Reproducibility in ecology and evolution: Minimum standards for data and code

Area of Science:

• Data Science
• Scientific Publishing
• Research Integrity

Background:

• Open data archiving is crucial for scientific transparency and reproducibility.
• Current data archiving practices lack standardization, hindering accessibility and reuse.
• Lack of clear guidelines impedes the acknowledgment of data contributions.

Purpose of the Study:

• To advocate for mandatory open data archiving policies in scientific journals.
• To propose standardized, user-friendly formats for data archiving.
• To highlight the benefits of open data for scientific progress and researcher recognition.

Main Methods:

• This study presents a call to action based on current challenges in data accessibility.
• It emphasizes the need for journal commitment to specific data archiving standards.
• The proposal is grounded in principles of open science and FAIR data.

Main Results:

• Consistent application of open data archiving requirements is proposed.
• Standardized formats will enhance data understandability and usability for readers.
• Clear policies will enable citation of open data, ensuring contributor acknowledgment.

Conclusions:

• Mandatory, standardized open data archiving by journals will significantly improve scientific research.
• Implementing these requirements will foster a culture of data sharing and reuse.
• This initiative aims to accelerate scientific discovery through enhanced data accessibility and proper attribution.