Daily life in the Open Biologist's second job, as a Data Curator.

Area of Science:

• Life Sciences
• Biological Research
• Data Science

Background:

• Data reusability is vital for the research data lifecycle, yet practical implementation remains challenging.
• Publicly shared datasets are often incomplete or not reusable, hindering scientific progress.
• Achieving FAIR (Findable, Accessible, Interoperable, Reusable) data principles faces obstacles in biology due to diverse data types and lack of standardized practices.

Purpose of the Study:

• To provide experimental researchers with practical strategies for managing and sharing reusable datasets.
• To bridge the gap between data generation and data sharing for publication authors.
• To simplify research data management and enhance data visibility and impact.

Main Methods:

• Working directly with experimental researchers to understand their data management needs.
• Detailing processes for organizing datasets from creation through to sharing.
• Recommending tools, strategies, and web resources for maximizing data reusability and productivity.

Main Results:

• A simplified approach to research data management challenges for experimentalists.
• Enhanced data visibility, recognition, and impact through improved data sharing.
• Practical examples and resources to facilitate FAIR data implementation.

Conclusions:

• The proposed strategy simplifies data management for experimental researchers.
• This approach promotes FAIR data sharing, benefiting the broader scientific community.
• Effective data management enhances research visibility and scientific impact.