage, a user-friendly interface, and export capabilities while adhering to FAIR principles.
Funding: European Union’s Horizon 2020 Research and Innovation Programme, funded under a Marie Skłodowska-Curie Innovative Training Network (MSCA ITN).
Declaration of Interest: None.
Ethical Approval: The Chairman, Prof. Richard Deane, on behalf of the Research Ethics Committee, has reviewed the amendment you submitted to the SJH/TUH JREC for the above named study and has given FULL approval for this amendment. Date of Valid Submission to REC: 21.10.2019 Date of Ethical Review: 08.05.2020
Keywords: Usability Testing, Semantic Data Integration, Knowledge Graph, Environmental Health Data, Rare Disease Research
Suggested Citation: Suggested Citation