Institute for Complex Additive Systems Analysis (ICASA) Applications of Data Analysis & Visualization Environment (DAVE) to Predict and Interdict IUU Fishing Activity Institute for Complex Additive Systems Analysis (ICASA) Van D. Romero, PhD Richard W. Miller, PhD

Well Known Problem Set – New Analytics Combined deep analysis of seemingly disparate data sources to create a more fulsome understanding of the nature , character, and scope of the problem Document, track, and even predict IUU behaviour patterns Support investigation & prosecution Financial Loss- $20B+ Environmental Damage Threatened Species Food Security Nutritional Requirements Limited Enforcement Resources

The analytic we are close to being able to demonstrate (albeit with some synthetic data) would be a rudimentary metric for identifying areas were there is a delta between VIIRS and AIS data and other data sources. We would envision being able to look at behavior analysis and anomaly detection as a way of doing both alerting, and potentially to study ways to make IUU interdictions more successful (e.g., prioritization of resources, patrol strategies, etc.)

DAVE: Data Analysis and Visualization Engine DAVE is a graphical data analysis environment built by NMT/ICASA that enables: Rapid development of analytic prototypes; Fusion of large, noisy, and/or disparate data sets; Development of modular, ‘snap-in’ analytic, visualization, and processing modules; and, Collaboration via sharing of saved work-flows and data sets. Numerous existing plug-ins, including: Complex network analysis; Document processing; Computer Network Forensics; Timeseries analysis; Multi-mode visualizations; and, many others. ICASA Approach: Enable data scientists to work with subject-matter experts ‘in the loop’ Top Image: A typical workspace in the DAVE environment Middle Image: Staff from the Bernalillo County District Attorney Office analyzing criminal justice data in the DAVE environment Bottom Image: The NMT Patented Internet Monitoring capability running from inside of DAVE Note – we were able to quickly write/update several plugins inside of DAVE for the purposes of being able to ingest HDF (VIIRS) data and improve existing visualizations for this project.

Using DAVE/ICASA to Explore IUU Data Potential Data Sources VIIRS data (satellite) AIS data (transponder) Ship/Manifest/Social Network/Investigative Data Synthetic / Notional (modeling / simulation) Initial Efforts: Proof-of-process ingestion of VIIRS and/or AIS data Development of prototype analytic approaches Development of simple agent-based fishing model Top Image: the internal catalog of data sources resulting from extensive basic research into shipping and IUU Middle Image: An initial DAVE workflow used to pre-process AIS data Bottom Image: TBD: one of the HDF pics from Max A lot of the heavy lift involved understanding the format of both the VIIRS data and the AIS data, and in particular, rectifying coordinate systems such that the data could be rendered in a consistent manner. One of the main challenges with VIIRS data was in dealing with artifacts such as cloud cover, reflection of moon-light, etc. Max was able to figure out a way to bin the intensity data so that lights associated with cities could be used as a reference, enabling the masking of noise in the VIIRS data.

Using DAVE/ICASA to Explore IUU Data Results to Date Open-source search, discovery, and characterization of problem-set data and approaches Ingestion / visualization of AIS data Ingestion / visualization of VIIRS data Incorporation of ABM-synthesized data into DAVE along-side real world data Initial analytic development Future Work Ingestion of additional data sets as available (closed-source, social-network, etc.) Advanced analytic approaches (situational awareness / alerting Validate agent-based models to real-world data Upper Left: AIS Data for a test region NE of Indonesia. We were trying to find a bounding box for which both AIS and VIIRS data were available in an attempt to build a analytic for detecting potential IUU vessels. More work would be needed on finding data sets that have enough data points to take the work much further (or the ability to get more than what is easily available from public sources) Upper Right: VIIRS data (normalized) as ingested and visualized in DAVE for the region surrounding Indonesia Center: One of the workflows as delivered for being able to ingest, process, and visualize AIS and VIIRS data from inside of DAVE Lower Left: Agent-based simulation of fishing (legitimate and IUU). Yellow dots and boxes correspond to simulated AIS and VIIRS data, respectively, red boxes correspond to simulated VIIRS data for IUU vessels. Lighter blue regions indicate higher density of fish. Boats periodically go to ‘port’ and empty their cargo. We are working to incorporate this data with real-world VIIRS data inside of DAVE. Lower Right: A synthetic network created and visualized inside of DAVE, to at least demonstrate the ability to perform analysis on multiple modes of data.

DAVE Video Clip Here

Institute for Complex Additive Systems Analysis (ICASA)