Editor’s note: This article originally appeared in Police1’s digital edition, “Empowering law enforcement through data sharing.” Click here to download this free publication.
Crime poses an ongoing challenge for law enforcement agencies, necessitating a comprehensive understanding of regional crime trends to ensure public safety. Law enforcement can identify and address emerging crime patterns by embracing cross-agency data sharing. This article explores the significance of cross-agency data sharing in enhancing public safety and highlights practical steps to implement this collaborative approach.
Collaborative data sharing: A powerful solution
In today’s interconnected world, criminal activities often transcend jurisdictional boundaries. It is no longer feasible for neighboring law enforcement agencies to operate in isolation. By establishing mechanisms for sharing crime data, agencies gain access to a broader pool of information. This collaborative effort enables the identification of patterns and trends that may have otherwise gone unnoticed, fostering more effective crime prevention and investigation. Here are four direct benefits of data sharing:
1. Detecting emerging crime patterns: Sharing crime data empowers law enforcement agencies to analyze information from various sources, unveiling emerging crime patterns at a regional level. By leveraging data from multiple jurisdictions, agencies can detect shifts in criminal activity, pinpoint areas of concern and strategically allocate resources to address emerging threats. This holistic perspective allows for a proactive approach to tackling crime, leading to more efficient and targeted law enforcement efforts.
2. Enhancing investigative capabilities: Cross-agency data sharing equips law enforcement agencies with a comprehensive understanding of criminal activities. By pooling resources and knowledge, agencies can collaborate on investigations, leveraging shared information to solve crimes more efficiently. This collaborative approach increases the chances of successful investigations and reveals potential connections between seemingly unrelated cases, aiding in apprehending criminals operating across jurisdictions.
3. Improving resource allocation: Analyzing regional crime trends through cross-agency data sharing enables law enforcement agencies to allocate resources effectively. By identifying high-crime areas or specific types of criminal activities on the rise, agencies can deploy personnel and assets where they are most needed. This targeted approach maximizes the impact of law enforcement efforts, ensuring that resources are directed to areas where they can have the most significant effect on public safety.
4. Proactive crime prevention: One of the most significant advantages of cross-agency data sharing is its potential for proactive crime prevention. By identifying emerging crime patterns, law enforcement agencies can develop targeted strategies and initiatives to address these trends before they escalate. Sharing information about modus operandi, suspect descriptions and other relevant details enables real-time collaboration and the implementation of proactive measures to prevent crimes or mitigate their impact on the community.
Implementing cross-agency data sharing: A practical approach
Implementing cross-agency data sharing requires careful planning and coordination to ensure secure and efficient information exchange.
Here are some practical steps for police departments to follow:
1. Establish partnerships: Initiating partnerships and collaborations with neighboring law enforcement agencies is a crucial first step in implementing cross-agency data sharing. Building relationships and attending interagency meetings fosters cooperation and lays the foundation for successful information exchange. Police departments can proactively contact neighboring agencies, demonstrating their commitment to collaboration and shared goals of enhancing public safety.
2. Develop data sharing agreements: Drafting formal agreements or memorandums of understanding (MOUs) between participating agencies is essential for clarifying roles, responsibilities, limitations and dispute resolution procedures. These agreements should outline the purpose and objectives of data sharing, specify the types of data that can be shared, and establish protocols for data retention, access controls and data quality assurance. Agreements should include the following information:
➔ Define data-sharing policies: Clear and comprehensive data-sharing policies ensure information is exchanged securely and complies with jurisdictional laws and regulations. Policies should address data privacy, security and confidentiality concerns and establish guidelines for handling sensitive information. Clearly outlining the purpose, scope and limitations of data sharing can promote transparency, build trust among participating agencies, and minimize potential conflicts or misunderstandings.
➔ Standardize data formats: Agreement on common data standards, formats and protocols is crucial for seamless integration and exchange of information between agencies. Standardization ensures that shared data can be easily understood and interpreted across different systems. Standardized data fields, terminology and coding systems promote consistency and interoperability, further enabling efficient data analysis and collaboration.
➔ Implement secure data infrastructure: Establishing a secure data infrastructure is paramount to safeguarding sensitive information during data-sharing. Encryption should be employed to protect data transmission and storage; only authorized individuals can access and interpret the shared data. Implementing secure networks and firewalls prevents unauthorized access, data breaches, or cyber threats that could compromise the integrity of shared information.
3. Train personnel: Providing comprehensive training is vital to ensure successful implementation and adherence to data-sharing protocols. Training programs should emphasize the importance of data sharing, familiarize personnel with the established policies and procedures, and highlight the ethical and legal considerations associated with handling sensitive information. Personnel should be educated on data protection regulations and the responsible use of shared data, promoting a culture of compliance and professionalism.
4. Implement data management systems: Investing in robust data management systems is crucial to securely storing, retrieving and analyzing shared information. These systems should be able to handle large volumes of data, ensuring efficient data storage and retrieval. Data visualization tools can help agencies gain insights from the shared data, facilitating better decision-making and strategic resource allocation. Data management systems should also incorporate robust security features to protect transmitted information from unauthorized access.
Following these practical steps, police departments can successfully implement cross-agency data-sharing initiatives. These steps foster collaboration, enhance the collective ability to address regional crime trends, and ultimately contribute to creating safer communities.
Engage in ongoing evaluation
Regular evaluation and refinement of the data-sharing processes based on feedback, emerging technologies and changing needs ensure continuous improvement and the effectiveness of cross-agency collaborations.
After identifying key performance indicators (KPIs), police departments can:
● Analyze crime data to assess the overall impact of data-sharing, paying particular attention to crime statistics before and after the data-sharing took effect. Compare crime data by time and location.
● Compare case resolution times before and after data sharing took effect.
● Assess the level of collaboration and information sharing among agencies by examining joint operations and investigations with surveys and interviews. Make sure to identify cases where data-sharing contributed to solving a complex case, identifying and locating suspects, or uncovering criminal networks.
● Gather feedback from participating members of the service via surveys and interviews. Assess morale and productivity from their perspective. Also, gather feedback from stakeholders to gauge their perception of data-sharing initiatives and their efficacy.
● Evaluate and measure the economic impact by analyzing costs associated with software, hardware, infrastructure, training and other personnel resources against the potential benefits of improved operational efficiency and reduced crime rates.
● Continue to monitor and evaluate data-sharing agreements, staying informed about best practices, innovations and evolving crime trends.
Data-sharing in action
From my professional experience, data-sharing is an effective way for agencies to assist each other beyond solving crimes and locating witnesses. For example, as a crime analyst for the Bronx District Attorney, I used NYPD arrest data to strengthen prosecutors’ bail applications by providing them with real-time arrest histories of defendants. Further, I used NYPD overdose data to create maps for targeted opioid-epidemic interventions by geocoding each event and filtering by drug type.
Conclusion
Data-sharing enhances the collaborative efforts between agencies in solving crimes and locating witnesses and empowers professionals, such as crime analysts, to utilize real-time information for more effective interventions and support in the criminal justice system.
About the author
Jill Paccione-Frometa is a law enforcement professional, criminal justice researcher, doctoral student and lecturer at John Jay College of Criminal Justice. She was previously employed as a research scientist at New York University and the New York City Police Department, among other roles in New York City’s criminal justice system, and is a New York State certified Crime Analyst. Recently, Jill founded The Police Pracademic, which aims to help smaller police departments create, implement, and evaluate evidence-based practice and research.