Lovell David, Vella Kellie, Muñoz Diego, McKague Matt, Brereton Margot, Ellis Peter
School of Computer Science, Queensland University of Technology, Brisbane, Australia.
Centre for Data Science, Queensland University of Technology, Brisbane, Australia.
Forensic Sci Res. 2022 Mar 25;7(3):467-483. doi: 10.1080/20961790.2021.2023418. eCollection 2022.
Disaster victim identification (DVI) entails a protracted process of evidence collection and data matching to reconcile physical remains with victim identity. Technology is critical to DVI by enabling the linkage of physical evidence to information. However, labelling physical remains and collecting data at the scene are dominated by low-technology paper-based practices. We ask, how can technology help us tag and track the victims of disaster? Our response to this question has two parts. First, we conducted a human-computer interaction led investigation into the systematic factors impacting DVI tagging and tracking processes. Through interviews with Australian DVI practitioners, we explored how technologies to improve linkage might fit with prevailing work practices and preferences; practical and social considerations; and existing systems and processes. We focused on tagging and tracking activities throughout the DVI process. Using insights from these interviews and relevant literature, we identified four critical themes: protocols and training; stress and stressors; the plurality of information capture and management systems; and practicalities and constraints. Second, these findings were iteratively discussed by the authors, who have combined expertise across electronics, data science, cybersecurity, human-computer interaction and forensic pathology. We applied the themes identified in the first part of the investigation to critically review technologies that could support DVI practitioners by enhancing DVI processes that link physical evidence to information. This resulted in an overview of candidate technologies matched with consideration of their key attributes. This study recognises the importance of considering human factors that can affect technology adoption into existing practices. Consequently, we provide a searchable table (as Supplementary information) that relates technologies to the key considerations and attributes relevant to DVI practice, for readers to apply to their own context. While this research directly contributes to DVI, it also has applications to other domains in which a physical/digital linkage is required, and particularly within high stress environments with little room for error.Key points:Disaster victim identification (DVI) processes require us to link physical evidence and digital information. While technology could improve this linkage, experience shows that technological "solutions" are not always adopted in practice.Our study of the practices, preferences and contexts of Australian DVI practitioners suggests 10 critical considerations for these technologies.We review and evaluate 44 candidate technologies against these considerations and highlight the role of human factors in adoption.
灾难遇难者身份识别（DVI）需要一个漫长的证据收集和数据匹配过程，以便将遗体与遇难者身份进行核对。技术对于DVI至关重要，它能够将物证与信息联系起来。然而，在现场对遗体进行标记和收集数据主要采用低技术含量的纸质做法。我们不禁要问，技术如何帮助我们标记和追踪灾难遇难者？我们对这个问题的回答分为两部分。首先，我们进行了一项以人机交互为主导的调查，探究影响DVI标记和追踪过程的系统因素。通过采访澳大利亚的DVI从业者，我们探讨了有助于改进关联的技术如何与现行工作实践和偏好相契合；实际和社会方面的考量；以及现有系统和流程。我们重点关注了整个DVI过程中的标记和追踪活动。利用这些访谈以及相关文献中的见解，我们确定了四个关键主题：协议与培训；压力与压力源；信息捕获和管理系统的多样性；以及实际情况与限制因素。其次，作者们对这些发现进行了反复讨论，他们融合了电子学、数据科学、网络安全、人机交互和法医病理学等多方面的专业知识。我们将调查第一部分中确定的主题应用于批判性地审视那些能够通过加强将物证与信息联系起来的DVI流程来支持DVI从业者的技术。这得出了一份候选技术概述，并对其关键属性进行了考量。本研究认识到考虑可能影响技术融入现有实践的人为因素的重要性。因此，我们提供了一个可搜索的表格（作为补充信息），将技术与DVI实践相关的关键考量因素和属性联系起来，供读者应用于他们自己的情境。虽然这项研究直接有助于DVI，但它也适用于其他需要进行物理/数字关联的领域，特别是在容错空间很小的高压力环境中。要点：灾难遇难者身份识别（DVI）过程要求我们将物证与数字信息联系起来。虽然技术可以改进这种关联，但经验表明，技术“解决方案”在实践中并不总是被采用。我们对澳大利亚DVI从业者的实践、偏好和背景进行的研究为这些技术提出了10个关键考量因素。我们根据这些考量因素对44种候选技术进行了审查和评估，并强调了人为因素在采用过程中的作用。
