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AMA Journals Research Transparency Policy | Dataverse Submission Instructions

AMA Journals Research Transparency Policy | Dataverse Submission Instructions

AMA Journals

When you submit the revision of your conditionally accepted manuscript to ScholarOne, you must also submit all data, code, and methodological materials to the journal’s Dataverse collection per the AMA Journals Research Transparency Policy. Please email journals@ama.org (including the journal name and ScholarOne manuscript ID) with any questions.

Preparing Your Materials

Before uploading files to the journal’s Dataverse collection, clearly name all files and organize them into folders and subfolders for each study in your paper, then compress the folders into one zip file. Dataverse will maintain the folder structure of the zip file to ensure your files are organized appropriately.

All submissions must include

  1. A README file that includes (for examples, download Example README File for a Quantitative Paper and download Example README File for an Experimental Paper):
    • A list of all file names with brief descriptions.
    • Clear instructions for replicating the results reported in the manuscript using the data, code, and other methodological materials provided by the authors.
      • If the research relies on data sourced from licensed databases (e.g., Census Bureau, Compustat, CRSP, Factset, WRDS), include detailed instructions for accessing and linking to licensed data sufficient for replication.
      • If multiple sources of data were combined, describe how intermediate datasets were combined to create the final dataset.
      • If no scripts or code were used to collect or analyze the data, identify the analysis tools and procedures used so that an informed reader can replicate the analysis.
    • A description of computing resources required to replicate the results (adapted from Social Science Data Editors Template README):
      • Identify all software, including version numbers, used to conduct the analyses for each study.
      • Describe computer hardware used by the authors (operating system, CPU, memory and disk space). If multiple computers were used in parallel to conduct the analyses, please provide the specification for each computer.
      • If more than 5 minutes are required to run any of the analyses, please provide the estimated time required to run the analyses.
  2. Any scripts or code used to collect or analyze the data.
  3. If primary data were collected (e.g., surveys, experiments, field studies, web scraping), the raw data analyzed for all quantitative results reported in the paper (e.g., as qsf, Excel, ASCII, or text files).
  4. If the paper is based on qualitative data (e.g., interviews, participant observation, textual datasets, or other cultural, archival, or historical material), any information, files, or materials necessary to replicate the results that are not included in the main document or web appendix, such as a sufficient number of transcribed interviews annotated to illustrate the process by which themes or categories were identified.
  5. Any additional files or methodological materials required to replicate the results reported in the paper.

If your data or code files are already publicly available on another trusted repository (Harvard Dataverse, OSF, Zenodo, Figshare), you do not have to reupload all the files. Your submission must include

  • A README file that meets the requirements outlined above.
  • The permanent link (i.e., not “view only” or anonymized for review) to your dataset in your submission’s metadata (for details, see Step 8, Submitting Your Materials).

If you proposed an alternative disclosure plan at initial submission, your submission must include

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Submitting Your Materials to Dataverse

  1. Log in to an existing Dataverse account or sign up for one at dataverse.harvard.edu.
  2. Navigate to the journal’s Dataverse collection:
  3. Select the Add Data button on the journal’s Dataverse and choose New Dataset.
    Note: There are two Add Data buttons. Select the button that is lower on the page and located within the journal’s Dataverse, which is outlined in the following screenshot.
    Screenshot of JMR's Dataverse collection page showing two Add Data buttons as described in Step 3 of the submission instructions on this page. The correct button (located within JMR's Dataverse, later on the page) is outlined in green.
  4. Ensure the Host Dataverse is the journal’s name (e.g., “Journal of Marketing Research” in the following screenshot). Screenshot of the Host Dataverse metadata field with Journal of Marketing Research listed as the host Dataverse, as described in Item 4 of the submission steps on this page.
  5. Enter metadata to describe your dataset (fields marked with an asterisk are required):
    • Title*: Select Add “Replication Data for” to Title and enter the title as it appears on ScholarOne.
    • Other Identifier*: Enter the manuscript ID from ScholarOne in the “Identifier” field (e.g., JMR-23-0001.R3, JNM-23-0115.R2, JPPM-25-004.R3).
    • Author*: Use the + button to add fields and enter all author names and affiliations. You may also add identifiers such as ORCIDs.
    • Point of Contact*: Enter the name, affiliation, and email of the corresponding author and/or the author to contact about the dataset.
    • Description*: Describe the purpose, nature, and scope of the dataset. If you proposed an alternative disclosure plan at initial submission, indicate that here.
    • Subject*: Select the relevant subjects.
    • Keyword: Enter relevant keywords.
    • Related Publication: Enter information about other publications that use this dataset.
    • Notes: Enter any additional notes about the dataset.
    • Software*: Use the + button to add fields and enter the name and version number of all software and packages used.
  6. Add files
    • Select or drag and drop the compressed zip file containing all of your files. Dataverse will unpack the zip file and maintain the folder structure.
    • Select or drag and drop any additional files or folders to upload them.
    • Edit the file name and enter a brief description.
      Note: File names, paths, and descriptions will be public, even if the file itself is restricted, so please do not include any confidential information in the file names (e.g., the name of a company).
    • Organize your files by adding or editing the File Path (for more information, see “File Path” section in the Dataverse User Guide).
    • Add tags or provenance information by selecting the three vertical dots.
  7. Select Save Dataset.
  8. On the next screen, select the Metadata tab, then select Add + Edit Metadata and add any additional information about your dataset (only fields marked with an asterisk are required). Select Save Changes when you are done.
    If your dataset, files, or code are publicly available on another trusted repository (Harvard Dataverse, OSF, Zenodo, Figshare), enter the permanent link (i.e., not “view only” or anonymized for review) in the Alternative URL field. You may add additional links or information in the Description field.
  9. Select the Terms tab, then select Edit Terms Requirements to specify the license and terms of use for your dataset and files (for help selecting a license, see Creative Commons License Chooser).
  10. To add, edit, or delete files, select the Files tab.
  11. When you are ready for the journal to review your dataset, select Submit for Review.
    Note: If the license and Terms of Use in the popup window are not updated or correct, go back to the Terms tab to update the license and Terms of Use before submitting.
  12. An Editor or Admin will return the dataset to you if any corrections are required. You will receive an email with more information if this is necessary.
  13. After your manuscript is unconditionally accepted and published, the journal will publish your dataset and you will receive an email notification.
    Note: All of your files will be restricted before they are published, so they will still only be accessible to the Editor in Chief and AMA staff. After your dataset has been published, you may unrestrict files to make them public (see Making Your Materials Public).

Editing Your Materials After Submission

If you need to edit your files or metadata (dataset description) after you have submitted your dataset for review, please email journals@ama.org (including the journal name and ScholarOne manuscript ID) and ask that the dataset be returned to you.

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Editing Your Materials After Publication

If you need to edit your files or metadata (dataset description) after the dataset has been published:

  1. Log into your Harvard Dataverse account.
  2. Select your account name on the top right and choose My Data.
  3. Select your dataset title.
  4. Select Edit, then Files (Upload) or Metadata.
  5. When you are done making changes, select Save Changes.
  6. Make sure you’re on the dataset page and select Submit for Review to submit a new version of your dataset. The journal will be notified about your changes.

Making Your Materials Public

If you would like to make some or all of your files public after publication:

  1. Log into your Harvard Dataverse account.
  2. Select your account name on the top right and choose My Data.
  3. Select your dataset title.
  4. Under Files, select the files you would like to make public.
  5. Select Edit Files and choose Unrestrict.
  6. When you are done, select Submit for Review to submit a new version of your dataset. The journal will be notified about your changes.

You may add the DOI link to your final, published article during copy editing.

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Additional Resources and Examples

Download Example README File for Experimental Paper
Download Example README File for Quantitative Paper
Download Sample Alternative Disclosure Plan – NDA

JMR Research Transparency Policy Workshop Video and Slides

Harvard Dataverse: Getting Started
Dataverse User Guide
Dataverse Best Practices: Replication Dataset Guidelines

Back to AMA Journals Research Transparency Policy

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