Guidelines for preparing and reviewing data papers

Before submitting a data paper, authors are advised to contact the managing editor, Marianne PEIFFER (email address: ann.for.sci@nancy.inra.fr), who will handle the manuscript during the whole submission and review process. Marianne will provide any help you need and advise you about the format of the files to be submitted as well as the review procedure. The general information about data papers is available in the instructions to authors.

Please make sure that the manuscript describing the data set contains an explicit dictionary describing the variables and the tables in the database, and clarifies all links between variables and components of the data base. This dictionary will be of great help for potential users of the data base.

The subscription should be made via Editorial Manager, with an adapted procedure, and the review will similarly be submitted via Editorial manager (https://www.editorialmanager.com/afsc/).

GENERAL GUIDELINES FOR REVIEWING DATA PAPERS 

• Confidentiality Please do not show the manuscript to anyone or discuss it, except to solicit assistance with a technical point. If you feel a colleague is more qualified than you to review the data paper, do not pass this responsibility on to that person without first requesting permission via Editorial Manager. Your review and your recommendation should also be considered confidential.
• Time In fairness to the author(s), you should return your review within 3 weeks. If it seems likely that you will be unable to meet this deadline, please e-mail do not accept the job.
• Conflicts of interest If your previous or present connection with the authors, data compilers, or an author’s institution might be construed as creating a conflict of interest, but no actual conflict exists, please discuss this issue in the cover letter that accompanies your review.
• Comments for the authorsshould explicitely answer following questions:What is the major contribution of the data paper? What are its major strengths and weaknesses? Is it suitable for publication? Please include both general and specific comments bearing on these questions, and emphasize your most significant points.

Provide your comments directly in “Reviewer Blind Comments for the Author” displayed in the Editorial Manager’s window or in an attached file in Editorial Manager.

General comments

1. Importance and interest to Annals of Forest Science’ users and readers.
2. Scientific and technical soundness of the database.
3. Originality.
4. Degree to which metadata fully describe the content, context, quality, and structure of the database.

Specific comments

Comment on any of the following matters that significantly affected your assessment of the database:

1. Metadata presentation Are the metadata logically organized and do they follow the Instructions for Authors? Do title, abstract, and key words accurately and consistently reflect the major point(s) of the database? Is the writing concise, easy to follow, interesting?
2. Metadata completeness Are the metadata complete and sufficient to facilitate interpretation and secondary use of the data? What fraction of the metadata should be expanded? Condensed? Deleted?
3. Data organization Are the data logically and consistently organized? Is the data format consistent with the format defined in the template data-set_paper.xlsx? This template for the metadata of the data base (data-set_paper.xlsx) can be downloaded from following address: https://metadata-afs.nancy.inra.fr/ressources
4. Data quality Were suitable methods employed to maintain the integrity of the original data and datasets? Are all data anomalies well-documented? Are the metadata sufficient to allow a secondary user to determine how outliers were identified and treated?
5. Data integrity Have adequate procedures been employed to allow a secondary user to determine whether errors may have been introduced during data transmission (e.g., checksum techniques, file size)?
6. Methods Are they appropriate? Current? Described clearly enough so that the work could be repeated by someone else?
7. Study design Is the design appropriate and correct? Can the reader readily discern which measurements or observations are independent of which other measurements or observations? Are replicates correctly identified? Are significance statements justified?
8. Errors Point out any errors in technique, fact, calculation, interpretation, or style.
9. Citations Are all (and only) relevant references cited?

Fairness and objectivity

If the research premise for the database is flawed, criticize the science, not the scientist. Harsh words in a review will cause the reader to doubt your objectivity; as a result, your criticisms will be rejected, even if they are correct! Comments directed to the authors should demonstrate that:

• You have carefully and thoroughly reviewed the data and metadata.
• Your criticisms are objective and correct, are not merely differences of opinion, and are intended to help the data originator improve his or her data paper.
• You are qualified to provide an expert opinion about the research that served as the impetus for the data paper.

If you fail to win the data originator’s respect and appreciation, your efforts will have been wasted.