Data and Reproducibility

 

The Journal of Decision Support Systems and Multi-Criteria Decision Making (JODESMA) encourages responsible data availability and research reproducibility. Authors should provide sufficient information about the research design, data sources, analytical procedures, computational methods, and evaluation processes to enable readers to understand how the reported findings were produced.

Data Availability

Authors are expected to:

  • State whether the supporting research data are available.
  • Provide repository details or access information when appropriate.
  • Explain any restrictions that prevent data from being shared publicly.
  • Protect personal, confidential, proprietary, or sensitive information.
  • Ensure that shared data are accompanied by sufficient documentation to support interpretation and reuse.
Computational Reproducibility

To support the verification and reproduction of computational research, authors should:

  • Describe algorithms and analytical procedures in sufficient detail.
  • Report important parameters, experimental settings, and implementation details.
  • Identify relevant software, libraries, tools, and computational environments.
  • Describe the datasets used and the procedures applied for data preprocessing.
  • Report evaluation metrics, validation procedures, and relevant experimental conditions.
  • Provide source code or supplementary materials when appropriate and legally permissible.
Transparency and Disclosure of Limitations

Authors should not omit methodological information necessary to understand or evaluate the validity of their reported findings. Where complete reproducibility is not possible because of confidentiality requirements, proprietary restrictions, unavailable historical data, or other legitimate limitations, these limitations should be clearly disclosed. Authors should explain the nature of the restrictions and, where feasible, indicate how readers may obtain additional information or verify the reported results.