Thank for agreeing to review an article for Data & Policy.
Data & Policy is an open access journal concerned with the potential for and impact of data science on policy and governance. The opening editorial sets out some of the issues the journal is seeking to address: the Editors-in-Chief call for a deeper understanding of "policy-data interactions" and the need for a “consistent, symmetrical approach to consideration of systems of policy and data, [and] how they interact with one another.”
Below we outline some guidelines for reviewers. The journal operates a single blind peer review process as standard, but note that for a specific set of articles (Telco Big Data Analytics for Covid-19) we are operating an open peer review process.
Data & Policy reviewer guidelines (regular submissions)
Articles submitted to Data & Policy are subject to a single blind review process and are seen by a minimum of two reviewers. Research articles may be assigned to an associate editor (often an individual on the Editorial Board with specific expertise) who will seek reviewer input before recommending a decision to the Editors-in-Chief.
In the event that an article is revised and resubmitted, the same reviewers will typically be asked to review the revised manuscript.
Types of paper
Please consider the type of paper you’ve been asked to review and what it aims to achieve.
Data & Policy publishes:
- Original research showing how data science can or is informing policy, using the rigorous methodology expected of an academic paper;
- Policy reports, such as edited working papers or white papers that report findings from international organisations, government agencies and other bodies;
- Replication studies that examine previously published research and attempt to replicate the findings
- Commentaries that discuss issues relating to data science and policy, a recent or anticipated article or study that warrants further explanation, or an overview of an issue relevant to Data & Policy;
Your review
You will be asked to complete your review in the Data & Policy ScholarOne system (https://mc.manuscriptcentral.com/dataandpolicy).
Alongside the standard rating (accept / minor revisions / major revisions / reject) you will be prompted to complete two sections.
In ‘Confidential Comments to Editor‘, you should provide:
- A statement about any conflicts of interest: any financial, professional and personal relationships that have the potential to bias or perceive to bias the review. If none exist, state: ‘None’;
- Any other comments for the editor too sensitive to pass to the author.
In ‘Comments to the Corresponding Author‘, your remarks should include:
- Your summary of the signfiicance of the article, noting what you think is original or interesting, bearing in mind the aims of the article type (e.g. a replication study will not present original findings);
- Your judgement of the overall quality of the paper and its suitability for publication;
- Your evaluation of whether the paper is technically correct and scientifically sound. Note that each research paper should contain a ‘Data Availability Statement’ that makes a declaration about the availability of the underlying data and materials in the interest of transparency and reproducibility;
- An assessment of whether the paper is written clearly and whether its length is appropriate;
- Detailed suggestions for improving the paper, including suggestions about the overall approach and structure of the paper and for additional work that might be required;
Resources
Introductory resources for peer reviewers can be found on Cambridge Core here.
Ethics
Guidance on ethical peer review can be found on Cambridge Core here.
Fast track papers
We invite a small numbers of articles per year to undergo a fast track review process. Typically these are articles that have been presented at a conference and are judged by the editors to be in a sufficiently advanced state to merit this process, or those that engage with an issue important or urgent enough to necessitate rapid assessment.
Reviewers who agree to provide input are expected to do so within a week of acceptance. They should follow the guidelines above, but we do not expect detailed comments on fast track papers. Instead, reviewers should focus on whether the findings are supported by the analysis and whether the article merits publication.
Reviewer Guidelines for Telco Big Data Analytics for Covid-19 articles
The Special Collection of articles on the use of Telco Big Data Analytics for Covid-19 are being assessed through an open peer review process in the interest of transparency. Reviewers with specific expertise for assessing this set of articles were recruited in advance and agreed to take part in this open peer review process.
Reviewers of these articles should note the following:
1. Authors will know who has reviewed their submission. We will publish your review of this and subsequent versions, if the article itself is accepted for publication. The published review will include the content of the review, your name, ORCID, and your Competing Interest statement. It will be published with a DOI.
2. Open peer review does not mean that reviewers should contact authors directly, or that authors should contact reviewers.
3. When writing your review, please avoid using the 'Confidential Comments to Associate Editor' box as this is not within the spirit of the open peer review process.
4. Use the 'Comments to the Author' box to provide your review. Note that the content of your review will be published without an editing process, so it should be written in clear and accurate English. The review should typically contain:
- Your brief summary of the significance of the article, noting what you think is original or interesting;
- Your judgement of the overall quality of the paper and its suitability for publication;
- Your evaluation of whether the paper is technically correct and scientifically sound;
- Detailed suggestions for improving the paper, including suggestions about the overall approach and structure of the paper and for additional work that might be required.
5. Note that you will be asked to provide a Competing Interest statement in the system, which will be published alongside your review. This should detail any competing personal, professional or financial interests that could be perceived as an influence on evaluating the work under review. Example: “Reviewer is employed at company B/owns shares in company D/ is on the Board of company E/is a member of organisation F/ has received grants from company H.” If no Competing Interest exist, please state “Reviewer declares none”.
6. We will ask for your agreement to publish the review under a Creative Commons 4.0 Attribution License.