The evaluation of fingermarks given activity level propositions.

Area of Science:

• Forensic Science
• Friction Ridge Analysis

Background:

• Fingermarks are crucial for identifying individuals in criminal cases.
• Courtroom inquiries increasingly focus on the deposition process of fingermarks, not just their source.

Purpose of the Study:

• To explore the evaluation of fingermarks using Bayesian networks for activity level propositions.
• To identify and discuss variables relevant to understanding fingermark deposition.

Main Methods:

• Utilized Bayesian networks to model the relationships between variables.
• Identified key variables including transfer, persistency, recovery, background marks, location, direction, skin area, and pressure distortions.
• Applied the methodology to three case examples.

Main Results:

• Demonstrated the application of Bayesian networks in evaluating fingermarks for activity level.
• Highlighted the importance of specific variables in reconstructing fingermark deposition events.

Conclusions:

• Bayesian networks provide a robust framework for assessing activity level propositions related to fingermarks.
• The identified variables are informative for understanding the 'how' behind fingermark presence.