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The title of chapter 5 was published incorrectly. The same has been corrected throughout the book to read as “Architecting Next Generation Community Policing Solutions”.

In security/safety-critical applications, such as community policing, citizens and Law Enforcement Officers (LEOs) need a safe and realistic environment to support their learning in handling challenging situations. In this context, the use of games can prove crucial in helping citizens improve awareness and better understand the potential value that can be developed in building relationships with Law Enforcement Agencies (LEAs) providing support within a specific area.

This paper will explore the motivation, workings and potential effect of the police’s use of various information and communication technologies to build trust in Afghanistan. To what degree do these efforts in fact contribute to trust-building and broader human security? What happens to trust-building when it comes to technology mediated interaction? Attention will be given to how the police, in addition to their own efforts, might link to ICT solutions being developed in civil society that are also aimed at improving accountability and more relations with the police and government in general. In doing so, it will consider the wider relations between the government and civil society, and the role technology might have in mediating this relationship and contributing to or hindering broader human security.

Evaluating policing strategies for effectiveness and community acceptance is a difficult task due to the lack of effective tools. To address these problems, we have developed the Visual Analytics Law Enforcement Toolkit (VALET) software that uses historical crime incident data to capture spatial and temporal trends while providing insight into departmental workload and performance. Through collaboration with partner police departments, we have used VALET’s crime mapping and prediction capabilities to educate both officers and citizens on how different policing enforcement strategies and changes within the community can affect crime trends. We overview the challenges of public perception of different community policy efforts and then describe the additional data exploration capabilities provided by VALET to fill this gap. We describe initial results from the use of VALET to support community outreach presentations, and make enhancement recommendations to improve community policing efforts and public perception of police action.

Nowadays social media mining is broadly used in the security sector to support law enforcement and to increase response time in emergency situations. One approach to go beyond the manual inspection is to use text mining technologies to extract latent topics, analyze their geospatial distribution and to identify the sentiment from posts. Although widely used, this approach has proven to be technically difficult for end-users: the language used on social media platforms rapidly changes and the domain varies according to the use case. This paper presents a monitoring architecture that analyses streams from social media, combines different machine learning approaches and can be easily adapted and enriched by user knowledge without the need for complex tuning.The framework is modeled based on the requirements of two H2020-projects in the area of community policing and emergency response.

Architecture in the current digital world is an essential discipline to safeguard the quality and proof of modern, complex IT-based solutions, in particular in the Next Generation Community Policing (NGCP), which is an emerging topic embracing new levels of complexity by incorporating also human aspects. This paper introduces the goals, the challenges and the opportunities of architecting for NGCP following the representative successful example of INSPECT EU H2020 project.

The architecture of INSPECT NGCP solution, is modular on open APIs, with flexibility to adapt and connect to existing police CAD/DBMS and provide a tailor-made (cherry picking) solution for the various Law Enforcement Agencies (LEA) formations. The choice of the architectural method, that is used in INSPECT /NGCP is the proven Risk- and Cost-Driven Architecture (RCDA), an agile solution architecture approach, which is a relatively new approach. For NGCP, the architecture primarily address bi-directional information flow between people and systems and dealing with potentially large, changing and various flows of data and it should facilitate flexible integration in a continually changing IT-landscape. An open, modular and loosely coupled architecture meets these strict requirements and therefore, is the best for the NGCP. It also allows for an incremental and iterative delivery strategy for each contributor to build a system together, leveraging the specific building blocks as part of the integrated solution. This architecture is documented via a set of multiple views. Integration is a major concern in modular architecture in NGCP, therefore, the integration plan is being introduced and followed during the design of the system. This paper will demonstrate the architecture approach in NGCP focusing on the example of INSPECT, as an emerging research and innovation project.

Community Policing has been evolving slowly but steadily. This progression shaped the present Community Policing model which is more than two decades old. Nowadays, the concept of Next Generation Community Policing is introduced. Police forces are utilizing existing social networks to address safety and policing issues. As such, social networks are used to evolve existing Community Policing strategies, advance the collaboration between law enforcement and other community stakeholders and build trustworthy partnerships with citizens.

At present, the police practice of using Social Networks to reach the communities they are serving is very popular and is gaining momentum. A growing number of police departments rely on social networks for public relations and notify the public of safety concerns. It therefore makes sense for the police to establish their own social network which will accommodate their practices and philosophy and will enhance the communication with the communities they serve. Despite the existence of a plethora of tools and applications available today, the development of a Social Network which is designed to meet police needs and to help in the evolution of Community Policing, is a very challenging task. This task requires, apart from a development effort, innovative ways of assessment, which will comply with an intricate Legal, Ethical, Societal framework governed by a complex Data Protection directive.

Consequently, a holistic approach is required for analysing functions and capabilities addressing technical and human issues, which are inter-related with legal and ethical aspects. The THOR approach consists of four dimensions: Technical, Human, Organisational, and Regulatory and can be used to assess the efficiency of the developed social network.

This paper presents research conducted under INSPECT (nspiring Citizearticipation for nhanced ommunity Poliing Acions), a project funded by the European Commission’s research agenda to bridge the gap between Community Policing as a philosophy and as an organizational strategy, capitalising on the use of Social Media.

Combining new technologies with traditional Community Policing (CP) activities aids in strengthening the cooperation between Law Enforcement Agencies (LEAs) and citizens. The Unity project will reinforce this connection by developing the Unity IT Toolkit; a suite of features that cover best practices used to support and assist CP methods across all CP stakeholders. It is structured in a web portal and in a mobile application. Both are developed taking into account the various views of the system such as the functional, data, business process, deployment, accessibility, usability, and security, among others. An iterative approach has been taken when implementing features to ensure they are relevant to the requirements of the user based on use and geographical location. A data driven analytics engine has also been implemented to assist in understanding the issues and concerns underpinning the volume of available information managed by the whole ToolKit. Additionally, a CP Strategy Generator is included to collect and build a CP data repository for helping LEAs in planning their CP strategy. Given the casuistry of each community, the ToolKit is instantiated for addressing the concrete local needs based on the 6 key pillars of community policing identified as part of the Unity project; (1) trust and confidence building, (2) accountability, (3) information sharing and communication, (4) addressing local needs, (5) collaboration, and (6) crime prevention. During key focus groups, end users envisioned the real potential of the ToolKit, identifying particular scenarios it would be beneficial.

This paper presents our initial, descriptive, practical, hybrid argumentation model, designed for the use by Criminal Intelligence Analysts (from now on referred to as analysts) working with sophisticated visual analytical software in uncertain sense-making environments. Analysts are required to create exhibits (as evidence) for a court of law or as input for decision-making in intelligence-led policing. These exhibits are required to be accurate, relevant and unbiased. The aim of our practical argumentation model is to assist software developers with understanding how analysts think and explain during uncertain sense-making activities. This should inform software developers on the requirements for the externalisation process of analysts’ thoughts and explanations. We believe that if software developers can support the externalisation process of analysts’ thoughts and explanations, then the process of assessing and judging the outcomes of sense-making activities becomes manageable and traceable for analysts and auditors.

With few exceptions, the situational dimension of fear of crime has been paid insufficient attention in criminological research. Departing from a theoretical framework of situational mechanisms, we argue that fear of crime should be studied as an experience following a person-setting interaction. Gathering data on situational circumstances, however, is not an easy task as it requires information regarding not only individuals but also time, place and content of a specific setting. However, following the innovative approach by Solymosi etal. (Legal Criminol Psych 20:193–211, 2015), we argue that technological advancements have allowed researchers to utilise the Experience Sampling Method through smartphone applications. This novel approach enables researchers to gather situational data in order to analyse fear of crime as a situational experience. The concluding discussion emphasises the potential practical implications of this knowledge and methods for further research that may contribute to increased knowledge on safety issues in urban communities.