JOURNAL ARTICLE

Accreditation of Crime Scene Investigation under ISO17020:2012 Standard in Hong Kong.

  • Published In: Forensic Science & Technology, 2025, v. 50, n. 3. P. 314 1 of 3

  • Database: Criminal Justice Abstracts with Full Text 2 of 3

  • Authored By: Duen-yee Luk; Terence Hok-man Cheung; Wai-nang Cheng; Wai-kit Sze; Man-hung Lo; Joseph Sze-wai Wong; Chi-keung Li 3 of 3

Abstract

Crime scene investigation (CSI) is an important link in the criminal justice system as it serves as a bridge between establishing the happenings during an incident and possibly identifying the accountable persons, providing light in the dark. The International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) collaborated to develop the ISO/IEC 17020:2012 standard to govern the quality of CSI, a branch of inspection activity. These protocols include the impartiality and competence of the crime scene investigators involved, contemporary recording of scene observations and data obtained, the correct use of resources during scene processing, forensic evidence collection and handling procedures, and the confidentiality and integrity of any scene information obtained from other parties etc. The preparatory work, the accreditation processes involved and the implementation of new quality measures to the existing quality management system in order to achieve the ISO/IE 17020:2012 accreditation at the Forensic Science Division of the Government Laboratory in Hong Kong are discussed in this paper. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Forensic Science & Technology. 2025/06, Vol. 50, Issue 3, p314
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2025
  • ISSN:1008-3650
  • DOI:10.16467/j.1008-3650.2025.3009
  • Accession Number:185953719
  • Copyright Statement:Copyright of Forensic Science & Technology is the property of Institute of Forensic Science, Ministry of Public Security and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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