Digital/Multimedia Scientific Area Committee

The Digital/Multimedia Scientific Area Committee (SAC) provides strategic direction, serves as a platform to integrate similar standards activities across multiple forensic science disciplines, and manages the activities of the following subcommittees:

Members

Lora Sims, SAC Chair, Ideal Innovations, Inc.

Matthew Graves, SAC Vice Chair, U.S. Army Criminal Investigation Laboratory

William Eber, Digital Evidence Subcommittee Chair, Self-employed

Krystal Howard, Facial & Iris Identification Subcommittee Chair, Michigan Department of State – Office of Investigative Services

Christina Malone, Video/Imaging Technology and Analysis Subcommittee Chair, U.S. Army Criminal Investigation Laboratory

Colin Bellair, Travis County District Attorney's Office (legal representative)

John Ellis, Law Offices of John C. Ellis, Jr., Inc. (legal representative)

Abhyuday Mandal, University of Georgia (statistics representative)

Lawrence Potier, Federal Bureau of Investigation (quality representative)

Interlaboratory Comparison

The Digital/Multimedia SAC, Facial & Iris Identification, and Video/Imaging Technology Analysis Subcommittees collaborated with North Carolina State University to conduct a global interlaboratory study exercise evaluating OSAC Proposed Standard 2022-S-0001, Standard Guide for Image Comparisons. The proposed standard is currently on the OSAC Registry.
- The published results of the Interlaboratory Study: Assessing the consistency and accuracy for determining source of face, hands, and clothing images across forensic practitioners and laypersons are published.
- The publication is available as open access through the Journal of Forensic Sciences: https://onlinelibrary.wiley.com/doi/10.1111/1556-4029.70368
- Highlights of the study:
  - OSAC proposed standard 2022-S-0001 details five opinion categories for determining the image source.
  - Forensic practitioners and laypersons were recruited to assess the technical soundness of 2022-S-0001.
  - Participants were given face, hand, or clothing images and determined the source using 2022-S-0001.
  - Practitioners were statistically more accurate at determining the true source of face and hands images over laypersons.
  - Practitioners had statistically higher agreement than laypersons for face, hand, and clothing images.