The dry lab microscopist or prompt microscopist: do we need them?

Area of Science:

• Biological microscopy
• Data science
• Bioinformatics

Background:

• Modern biological microscopy generates vast and complex datasets.
• Traditional microscopy approaches are insufficient for managing big data challenges.
• The increasing volume and complexity of microscopy data require specialized support.

Purpose of the Study:

• To highlight the urgent need for specialized data management roles in biological microscopy.
• To define the skills and responsibilities of "dry lab microscopists".
• To emphasize the importance of integrating data experts into research institutions.

Main Methods:

• Analysis of current trends in biological microscopy data generation.
• Identification of skill gaps in traditional microscopy support.
• Review of job market demands for data management specialists.

Main Results:

• A significant gap exists between data generation and data management capabilities in microscopy.
• The demand for "dry lab microscopists" with expertise in data management, software interoperability, and AI is rising.
• Job markets indicate a need for dedicated training programs for these specialists.

Conclusions:

• Integrating "dry lab microscopists" is essential for addressing digital data challenges in biological research.
• These specialists are crucial for maintaining data integrity and advancing research in the data-driven era.
• Dedicated training programs are necessary to equip researchers with essential data management skills.