PhD Thesis




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  • S. W. van den Braak, "Sensemaking Software for Crime Analysis," PhD Thesis , Utrecht University, Utrecht, The Netherlands, 2010. bibtex Go to document
    @PHDTHESIS{Thesis, AUTHOR = {Braak, S.W. van den},
      TITLE = {Sensemaking Software for Crime Analysis},
      institution = {Utrecht University},
      YEAR = {2010},
      address = {Utrecht, The Netherlands},
      url = {http://igitur-archive.library.uu.nl/dissertations/2010-0226-200328/UUindex.html},
      abstract = {Criminal investigation is a difficult and laborious process that is prone to error as teams of investigators may be subject to tunnel vision, groupthink, and confirmation bias. As a result, miscarriages of justice may ensue. To overcome these problems, in the Dutch law enforcement organization, crime analysts have been given a more important role. It is now their task to critically evaluate the investigation that is going on. They have to make sense of the vast amount of evidence available in a case by generating plausible scenarios about what might have happened. Subsequently, they have to assess the quality of their scenarios and choose the best alternative. Due to the difficulty of this process, a great need exists for software that supports crime analysts in their task. However, current support tools for crime analysis do not allow analysts to record scenarios and their relation to the evidence and as a result the most important part of the analysis process remains in the analysts' minds. Therefore, they may benefit from so-called sensemaking systems that allow them to make their reasoning process explicit by visualizing scenarios and the reasons why these scenarios are supported by the evidence. Nevertheless, such sensemaking tools for crime analysis are relatively sparse and often do not incorporate a logical model of reasoning with evidence in the context of crime analysis. This thesis aims to fill this gap by proposing sensemaking software that has specifically been designed for crime analysis. Such a tool should be rationally well-founded, natural, useful, usable, and effective. To this aid, a proof-of-concept application called AVERs (Argument Visualization for Evidential Reasoning based on stories) was built that implements a rationally well-founded and natural model of the reasoning that takes place in crime analysis. In this way a standard of rational reasoning is encouraged and errors may be reduced. Using AVERs analysts are able to create visual representations of scenarios and evidential arguments. Scenarios are represented as causal networks of events, while evidential arguments are arguments based on the evidential data in the case. Such arguments are based on argumentation schemes that often come with critical questions. These questions make the analysts more aware of possible sources of doubt and encourage them to critically examine the evidence. Evidential arguments can be used to support or attack scenarios with the available evidence. In this way, this software allows the analysts to reason about scenarios and to critically evaluate them. Moreover, it provides features that can be used to compare alternative scenarios. A series of empirical studies has confirmed that the design and implementation of AVERs fulfills all five criteria to a certain degree. This means that it is useful to crime analysts and satisfies their desires, while it may improve their analysis of the case and the communication of their results to the investigators working on the case, and ensures that rational analyses are performed. Therefore, through this software in the future biases in the crime analysis process may be avoided.}
    }

Summary

 

A sensemaking tool called AVERs was developed to aid the crime analysis process. Using this tool crime analysts are able to create visual representations of plausible scenarios about what might have happened in a case and their relation to the evidence. Thus, it allows them to reason about scenarios and to critically evaluate them.

The application implements a rationally well-founded and natural model of the reasoning that takes place in crime analysis. In this way a standard of rational reasoning is encouraged and errors may be reduced. Studies indicate that the developed tool is useful to crime analysts and satisfies their desires, while it may improve their analysis of the case and the communication of their results to the investigators working on the case, and ensures that rational analyses are performed. Therefore, through this software in the future biases in the crime analysis process may be avoided.

Press release of The Netherlands Organisation for Scientific Research (NWO)

New software can prevent mistakes in detective work. At present, the police still make unnecessary mistakes when collecting and analysing evidence, which sometimes results in miscarriages of justice. Dutch researcher Susan van den Braak has developed a computer program that can help to prevent such blunders.

Coverage in the Dutch press

About the project

Crime investigation is a difficult and laborious process that is prone to error and the costs of mistakes can be high. This project will develop software support to tackle two problems that often occur in complex criminal cases: lack of overview of a mass of evidence by initial investigators and lack of transparency of case files for subsequent investigators, prosecutors and fact finders.

A demonstrator prototype will be developed of software with which crime investigators can visualize and analyse their reasoning about a case. Such software will support investigators in seeing patterns, discovering new relationships or inconsistencies, and identifying missing evidence. It will also enable subsequent investigators, prosecutors and fact finders to gain a better understanding of a case. The software will be built as an extension to evidence data modelling software currently used in six Dutch police regions. The effects of the software on an investigator’s understanding of a case and the quality of file transfer will be measured in detailed user experiments.

The software will be based on recent insights that the only viable manner in which police
investigators can structure the gathered information is through stories about what happened, linked to the available evidence and hypotheses with evidential arguments. These insights will be further developed and made precise by clarifying how stories can be anchored in the available evidence by building arguments with general knowledge. Thus the necessary theoretical foundations will be provided for software that is theoretically sound and respects the practical constraints of crime investigation.