Reviewers will be asked to answer the following questions when completing a review of an article:
- Does the paper contribute to the body of knowledge?
- Is the paper technically sound?
- Is the subject matter presented in a comprehensive manner?
The decision options you can choose from when reviewing an article are
- Accept: Reviewers should only recommend accepting if there are minor edits required prior to publication (grammar, minor edits to figures or graphs, etc.)
- Revision Required: The reviewer should recommend this decision if the article has merit but requires updates before it can be published.
- Reject: The reviewer should recommend this option if you feel the changes needed are too significant, if the additional revision would not improve the manuscript, or if the article was previously rejected (updates required before resubmission) but the authors did not sufficiently address the reviewers’ concerns, and the article is still not ready for publication.
The criteria for an article to be accepted for publication include:
- Results reported have not been submitted or published elsewhere (although expanded versions of conference publications as well as preprints are eligible for submission).
- Experiments, statistics, and other analyses are performed to a high technical standard and are described in sufficient detail.
- Conclusions are presented in an appropriate fashion and are supported by the data.
- The article is written in Standard English with correct grammar.
- Appropriate references to related prior published works must be included.
- The article falls within the scope.
The reviewer needs to do a good quality review as
- The article should be original writing that enhances and contributes to the existing body of knowledge in the given subject area. Original review articles and surveys are acceptable, even if new data/concepts are not presented, but there must be a clear advance over existing work. **If you have any concerns about plagiarism, please alert the Associate Editor or article administrator immediately. Please do not run the manuscript through any plagiarism software. Each article submitted is scanned for plagiarism and evaluated during our thorough prescreening process.
- Summarize the work, comment on its overall merits and drawbacks, and provide constructive, substantial feedback.
- Consider the strength of the technical content.
- Does the literature review provide sufficient background and motivation for the work?
- Review the theoretical/experimental depth, strength of analysis, quality of supporting data, and results.
- Is there sufficient benchmarking and validation, are the conclusions supported by the data and analysis and is the flow of information logical?
- Is there enough information in this paper for the experiments to be reproducible? If not, comment on what additional or supplementary information is needed. Are there any major technical flaws?
- Comment on the article’s technical presentation and organization. Consider things like the structure of the paper, language, writing style, quality of figures and tables, typos, and formatting.
The reviewer can ask authors to cite specific references
- Suggesting specific references, including articles you have authored, if not relevant to the article or at an excessive level, is not permitted.
- You are expected to check if the references are current and relevant to the subject. If you feel that the authors have overlooked important prior research, we encourage you to recommend particular topic areas rather than specific articles to improve their literature review and/or better highlight the advantages over the state-of-the-art. If there are any irrelevant, inappropriate, or unnecessary references, be sure to mention this in your comments to the authors.
- We, of course, realize that sometimes authors may miss crucial references to seminal work or even very recent publications that the authors would benefit from seeing, so if you are going to recommend specific references while completing the review, please be sure to explain why you believe they are relevant to the work.