Establishing the most appropriate databases for addressing source level propositions

Area of Science:

• Forensic Science
• Probability Theory
• Evidence Interpretation

Background:

• The Case Assessment and Interpretation (CAI) project has been developed over several years within the Forensic Science Service (FSS).
• The CAI model's principles, refined through casework, offer a balanced, robust, and logical framework for evidence interpretation.
• A frequent challenge in forensic interpretation is identifying the most suitable database for assigning probability values to evidence.

Purpose of the Study:

• To present guidelines for selecting appropriate databases in forensic interpretation.
• To illustrate the application of these guidelines using various case examples.
• To enhance the robustness and logical consistency of forensic probability assignments.

Main Methods:

• Development of a set of guidelines presented as flowcharts.
• Application and exploration of these guidelines within a diverse range of forensic case examples.
• Review of principles underpinning the Case Assessment and Interpretation (CAI) model.

Main Results:

• A structured approach to database selection for forensic probability assessment has been developed.
• Flowchart-based guidelines are provided to assist practitioners in this selection process.
• The practical utility of the guidelines is demonstrated through detailed case examples.

Conclusions:

• The developed guidelines offer a systematic method for choosing appropriate databases in forensic casework.
• Implementing these guidelines can improve the consistency and validity of probability assignments in forensic interpretation.
• The CAI model's principles are foundational to achieving a balanced and logical approach to forensic evidence evaluation.