Innovative data collection methods in criminological research: editorial introduction

Novel technologies, such as GPS, the Internet and virtual environments are not only rapidly becoming an increasingly influential part of our daily lives, they also have tremendous potential for improving our understanding of where, when and why crime occurs. In addition to these technologies, several innovative research methods, such as neuropsychological measurements and time-space budgets, have emerged in recent years. While often highly accessible and relevant for crime research, these technologies and methods are currently underutilized by criminologists who still tend to rely on traditional data-collection methods, such as systematic observation and surveys. The contributions in this special issue of Crime Science explore the potential of several innovative research methods and novel technologies for crime research to acquaint criminologists with these methods so that they can apply them in their own research. Each contribution deals with a specific technology or method, gives an overview and reviews the relevant literature. In addition, each article provides useful suggestions about new ways in which the technology or method can be applied in future research. The technologies describe software and hardware that is widely available to the consumer (e.g. GPS technology) and that sometimes can even be used free of charge (e.g., Google Street View). We hope this special issue, which has its origins in a recent initiative of the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR) called CRIME Lab, and a collaborative workshop together with the Research consortium Crime, Criminology and Criminal Policy of Ghent University, will inspire researchers to start using innovative methods and novel technologies in their own research. Issues and challenges facing crime researchers Applied methods of scientific research depend on a variety of factors that play out at least in part beyond researcher control. One such factor regards the nature and availability of data, which largely determines the research questions that can be addressed: Data that cannot be collected cannot serve to answer a research question. Although this may seem like stating the obvious, it has had and continues to have far-reaching implications for criminological research. Because crime tends to be a covert activity and offenders have every interest in keeping it that way, crime in action can rarely be observed, let alone in such a way as to allow for systematic empirical study. Consequently, our knowledge of the actual offending process is still limited and relies in large part on indirect evidence. The same applies to offender motivations and the offending process; these cannot be measured directly in ways similar to how * Correspondence: [email protected] Netherlands Institute for the Study of Crime and Law Enforcement (NSCR), De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands Full list of author information is available at the end of the article © 2014 van Gelder and van Daele; licensee Spr Commons Attribution License (http://creativeco reproduction in any medium, provided the orig we can observe say the development of a chemical process or the workings of gravity. This has placed significant restrictions on the way crime research has been performed over the years, and most likely has coloured our view of crime and criminality by directing our gaze towards certain more visible elements such as offender backgrounds, demographics and criminal careers. Another factor operating outside of researcher control regards the fact that the success of scientific analyses hinges on the technical possibilities to perform them. Even if researchers have access to particular data, this does not guarantee that the technology to perform the analysis in the best possible way is available to them. The complexity of the social sciences and the interconnectivity of various social phenomena, together with the lack of a controlled environment or laboratory, require substantial computational power to test highly complicated models. For instance, the use of space-time budgets, social network analysis or agent-based modelling can be quite resource-intensive. Adding the complexity of social reality to the resulting datasets (e.g. background variables related to social inger. This is an Open Access article distributed under the terms of the Creative mmons.org/licenses/by/4.0), which permits unrestricted use, distribution, and inal work is properly credited. van Gelder and Van Daele Crime Science 2014, 3:6 Page 2 of 4 http://www.crimesciencejournal.com/content/3/1/6 structure, GIS to incorporate actual road networks, etc.) puts high pressure on the available computational power of regular contemporary desktop computers. Addressing these challenges has practical and financial consequences, which brings us to the third issue, which although more mundane in nature is by no means limited to the applied sciences: a researcher requires the financial and non-financial resources to be able to perform his