DISN Wildlife - Abstract

This Disrupting Operations of Illicit Supply Networks (D-ISN) project aims to address the illegal trade in wild animals. Wildlife trafficking is one of the most common illicit activities globally and poses a substantial human cost along with detrimental social and economic impacts, including increased crime, violence, and environmental destruction. The COVID-19 pandemic, likely the result of a virus that spread to humans from a wildlife market, demonstrates that wildlife trafficking can have serious public health and biosafety implications. This project seeks to catalyze technological innovations by creating tools that empower domain experts to continuously discover and obtain actionable insights by exploring the wealth of data related to illicit networks that spread over multiple sources. The project will advance our Nation's ability to counter wildlife trafficking activities through novel approaches for data discovery, analytics, and modeling. The project will also promote the progress of research in criminal activities that have an online footprint. Data collected in the course of the project will be made publicly available through a dataset search engine, making it possible for researchers to enrich data-driven analyses through the dynamic discovery and linkage of previously unknown data, and allowing them to answer important questions. The project team's collaboration with non-governmental organizations and discussions with law enforcement agencies will facilitate an interactive process that can fine-tune disruption techniques and suggest pragmatic real-world implementation strategies and policy recommendations. The project uses an interdisciplinary approach – combining methods and tools from computer science and engineering as well as wildlife criminology to advance the state of the art and build fundamental knowledge in methods for the discovery and exploration of data related to illicit activities with an online footprint, as well as enhance wildlife trafficking research. Specifically, this project contributes new algorithms that provide capabilities to: 1) discover and automatically collect data related to wildlife trafficking from multiple platforms at an unprecedented scale; and 2) use these data to build computational models and study wildlife trafficking patterns and networks at the global level. Through the use of analytical techniques such as crime mapping, quantitative data analysis, and social network analysis, this project will address research questions related to the scale and the nature of illicit wildlife trade, network structures of online wildlife trafficking, and empirically-driven disruption models that can be used to best tackle them. The algorithms are adaptable to different domains and data, support the discovery of both unstructured data and structured datasets, and will serve as the basis for usable tools that empower domain experts to continuously discover and monitor relevant data.

Team

Juliana Freire

https://vgc.engineering.nyu.edu/~juliana

Juliana is a Professor of Computer Science and Data Science at New York University, and the Elected Chair of the ACM SIGMOD.

Jennifer Jacquet

https://jenniferjacquet.com/

Jennifer Jacquet is an Associate Professor in the Department of Environmental Studies and Director of XE: Experimental Humanities and Social Engagement at NYU. She is also deputy director of NYU's Center for Environmental and Animal Protection. Her research focuses on animals and the environment, Agnotology, and attribution and responsibility in the Anthropocene

Gohar Petrossian

https://www.jjay.cuny.edu/faculty/gohar-petrossian

Dr. Gohar Petrossian is Associate Professor in the Department of Criminal Justice, Director of the International Crime and Justice Master’s Program at John Jay College of Criminal Justice, and Deputy Executive Officer of the CUNY Graduate Center Criminal Justice Doctoral Program. Dr Petrossian is also the co-editor of the Problem-Oriented Policing Guides (at the popcenter.org) for Wilderness Problems.

Sunandan Chakraborty

https://luddy.iupui.edu/people/sunandan-chakraborty/

Sunandan Chakraborty focuses on data science for social good. Building computational models that leverage vast data sets, he applies them to a broad spectrum of problems in social and environmental science, agriculture, health, and other fields. He draws on diverse data sets (news, social media, images, etc.) and uses tools such as big data analytics, machine learning, information extraction, and time series analysis to compile information and discover knowledge that can lead to solutions.

Monique Sosnowski

https://www.msosnowski.com/

Monique is a wildlife crime and security specialist who integrates her hands-on experience in wildlife crime prevention and analysis with African field conservation. Her work in this field is reflected in her 30 academic articles, reports, and book chapters, alongside a co-authored book on African security and politics in Benin. With nearly a decade of research experience on wildlife crime prevention in Africa, Monique focuses on integrating academic insights into practical field operations to ensure they are evidence-based and optimally effective.

Juliana Barbosa

https://github.com/julesbarbosa

Juliana is a Research Scientist at New York University - Visualization Imaging and Data Analysis Center

News

1. NSF DISN Conference 2023

An Interdisciplinary Approach to the Discovery, Analysis, and Disruption of Wildlife Trafficking Networks

NSF Conference Poster

This project is funded by the NSF