Rapid character scoring and tabulation of large leaf-image libraries using Adobe Bridge.

Area of Science:

• Paleobotany
• Digital specimen research

Background:

• Digital image libraries are crucial for specimen-based research.
• Current methods for coding and extracting metadata are complex and often require downsampling or platform switching.
• Existing workflows lack direct links between character data and images.

Purpose of the Study:

• To demonstrate a method for coding and embedding standard paleobotanical characters into digital images.
• To provide a workflow that links character data directly to full-resolution images.
• To offer an intuitive digital tool that complements in-person specimen analysis.

Main Methods:

• Coding standard leaf architecture and insect-damage characters into images.
• Utilizing Adobe Bridge for applying customizable and searchable keywords directly to images.
• Employing scripts for reversible data extraction and matrix formatting.

Main Results:

• Keywords are applied directly and reversibly to individual full-resolution images.
• Data can be extracted and formatted into a matrix using scripts.
• The method is intuitive and acts as a digital mimic of in-person specimen analysis.

Conclusions:

• The developed approach simplifies the coding and extraction of specimen metadata.
• Keywords can be customized for various data types requiring visual sorting.
• This method enhances the utility of digital image libraries for specimen-based research.