Data and reproducibility

1. Introduction

Darmabakti: Jurnal Pengabdian kepada Masyarakat is committed to fostering research that is transparent, robust, and reproducible. We believe that the availability of underlying research data, along with clear descriptions of methodologies (including models, algorithms, and software), is fundamental to the scientific process. It enables verification, promotes collaboration, facilitates new research avenues, and ultimately enhances the credibility and impact of published work. This policy outlines Darmabakti's expectations for authors regarding data sharing, data citation, adherence to reporting guidelines, and the overall reproducibility of their research, in line with the Core Practices of the Committee on Publication Ethics (COPE).

2. Description

  • Research Data: Encompasses any information or materials that were collected, observed, generated, or created to validate original research findings. This can include numerical data, textual data, images, audio-visual recordings, software, code, algorithms, mathematical models, protocols, and methods. For Darmabakti, this particularly relates to data used in developing and testing optimization models, industrial system simulations, ergonomic assessments, and decision-making frameworks.
  • Reproducibility: Refers to the extent to which consistent results can be obtained when an experiment or study is replicated. This may involve using the original authors' data and analytical methods (computational reproducibility) or conducting new studies based on the original methods (empirical reproducibility).
  • Reporting Guidelines: Standardized checklists, flow diagrams, or structured text that guide authors in reporting specific types of research, ensuring completeness and transparency (e.g., guidelines for simulation studies, empirical studies, or systematic reviews).

The benefits of open data and reproducible research practices include increased confidence in research findings, opportunities for data reuse and new discoveries, reduced duplication of effort, enhanced collaboration, and greater public trust in science.

3. Policy

  • Data Availability and Sharing:

    • Darmabakti strongly encourages authors to make all research data, code, mathematical models, algorithms, and other materials necessary to understand, verify, and reproduce their research findings publicly available whenever ethically and legally permissible.
    • Authors are required to include a "Data Availability Statement" in their submitted manuscript, which will be published with the article, detailing how and where the underlying data can be accessed.
    • Acceptable methods for data sharing include deposition in recognized public data repositories, inclusion as supplementary material with the published article, or clear instructions for requesting access under defined conditions.
    • Darmabakti recognizes that some data cannot be shared publicly due to legitimate ethical concerns (e.g., protection of human subject confidentiality if data cannot be fully anonymized), legal restrictions (e.g., proprietary data from industry collaborations), or intellectual property considerations. In such cases, authors must clearly state these restrictions in their Data Availability Statement and provide information on how qualified researchers may request access, if possible.

  • Data Citation:

    • Authors must appropriately cite all datasets (whether their own or those created by others) that are used or generated in their research. Citations should appear both in the main text where the data are discussed and in the reference list.
    • Darmabakti strongly encourages the use of persistent identifiers (e.g., Digital Object Identifiers - DOIs) for cited datasets.

  • Use of Reporting Guidelines:

    • Darmabakti encourages authors to adhere to established reporting guidelines relevant to their specific study design and research area within industrial engineering and systems optimization. This helps ensure the clarity, completeness, and transparency of their research reporting. Authors should consult resources like the EQUATOR Network or specific guidelines recommended for their type of study.

  • Code, Software, Models, and Algorithms:

    • For research involving computational analyses, custom software, specific algorithms, or mathematical models (which are central to Darmabakti's scope), authors are strongly encouraged to make the relevant code, software, models, and algorithms publicly available (e.g., through repositories like GitHub, Zenodo, or institutional repositories).
    • These materials should be sufficiently documented to allow other researchers to understand, implement, validate, and build upon them. They should also be appropriately cited in the manuscript.

  • Reproducibility of Results:

    • Authors bear the primary responsibility for ensuring that their methods, data, and any associated materials are described with sufficient detail and clarity to allow other researchers to attempt to reproduce the reported findings.
    • Darmabakti may encourage or require the submission of materials that facilitate reproducibility, such as computational notebooks (e.g., Jupyter), detailed pseudocode, or scripts.

  • Data Integrity and Retention:

    • Authors are expected to maintain the original research data and related documentation for a reasonable period after publication (e.g., 5-10 years, or as per institutional/funder requirements) and to provide access to this data upon reasonable request from the journal, reviewers, or readers, subject to ethical, legal, and confidentiality constraints.
    • Responsible data management practices should be employed throughout the research lifecycle.

  • Registration of Studies (if applicable):

    • While less common for all study types in Darmabakti's scope, for certain research designs such as systematic reviews (e.g., registration in PROSPERO) or prospectively planned simulation studies, pre-registration in a publicly accessible registry is encouraged to enhance transparency and reduce publication bias.

4. Technicalities to Achieve and Materialise the Policies

  • Data Availability Statement (DAS):

    • A DAS is a mandatory component of all research articles submitted to Darmabakti. This statement must be included in the manuscript (e.g., after the Conclusions section or before the References).
    • The DAS should clearly explain how and where the data supporting the reported results can be found. Examples include:
      • "The data presented in this study are openly available in [Repository Name] at [DOI/URL/Accession Number]."
      • "The data supporting the findings of this study are available as Supplementary Material with this article."
      • "The data that support the findings of this study are available from the corresponding author upon reasonable request, subject to [specify any conditions, e.g., a data sharing agreement, ethical approvals]."
      • "Data sharing is not applicable to this article as no new data were created or analyzed in this study (e.g., for a review or conceptual paper)."
      • "The data that support the findings of this study are subject to [restrictions, e.g., privacy, proprietary rights]. De-identified data may be available from [contact point] for researchers who meet the criteria for access to confidential data."

  • Selection of Data Repositories:

    • Darmabakti recommends that authors deposit their data in recognized, trusted, and preferably community-endorsed public repositories that ensure long-term preservation and access, and assign persistent identifiers (e.g., DOIs). Examples include Zenodo, Figshare, Dryad, OSF, institutional repositories, or discipline-specific repositories relevant to engineering or computational sciences.

  • Formatting and Documentation of Data, Code, and Models:

    • Shared data should be well-organized, in commonly used and preferably open formats, and accompanied by clear documentation (e.g., a README file, data dictionary, codebook) explaining the data structure, variables, units, and any necessary context for interpretation and reuse.
    • Code and software should be commented and include information on dependencies, versions, and how to run the code. Models and algorithms should be described with sufficient mathematical and procedural detail.

  • Citing Data, Code, Software, and Models:

    • These research outputs should be formally cited in the reference list, similar to other scholarly publications. Citations should include, where available: author(s)/creator(s), title, year of publication/creation, repository name, version number, and a persistent identifier (e.g., DOI or direct URL).

  • Peer Review Considerations:

    • Peer reviewers will be encouraged to consider the availability and adequacy of the data and methods described for enabling reproducibility.
    • Where data and code are shared, reviewers may be invited to access and assess these materials as part of their review, if feasible and appropriate for their expertise.
    • Reviewers will also assess the clarity and completeness of the Data Availability Statement.

  • Guidance on Reporting Guidelines:

    • Darmabakti's "Instructions for Authors" will provide links to relevant resources for reporting guidelines, such as the EQUATOR Network, and encourage authors to consult guidelines specific to their methodology (e.g., for simulation studies, empirical research, algorithm development).

  • Post-Publication Data Issues:

    • If concerns are raised after publication regarding the availability, integrity, or interpretation of data, or the reproducibility of the research, Darmabakti will investigate these issues following COPE guidelines. This may involve contacting the authors for clarification, requesting access to underlying data, or, if necessary, publishing a correction, expression of concern, or retraction.

  • Exceptions and Embargoes:

    • Authors who are unable to share their data publicly due to compelling ethical, legal, or confidentiality reasons must clearly explain these restrictions in their Data Availability Statement at the time of submission. The journal will consider such exceptions on a case-by-case basis.
    • If data are subject to an embargo period before public release (e.g., to allow authors time to file patents), this should also be stated and justified in the DAS.

Darmabakti believes that adherence to these principles of data sharing and reproducibility will significantly contribute to the quality and impact of research in industrial engineering and systems optimization.

COPE resources