A Review of Environmental Factors for an Ontology-Based Risk Analysis for Pandemic Spread
Round 1
Reviewer 1 Report
The research, which aims to analyze environmental factors contributing to pandemic spread and propose a new approach for pandemic prediction using big data architecture, presents a significant contribution to this field. By conducting an empirical review and content analysis of studies archived in EBSCOhost databases from 2019 to 2022 and identifying key factors influencing pandemic spread, the authors have provided valuable insights into understanding and potentially mitigating the impact of pandemics such as COVID-19.
The proposed ontology-based big data architecture for collecting factors influencing pandemic spread and building a spread prediction model is innovative and addresses the limitations of traditional models like SEIR. Furthermore, the incorporation of multidimensional data and modern AI methods for training contagion scenarios presents a promising avenue for policymakers in planning effective pandemic prevention programs.
Additionally, the international scope of the study enhances its relevance and applicability across different regions and contexts, further strengthening its contribution to the field.
In my opinion, the paper is suitable for publication in this journal and the necessary revisions are minor.
There are some concerns regarding the description of the methodology that need to be addressed before the manuscript can be considered for publication.
The authors have outlined the methodology as an empirical study and content analysis to determine the environmental factors contributing to the pandemic outbreak. While the overall approach is appropriate, the description provided in the manuscript lacks sufficient detail regarding the process of extraction, selection, and analysis of studies. Specifically, the following points need to be addressed:
Extraction Process: The authors mentioned conducting a literature review to identify environmental factors causing the pandemic outbreak and utilizing EBSCOHost databases from 2019 to 2022. However, further clarification is needed on how the literature search was conducted, including the specific search terms used, any inclusion or exclusion criteria applied, and the rationale behind selecting EBSCOHost databases for the search.
Selection Criteria: The manuscript states that out of 588 studies retrieved, only 84 were found relevant. However, there is a lack of detail on the criteria used to determine the relevance of studies. It would be beneficial for the authors to provide a clear explanation of the inclusion and exclusion criteria applied during the study selection process.
Analysis Method: While the authors mention using content analysis to identify environmental factors and frequency counting to summarize relevant factors, there is limited information on the specific techniques employed for data analysis. Additionally, further elaboration is needed on the ground theory of information coding, grouping and classification, and theme generation used for analyzing environmental factors.
Explanation of Findings: The manuscript briefly mentions using literatures and self-exploratory methods to explain the findings. However, it would be helpful for the authors to provide more detail on how these methods were employed to interpret the identified environmental factors and derive insights from the analysis.
Author Response
(1) The authors have outlined the methodology as an empirical study and content analysis to determine the environmental factors contributing to the pandemic outbreak. While the overall approach is appropriate, the description provided in the manuscript lacks sufficient detail regarding the process of extraction, selection, and analysis of studies.
Extraction Process: The authors mentioned conducting a literature review to identify environmental factors causing the pandemic outbreak and utilizing EBSCOHost databases from 2019 to 2022. However, further clarification is needed on how the literature search was conducted, including the specific search terms used, any inclusion or exclusion criteria applied, and the rationale behind selecting EBSCOHost databases for the search.
=> The specific search terms used, the inclusion or exclusion criteria and the rationale behind selecting EBSCOHost were added in the "research method" chapter.
(2) Selection Criteria: The manuscript states that out of 588 studies retrieved, only 84 were found relevant. However, there is a lack of detail on the criteria used to determine the relevance of studies. It would be beneficial for the authors to provide a clear explanation of the inclusion and exclusion criteria applied during the study selection process.
=> It has been done in point 2. The inclusion or exclusion criteria were added in the "research method" chapter.
(3) Analysis Method: While the authors mention using content analysis to identify environmental factors and frequency counting to summarize relevant factors, there is limited information on the specific techniques employed for data analysis. Additionally, further elaboration is needed on the ground theory of information coding, grouping and classification, and theme generation used for analysing environmental factors.
=> The grounded theory of information coding, grouping and classification, and theme generation to identify environmental factors was discussed the "research method" chapter.
(4) Explanation of Findings: The manuscript briefly mentions using literatures and self-exploratory methods to explain the findings. However, it would be helpful for the authors to provide more detail on how these methods were employed to interpret the identified environmental factors and derive insights from the analysis.
=> In the “research method” chapter, how the literatures and self-exploratory methods were used for explaining the findings and derive insights from the analysis were done.
(5) Minor editing of English language required.
=> The manuscript has sent to editing service office again.
Reviewer 2 Report
The authors conducted an empirical review and content analysis to identify the environmental factors that cause the spread of a pandemic. Based on the results, they propose a Big Data architecture based on ontologies. The ontology summarizes the factors for prediction purposes. The work is innovative from the standpoint of the information they gather, classifying the factors that influence the spread of a pandemic. This is important because it allows the identification of a set of measures that can be analyzed by authorities in order to make better decisions. The work is well written. However, several modifications are required for it to be published:
- The work allows for collecting a set of factors to analyze how a pandemic spreads. However, there needs to be more to design a Big Data architecture. To qualify as an architecture, the complete process must be designed, from data ingestion to identifying data sources and visualization. This is not observed in the scheme created. I suggest changing the study's objective to a proposal for an ontology, but not as a Big Data architecture.
- The scheme achieved is attractive, but it does not seem to be an ontology. I suggest using some standard to represent the relationships between the found factors. Visualizing the relationships among them is essential.
- Modify the title since it should not be a Big Data architecture proposal.
- A sentiment analysis seems appropriate for future work. However, it is much more suitable for this work to relate the factors through a standard language like SBVR from OMG. This would allow a common language for multidisciplinary work.
Author Response
(1) The work allows for collecting a set of factors to analyze how a pandemic spreads. However, there needs to be more to design a Big Data architecture. To qualify as an architecture, the complete process must be designed, from data ingestion to identifying data sources and visualization. This is not observed in the scheme created. I suggest changing the study's objective to a proposal for an ontology, but not as a Big Data architecture.
=> The title of “A Review of Environmental Factors for an Ontology-Based Risk Analysis for Pandemic Spreading ”. Thank you for reviewer’s suggestion to make the title more precisely to reflect the manuscript’s content.
(2) The scheme achieved is attractive, but it does not seem to be an ontology. I suggest using some standard to represent the relationships between the found factors. Visualizing the relationships among them is essential.
=> The OWL/XML can be used to model the ontology. However, the implementation if using OWL/XML is not the scope of this study. To echo author’s concern, a high level design of the ontology was presented to demonstrate how to model the relationships between the found factors into the ontology
(3) Modify the title since it should not be a Big Data architecture proposal.
=> The title of “A Review of Environmental Factors for an Ontology-Based Risk Analysis for Pandemic Spreading ”. Thank you for reviewer’s suggestion to make the title more precisely to reflect the manuscript’s content.
(4) A sentiment analysis seems appropriate for future work. However, it is much more suitable for this work to relate the factors through a standard language like SBVR from OMG. This would allow a common language for multidisciplinary work.
=> Thanks for reviewer suggestion on future work. The OWL/XML and Jena was mentioned in the “conclusion and future work” chapter.
(5) Minor editing of English language required.
=> The manuscript has sent to editing service office again.
Round 2
Reviewer 2 Report
The reviewers have made the suggested changes. Only a few details remain to be improved, such as the abstract and the figures are too small and the text is not readable.
No details
Author Response
Response to reviewer’s comment of the minor revision.
(1) Only a few details remain to be improved, such as the abstract and the figures are too small and the text is not readable.
=> The font size of the abstract has changed from 9 to 10.
=> The font size of the text in figure 1 and 2 has changed from 8 to 10.
=> The figure 2 label “A high level design of the ontology for contact tracking” was added.
