Rowan's Story

In my applied criminology capstone, my group analyzed where registered sex offenders live across New York State using registry and Census data. My job was making the data usable and reliable. I audited hundreds of records, fixed mismatches, set a simple four-step data cleaning checklist, and kept a change log so any of the other groups could follow our process. I also checked ethical considerations with my professor and limited sensitive details. The result was a clean, consistent dataset our group and the class could rely on. I was invited to help two other groups apply the same process my group used. The project strengthened my decision-making, documentation, and communication, all skills I'll bring to a crime analyst role where qualities like accuracy and transparency matter a great deal.

• Cleaned and documented multi-source datasets (NYS Registry + ACS) for capstone analysis; created a 4-step workflow and change log adopted by 2 additional teams, improving class-wide data quality and reproducibility.

Senior seminar project linking registry and community data across NY counties. Led data quality workflow and documentation; supported two groups in their work.

Skills

• Critical thinking & inquiry
• Professional responsibility
• Ethical practice
• Tech fluency
• Collaboration
• Purposeful communication

In a senior seminar focused on applied criminology, our class took on a semester-long project to investigate the kinds of communities where registered sex offenders are more likely to live. We used publicly available community and sex offender registry data for New York State. The class was organized into small group, each one assigned to a specific region of the state. One component of the project involved collecting and examining data across multiple counties.

My role for this part of the project was to help clean and organize the data, ensuring that all entries were accurate and could be used for meaningful analysis and reporting. This meant identifying errors and discrepencies, correcting inconsistencies, and making decisions about what information was reliable and should be included in the analysis.

I reviewed each dataset, checking hundreds of entries for duplications, typos and formatting errors, and inconsistencies. I had to decide what information was important, flag inaccuracies, and document the changes I made. With guidance from my professor, I used data to inform my decisions and worked through some of the practical and ethical challenges of using sensitive information for the purpose of research.

My work helped ensure the data was accurate, consistent, and usable for the class project. Because of the quality and clarity of the process I created with my group, I was asked to help other groups in the class apply the same standards and process to their own datasets.

This experience is preparing me for the kind of work I want to do as a crime analyst. I'm learning how to manage complex datasets, make decisions about data accuracy and relevance, and communicate about how I made those decisions clearly to others. I'm also seeing how technical work like data cleaning connect to bigger questions of justice and social problems. I feel more confident stepping into a role where I have these kinds of responsibities.