10-Data Sharing Policy

10.1   Data Sharing

As part of its commitment to transparency, academic rigor, and reproducibility, the Business & Economic Review (BER) encourages and, in some cases, requires authors to share the data underpinning their published research. The Data Sharing Policy outlines the expectations, procedures, and ethical responsibilities related to research data submitted to or published in BER. It applies to all manuscript types that include empirical analysis or generate original datasets.

10.2  Policy Objectives

The primary objectives of this policy are to:

  • Promote research transparency and accountability
  • Enable reproducibility and validation of results
  • Encourage reuse and reanalysis of data for new discoveries
  • Align with the FAIR Data Principles:
    • Findable, Accessible, Interoperable, and Reusable
  • Comply with funder, institutional, and international mandates on data availability

10.3    Scope of the Policy

This policy applies to:

  • All empirical research articles submitted to BER
  • Authors whose research relies on:
    • Quantitative or qualitative datasets
    • Survey or interview data
    • Economic indicators or financial reports
    • Simulation data
    • Proprietary or open-access databases

Authors of theoretical, conceptual, or review articles are exempt from data deposit but are encouraged to cite relevant data sources where applicable.

10.4    Types of Data Covered

This policy encompasses a wide range of research data, including:

  • Raw data (e.g., numerical datasets, audio files, video recordings)
  • Processed data (e.g., cleaned or normalized datasets)
  • Derived data (e.g., econometric models, indicators)
  • Supplementary material (e.g., codebooks, interview transcripts, survey instruments)
  • Analytical tools or code (e.g., R scripts, Python code, Stata .do files)

10.5    Data Availability Statement (DAS)

A Data Availability Statement must be included in the submission and clearly indicate:

  • Whether data is publicly available
  • The repository name and persistent link (e.g., DOI)
  • Access conditions or restrictions (if applicable)
  • Contact information for obtaining restricted data (if not public)
  • Reasons for any exceptions to data sharing (e.g., privacy, security)

Example DAS Formats

  • Public Data:

“The dataset generated and analyzed during this study is publicly available in the Harvard Dataverse repository at https://doi.org/10.7910/DVN/XXXXXX.”

  • Restricted Data:

“The data supporting the findings of this study are available from [name], but restrictions apply due to commercial sensitivity, and are not publicly available.”

  • No Data:

“This study did not generate any new data.”

10.6    Ethical and Legal Considerations

BER recognizes that some data cannot be openly shared due to:

  • Confidentiality agreements
  • Privacy laws (e.g., GDPR, HIPAA)
  • Commercial sensitivity
  • National security or intellectual property concerns

In such cases, authors must:

  • Provide justification for non-disclosure
  • Share anonymized or aggregated data if possible
  • Offer a redacted dataset or synthetic data
  • Ensure that informed consent included permission for data sharing, where applicable

10.7    Code and Analytical Tools

In addition to datasets, authors are encouraged to share:

  • Analysis scripts, code, or macros used to generate findings
  • Software environments (e.g., R, Python packages)
  • Detailed replication instructions

10.8    Review and Verification of Data

10.8.1 Editorial Assessment

During peer review and editorial processing:

  • Editors verify that the Data Availability Statement is included
  • Reviewers may be asked to assess the clarity and sufficiency of the data and its availability
  • In rare cases, reviewers may be granted access to private datasets under strict confidentiality

10.8.2 Post-Publication Audits

BER may conduct random audits or respond to complaints about data accessibility post-publication. If data is found to be unavailable or falsified:

  • A correction, expression of concern, or retraction may be issued

10.9    Exceptions to Data Sharing

BER acknowledges that in specific cases, open data sharing may not be feasible. Valid exceptions include:

  • Legal restrictions or court orders
  • Human subject data without proper consent
  • Proprietary data under license or trade secrets

Authors must explain any such restrictions clearly in the Data Availability Statement. Editors may request documentation to verify such claims.

10.10    Data Citation Practices

Authors should cite datasets using standard referencing formats, including:

  • Author(s)
  • Year
  • Title of dataset
  • Repository name
  • Version
  • DOI or persistent URL

Example Data Citation:

Smith, J. (2023). Consumer Behavior Survey Data [Dataset]. Harvard Dataverse. https://doi.org/10.7910/DVN/ABC123

Data citations must appear in both:

  • The main reference lists
  • The Data Availability Statement

10.11   Benefits of Data Sharing

BER encourages data sharing due to its benefits for:

  • Researchers: Increases citation, credibility, and collaborative opportunities
  • Reviewers: Facilitates deeper evaluation of methodological rigor
  • Readers: Enhances transparency and understanding
  • Policy Makers and Practitioners: Enables evidence-based decision-making
  • The Public: Ensures public access to publicly funded research.

    10.12  Enforcement and Non-Compliance

Failure to comply with the data sharing policy may result in:

  • Manuscript rejection
  • Delayed publication
  • Retraction of published articles
  • Reporting to funders or institutions (in case of serious ethical violations)

Authors are responsible for ensuring that their data availability commitments are fulfilled post-publication.

10.13   Policy Review and Updates

This Data Sharing Policy is reviewed every two years, or sooner if:

  • New ethical, legal, or technical standards emerge
  • Funder mandates change
  • Open science practices evolve

All changes will be published on BER’s website and reflected in the Author Guidelines and Submission Portal