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Just Using Inadvertently Photographed Ridge Detail As Evidence
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Manage episode 451465752 series 1433931
Content provided by Just Science and RTI International. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Just Science and RTI International or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
In episode two of our Case Studies season, Just Science sat down with Tim Fayle, Training Capability Lead for IDEMIA Australasia and Chair of the International Association for Identification’s Latent Print Certification Board, to discuss the utility of friction ridge detail inadvertently captured via photographs as a valuable and potentially underutilized type of evidence within a variety of case types. While the use of latent fingerprints recovered from crime scenes has been established as an important type of forensic evidence for decades, the increasingly widespread use of social media and other digital platforms has contributed to even more opportunities to garner friction ridge detail evidence following a crime. Practitioners and researchers alike have demonstrated the value of utilizing photographs presenting inadvertently captured finger and palm friction ridge detail – obtained via social media posts, other digital forums, and cellphone data – to identify perpetrators and help bring justice to victims. Listen along as Tim describes several cases where inadvertently photographed friction ridge detail was utilized to make an identification to a perpetrator, the various methods and techniques latent print examiners can add to their toolkit to analyze and compare this type of friction ridge detail, and his recommendations for ensuring this type of evidence is not overlooked or underutilized within future cases. This episode is funded by the National Institute of Justice’s Forensic Technology Center of Excellence (Award No. 15PNIJ-21-GK-02192-MUMU).
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293 episodes
MP3•Episode home
Manage episode 451465752 series 1433931
Content provided by Just Science and RTI International. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Just Science and RTI International or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
In episode two of our Case Studies season, Just Science sat down with Tim Fayle, Training Capability Lead for IDEMIA Australasia and Chair of the International Association for Identification’s Latent Print Certification Board, to discuss the utility of friction ridge detail inadvertently captured via photographs as a valuable and potentially underutilized type of evidence within a variety of case types. While the use of latent fingerprints recovered from crime scenes has been established as an important type of forensic evidence for decades, the increasingly widespread use of social media and other digital platforms has contributed to even more opportunities to garner friction ridge detail evidence following a crime. Practitioners and researchers alike have demonstrated the value of utilizing photographs presenting inadvertently captured finger and palm friction ridge detail – obtained via social media posts, other digital forums, and cellphone data – to identify perpetrators and help bring justice to victims. Listen along as Tim describes several cases where inadvertently photographed friction ridge detail was utilized to make an identification to a perpetrator, the various methods and techniques latent print examiners can add to their toolkit to analyze and compare this type of friction ridge detail, and his recommendations for ensuring this type of evidence is not overlooked or underutilized within future cases. This episode is funded by the National Institute of Justice’s Forensic Technology Center of Excellence (Award No. 15PNIJ-21-GK-02192-MUMU).
…
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293 episodes
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