This policy outlines our commitment to enhancing data transparency through various measures such as data citation, analysis code transparency, materials transparency, reporting guidelines, preregistration, replication, registered reports, publication bias, and open science badges.
Authors must provide proper citations for all data sources used in their research, allowing readers to access and verify the data. Data citations should follow standard citation styles and include relevant metadata to ensure accurate identification and retrieval. Check our policy related to Citation style.
Authors are encouraged to share all relevant research data to promote transparency and enable the reproducibility of their findings. Transparently shared data should be deposited in reputable, publicly accessible repositories or platforms. All related data must be archived in a permanent server and linked to the manuscript via Data Availability section.
This section emphasizes the authors' need to provide accessible access to the analysis code used in their study. This transparency enables other researchers to validate and reproduce the analysis, promoting the reliability and accountability of scientific research.
The shared analysis code should be presented in a clear and organized manner to facilitate understanding and reuse by others. The importance of clarity and organization cannot be overstated, as it expedites comprehension and ensures that fellow researchers can effectively comprehend and reuse the analysis.
Furthermore, providing comprehensive documentation alongside the analysis code, outlining each analysis stage, algorithm usage, and result interpretation, is essential.
Using standard formats and ensuring compatibility eases the process for others to open and work with the analysis code without significant obstacles. Commitment to maintaining and updating the analysis code as needed, including bug fixes and addressing queries from other researchers, is equally crucial. This transparency regarding code maintenance ensures that the code remains relevant, accurate, and useful over time.
Authors should provide detailed information about the materials used in their study, including instruments, questionnaires, or other tools. If feasible and appropriate, authors should share digital versions or detailed descriptions of materials to enhance replicability.
Authors must adhere to established reporting guidelines relevant to their study design and analysis methodology (e.g., CONSORT, PRISMA, STROBE). Check our standard of reporting policy. Compliance with reporting guidelines ensures comprehensive and standardized reporting, aiding readers and reviewers.
Authors are encouraged to preregister their studies and analysis plans to enhance transparency and reduce bias in reporting results.
Preregistration involves documenting the study design, methodology, data collection, and analysis techniques in advance, essentially setting a predefined path for the research process. By doing so, researchers establish a clear record of their intentions, making it easier to differentiate between confirmatory analyses, which validate pre-existing hypotheses, and exploratory analyses, which involve examining patterns or trends in the data.
This differentiation is essential as it helps maintain the integrity of the research process and offers valuable insights into the reliability of the study's findings.
Replication is a fundamental aspect of the scientific process promoted by ETFLIN, encouraging researchers to conduct replication studies to validate and confirm previous research findings.
Replication involves the rigorous duplication of a study's methodology and analysis to independently assess and verify the original results.
This practice is crucial in establishing the reliability and robustness of research findings, as it helps identify if the initial results can be consistently reproduced under similar conditions.
Replication studies should meticulously adhere to rigorous methodologies, ensuring the approach closely mirrors the original study's design. Furthermore, it's essential for replication studies to be transparently reported, regardless of the outcome. Transparent reporting provides a clear account of the replication process, detailing any deviations from the original methodology and providing insights into potential factors influencing the results.
Also, read our policy related to Plagiarism.
ETFLIN supports the submission of registered reports, allowing for peer review and acceptance based on study design and methodology before data collection. We are committed to mitigating publication bias by considering the importance of the research question and the quality of the study rather than the results.
ETFLIN employs open science badges to recognize and incentivize open research practices. Badges are awarded based on adherence to various transparency measures, promoting a culture of openness within the scientific community.
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