Policy

Data & Reproducibility Policy

SIARE (Society of Integrated Academic Research and Education), through AcademicProceeding.org, supports transparent, trustworthy, and reproducible scholarship. Authors are expected to retain, document, and, where appropriate, share the data, materials, methods, software, and supporting resources needed to understand and verify published research.

This policy outlines expectations relating to data availability, reproducibility, documentation, repositories, justified restrictions, and post-publication verification.

Core Expectations
  • Clear Data Availability Statement
  • Documented methods and workflows
  • Appropriate sharing of data and code
  • Transparent explanation of restrictions

Data Availability

Authors should clearly state whether supporting data are open, restricted, available on request, or not applicable.

Reproducibility

Methods, code, workflows, and supporting materials should allow meaningful verification of the research.

Responsible Sharing

Sharing should be encouraged wherever possible, while respecting privacy, ethics, confidentiality, and law.

Editorial Integrity

Editors may request clarification or supporting files where reproducibility or data-access concerns arise.

1

Purpose and Principles

SIARE encourages research practices that improve reliability, verification, scholarly reuse, and confidence in the published record.

Authors should provide enough detail, documentation, and supporting evidence for editors, reviewers, and readers to understand how findings were produced and to assess whether the work can be reasonably verified or reproduced.

Reproducibility does not always require unrestricted public release of every file, but it does require honest, sufficient, and transparent reporting of what is available, what is restricted, and why.
2

Supporting Research Outputs Covered by this Policy

Supporting outputs may vary by discipline, but can include any material necessary to understand, verify, or build upon the published research.

Data & Evidence

  • Raw and processed datasets
  • Survey responses and measurement outputs
  • Derived tables and analytical files
  • Supporting evidence used in conclusions

Methods & Materials

  • Protocols and procedures
  • Instruments, questionnaires, or forms
  • Experimental or analytical setup details
  • Supplementary methodological appendices

Code & Computational Workflows

  • Software scripts and source code
  • Notebooks and computational pipelines
  • Model settings and dependencies
  • Simulation and algorithmic files

Supporting Media

  • Figures and source files
  • Images, audio, video, or annotations
  • Repository packages and metadata files
  • Other supplementary materials
3

Data Availability Statement

Original research submissions should include a clear statement explaining whether and how supporting data or materials can be accessed.

The Data Availability Statement should identify whether supporting materials are publicly available, available on reasonable request, available under restricted access, not shareable for justified reasons, or not applicable because no new data were generated.

Examples of Data Availability Statements

  • “The data supporting this study are publicly available in a repository at the cited DOI or link.”
  • “The datasets generated during this study are available from the corresponding author on reasonable request.”
  • “The data are not publicly available because they contain confidential or sensitive information.”
  • “No new data were generated or analyzed in support of this work.”
4

Core Reproducibility Expectations

Reproducibility is strengthened when the manuscript explains clearly how the research was conducted.

4.1 Methods and Procedures
  • Describe study design, sampling, and analytical procedures clearly
  • Identify variables, instruments, and decision points transparently
  • State limitations or assumptions that affect interpretation
4.2 Data Processing and Analysis
  • Explain preprocessing, exclusions, transformations, or cleaning steps
  • Describe how results were derived from the underlying data
  • Clarify how missing values, outliers, or abnormal cases were handled
4.3 Software, Code, and Tools
  • Identify software, versions, packages, and dependencies where relevant
  • Share scripts or notebooks when they materially support the results
  • Document model parameters, settings, and computational assumptions
4.4 Documentation and Metadata
  • Use understandable file names, labels, and folder structures
  • Include explanatory documentation where needed
  • Define abbreviations, coding schemes, and variable names clearly
5

Sharing, Repositories, and Citation

Authors are encouraged to use trusted repositories and provide stable access details wherever appropriate.

  • Use discipline-appropriate, institutional, or general trusted repositories
  • Prefer repository records with DOI, accession number, or permanent link
  • Cite datasets, code, and repositories where they materially support the article
  • Ensure deposited files are organized, understandable, and complete enough for review or reuse
6

Restrictions and Legitimate Limits

Not all data can be openly shared. Restrictions may be justified where privacy, consent, confidentiality, licensing, law, or safety concerns apply.

Examples of Legitimate Restrictions

  • Personal or identifiable participant data
  • Commercially confidential or proprietary material
  • Licensed or third-party restricted content
  • Legal or regulatory constraints

What Authors Should Do

  • Explain the restriction clearly in the manuscript
  • State whether restricted or mediated access is possible
  • Avoid vague claims such as “data unavailable” without explanation
  • Protect ethical and legal obligations first
7

Author Responsibilities

Authors are responsible for the integrity, availability, and documentation of the supporting evidence behind their published work.

  • Retain underlying records and supporting files for an appropriate period
  • Ensure Data Availability Statements are accurate and complete
  • Be prepared to clarify methods, data, or code if editorial questions arise
  • Disclose any restrictions honestly and at the time of submission
8

Editorial Review and Post-Publication Concerns

Editors and reviewers may raise concerns about missing data, insufficient documentation, inaccessible supporting files, or inconsistencies between evidence and reported findings.

During peer review or editorial assessment, SIARE may request clarification, supporting files, repository evidence, or additional documentation. If significant concerns are identified after publication, the journal may pursue correction, clarification, or other post-publication action as appropriate.

Transparency is expected both before and after publication. Where reproducibility limitations exist, authors should disclose them clearly rather than allowing ambiguity in the scholarly record.
Need Assistance?

Contact for Data & Reproducibility Queries

For questions relating to data availability, reproducibility expectations, repositories, or supporting materials, please contact:

Email [email protected]
Email [email protected]
Email [email protected]