{"id":840,"date":"2026-08-27T15:26:12","date_gmt":"2026-08-27T15:26:12","guid":{"rendered":"https:\/\/www.tarleton.edu\/crime-analysis\/?page_id=840"},"modified":"2026-08-27T20:31:04","modified_gmt":"2026-08-27T20:31:04","slug":"synthetic-spatial-crime-data-project","status":"publish","type":"page","link":"https:\/\/www.tarleton.edu\/crime-analysis\/synthetic-spatial-crime-data-project\/","title":{"rendered":"Synthetic Spatial Crime Data Project"},"content":{"rendered":"\n
\n
\n
\n

CURRENT RESEARCH \u2022 AI \u2022 SPATIAL DATA \u2022 DIGITAL TWIN<\/p>\n\n\n\n

Synthetic Spatial Crime Data<\/h1>\n\n\n\n

Building realistic digital environments for a new generation of spatial criminology and experimental crime research.<\/p>\n\n\n\n

This project combines generative artificial intelligence, spatial statistics and crime data to develop high-fidelity synthetic datasets that can support theory testing, simulation and evaluation while addressing many of the privacy and access limitations associated with sensitive criminal justice data.<\/p>\n\n\n\n

\n
Explore the Project \u2193<\/a><\/div>\n\n\n\n
\u2190 Institute Home<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n
\n
\n
\"Teal<\/figure>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
\n
\n
\n

Project Overview<\/a><\/p>\n<\/div>\n\n\n\n

\n

Why Synthetic Data?<\/a><\/p>\n<\/div>\n\n\n\n

\n

Research Approach<\/a><\/p>\n<\/div>\n\n\n\n

\n

Synthetic City<\/a><\/p>\n<\/div>\n\n\n\n

\n

Research Team<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n
\n
\n

PROJECT OVERVIEW<\/p>\n\n\n\n

Building a Digital Laboratory for Crime Research<\/h2>\n\n\n\n

Crime researchers often depend on administrative datasets that contain sensitive information, vary substantially across jurisdictions and can be difficult to access or share. These limitations make replication, methodological experimentation and large-scale comparative research difficult.<\/p>\n\n\n\n

The Synthetic Spatial Crime Data project is developing a digital research infrastructure capable of generating realistic artificial crime incidents and related urban characteristics. The goal is not simply to create artificial records, but to construct synthetic environments that reproduce meaningful spatial, temporal and social relationships found in real cities.<\/p>\n\n\n\n

The initial proof of concept focuses on Dallas, Texas, with a longer-term vision of developing scalable research infrastructure capable of supporting comparative research across multiple U.S. metropolitan areas.<\/p>\n<\/div>\n\n\n\n

\n
\n

PROJECT AT A GLANCE<\/p>\n\n\n\n

Synthetic Crime Research Infrastructure<\/h3>\n\n\n\n
\n

FOCUS<\/p>\n\n\n\n

Synthetic spatial and temporal crime data<\/p>\n<\/div>\n\n\n\n

\n\n\n\n
\n

INITIAL LOCATION<\/p>\n\n\n\n

Dallas metropolitan area<\/p>\n<\/div>\n\n\n\n

\n\n\n\n
\n

CORE METHODS<\/p>\n\n\n\n

Generative AI \u2022 Spatial modeling \u2022 Simulation<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n

WHY SYNTHETIC DATA?<\/p>\n\n\n\n

Creating New Opportunities for Experimental Criminology<\/h2>\n\n\n\n

Well-designed synthetic datasets can create controlled research environments that complement\u2014not replace\u2014real-world criminal justice data.<\/p>\n\n\n\n

\n
\n
\n

Privacy<\/h3>\n\n\n\n

Reduce reliance on identifiable or sensitive incident-level information when developing and testing analytical methods.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

Reproducibility<\/h3>\n\n\n\n

Create research environments that can be shared, repeated and systematically evaluated by other researchers.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

Experimentation<\/h3>\n\n\n\n

Manipulate controlled conditions to evaluate theories, analytical assumptions and alternative crime-prevention scenarios.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

Scalability<\/h3>\n\n\n\n

Develop methods that can eventually support comparative research across multiple cities and metropolitan environments.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n
\n
\n
\"The<\/figure>\n<\/div>\n\n\n\n
\n

DATA FOUNDATION<\/p>\n\n\n\n

Modeling the Complexity of Real Cities<\/h2>\n\n\n\n

Synthetic crime cannot be modeled in isolation. The research environment integrates multiple types of spatial and social information to represent the context in which criminal events occur.<\/p>\n\n\n\n

\n
\n
\n

Crime Incident Data<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

Census & Demographic Data<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n
\n
\n

Human Mobility Data<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

Foot-Traffic Patterns<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n
\n
\n

Points of Interest<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

Urban Spatial Infrastructure<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n

RESEARCH APPROACH<\/p>\n\n\n\n

From Real Data to Synthetic Environments<\/h2>\n\n\n\n

The project combines computational methods with spatial criminology to generate, evaluate and ultimately use synthetic urban crime environments.<\/p>\n\n\n\n

\n
\n
\n

01<\/p>\n\n\n\n

Integrate Data<\/h3>\n\n\n\n

Combine crime, demographic, mobility and spatial information into a unified research environment.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

02<\/p>\n\n\n\n

Train Models<\/h3>\n\n\n\n

Evaluate generative approaches including GANs, variational autoencoders and diffusion models.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

03<\/p>\n\n\n\n

Generate Crime Data<\/h3>\n\n\n\n

Produce synthetic incidents designed to reproduce meaningful spatial and temporal crime characteristics.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

04<\/p>\n\n\n\n

Validate & Simulate<\/h3>\n\n\n\n

Compare synthetic patterns with empirical data and use validated environments for simulation and experimentation.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n
\n
\n

CLOUD-ENABLED RESEARCH<\/p>\n\n\n\n

Computational Infrastructure for Research at Scale<\/h2>\n\n\n\n

The proof of concept is being developed with cloud infrastructure and consultation from Amazon Web Services specialists. The computing environment supports large geospatial datasets, GPU-based model training, synthetic data generation and spatial post-processing workflows that would be difficult to conduct on conventional desktop systems.<\/p>\n<\/div>\n\n\n\n

\n
\n

Research Infrastructure<\/h3>\n\n\n\n

Data Lake<\/strong>
Large-scale geospatial and criminal justice research data<\/p>\n\n\n\n

GPU Training<\/strong>
Machine-learning and generative-model development<\/p>\n\n\n\n

Spatial Processing<\/strong>
Geospatial simulation and validation workflows<\/p>\n\n\n\n

Generative AI<\/strong>
Advanced synthetic-data experimentation<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n
\n
\n

FUTURE RESEARCH DIRECTION<\/p>\n\n\n\n

Toward a Synthetic City<\/h2>\n\n\n\n

The longer-term vision extends beyond generating individual synthetic crime records. The project seeks to develop an AI-enabled synthetic city in which people, places, movement, social relationships and criminal events can interact within a virtual urban environment.<\/p>\n\n\n\n

Such an environment could provide criminologists with a new form of experimental laboratory\u2014one in which researchers can alter conditions, observe emerging crime patterns and test the potential effects of interventions without imposing those experiments on real communities.<\/p>\n\n\n\n

\n
\n
\n

Simulate Human Movement<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

Model Social Behavior<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

Test Interventions<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n
\"Futuristic<\/figure>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
\n

RESEARCH TEAM<\/p>\n\n\n\n

Project Research Team<\/h2>\n\n\n\n

The project combines expertise in spatial criminology, crime analysis, data science, cybercrime and emerging technologies.<\/p>\n\n\n\n

\n
\n
\n
\"Headshot<\/figure>\n\n\n\n

PROJECT RESEARCHER<\/p>\n\n\n\n

Dr. Olga B. Semukhina<\/h3>\n\n\n\n

Department Head & Professor<\/p>\n\n\n\n

Department of Criminal Justice<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n
\"Professional<\/figure>\n\n\n\n

PROJECT RESEARCHER<\/p>\n\n\n\n

Dr. Christopher Copeland<\/h3>\n\n\n\n

Associate Professor<\/p>\n\n\n\n

Department of Computer Science & Electrical Engineer<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n

CURRENT STATUS<\/p>\n\n\n\n

From Proof of Concept to Research Platform<\/h2>\n\n\n\n
\n
\n
\n

PHASE 01<\/p>\n\n\n\n

Dallas Proof of Concept<\/h3>\n\n\n\n

Develop and evaluate synthetic spatial crime-data generation using a major metropolitan environment.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

PHASE 02<\/p>\n\n\n\n

Model Validation<\/h3>\n\n\n\n

Evaluate whether synthetic datasets reproduce meaningful spatial, temporal and social characteristics of observed crime.<\/p>\n<\/div>\n<\/div>\n\n\n\n

\n
\n

FUTURE<\/p>\n\n\n\n

Multi-City Research<\/h3>\n\n\n\n

Expand the infrastructure to support comparative research, simulation and experimental criminology across multiple cities.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

\n
\n
\n

AI \u2022 SPATIAL DATA \u2022 EXPERIMENTAL CRIMINOLOGY<\/p>\n\n\n\n

Interested in Synthetic Crime Data Research?<\/h2>\n\n\n\n

We welcome interdisciplinary collaboration involving synthetic data, generative AI, geospatial science, criminology, simulation and data-driven public safety research.<\/p>\n<\/div>\n\n\n\n

\n
\n
Contact the Research Team \u2192<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

CURRENT RESEARCH \u2022 AI \u2022 SPATIAL DATA \u2022 DIGITAL TWIN Synthetic Spatial Crime Data Building realistic digital environments for a new generation of spatial criminology and experimental crime research. This …<\/p>\n","protected":false},"author":973,"featured_media":962,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"functions-assets\/subsite-hero-page-template.php","meta":{"_acf_changed":false,"inline_featured_image":false,"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":"","footnotes":""},"class_list":["post-840","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"coauthors":[],"author_meta":{"author_link":"https:\/\/www.tarleton.edu\/crime-analysis\/author\/semukhina\/","display_name":"semukhina"},"relative_dates":{"created":"Posted 2 weeks ago","modified":"Updated 2 weeks ago"},"absolute_dates":{"created":"Posted on August 27, 2026","modified":"Updated on August 27, 2026"},"absolute_dates_time":{"created":"Posted on August 27, 2026 3:26 pm","modified":"Updated on August 27, 2026 8:31 pm"},"featured_img_caption":"","featured_img":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-content\/uploads\/sites\/233\/2026\/08\/Gemini_Generated_Image_ey4hsley4hsley4h.jpg","series_order":"","_links":{"self":[{"href":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-json\/wp\/v2\/pages\/840","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-json\/wp\/v2\/users\/973"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-json\/wp\/v2\/comments?post=840"}],"version-history":[{"count":10,"href":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-json\/wp\/v2\/pages\/840\/revisions"}],"predecessor-version":[{"id":999,"href":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-json\/wp\/v2\/pages\/840\/revisions\/999"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-json\/wp\/v2\/media\/962"}],"wp:attachment":[{"href":"https:\/\/www.tarleton.edu\/crime-analysis\/wp-json\/wp\/v2\/media?parent=840"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}