Evaluating the usability of a semantic environmental health data framework: approach and study

Tracking #: 3212-4426

Albert Navarro-Gallinad
Fabrizio Orlandi1
Jennifer Scott
Mark Little
Declan O'Sullivan

Responsible editor: 
Guest Editors SW Meets Health Data Management 2022

Submission type: 
Full Paper
Environmental exposures transported across air, land and water can affect our health making us more susceptible to developing a disease. Therefore, researchers need to face the complex task of integrating environmental exposures and linking them to health events with the relevant spatiotemporal and health context for individuals or populations. We present a usability evaluation approach and study of a semantic framework (i.e. Knowledge Graph, Methodology and User Interface) Health Data Researchers (HDR), when trying to link particular health events with environmental data to explore the environmental risk factors of rare diseases. The usability study includes 17 HDRs with expertise in health data related to ANCA associated vasculitis in Ireland and Kawasaki Disease in Japan, and with no previous practical experience in using Semantic Web (SW) technologies. The evaluation results are promising in that they indicate that the framework is useful in allowing researchers themselves to link health and environmental data whilst hiding the complexities of SW technologies. As a result of this work, we also discuss the limitations of the approach together with the applicability to other domains. Beyond the direct impact on environmental health studies, the description of the evaluation approach can guide researchers in making SW technologies more accessible to domain experts through usability studies.
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Solicited Reviews:
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Review #1
Anonymous submitted on 19/Aug/2022
Minor Revision
Review Comment:

Minor English editing is required. There were still a few grammatical and wording issues throughout that would benefit from a thorough proofing to make reading smoother. The authors added an adequate description which confirms the ability of the proposed framework to comply with HL7 standards. The authors provide sufficient information regarding the FAIRness of the proposed framework and the applicability to other domains. A comparison table reflecting the advantages of the proposed framework against the current state of the art should be added.

Review #2
By Ioannis Chrysakis submitted on 25/Aug/2022
Review Comment:

The second version of the paper contains significant improvements and additions which are in line with the reviewers comments on its previous versions.

Regarding my comments (Reviewer 3) all of them have been resolved or answered.
In particular the authors made updates to the text to include their contributions, discussion topics and a very helpful running example.
Moreover, the authors added a separate section to highlight the FAIRness of the framework and they provide in Appendix a metadata example as snippet to somehow demonstrate the health events data, as indicated by Reviewer 1.
The limitations of the study is important that have been added in a separate section (7.2) as indicated by Reviewer 2.

Consequently, I suggest that the paper to be published because it fits well with the journal's issue presenting a very interesting study to the health domain which can be extended to other domains as well.