In Oceanus, island life is defined by the coming and going of seafaring vessels, many of which are operated by commercial fishing companies. Typically, the movement of ships and goods are a sign of Oceanus’s healthy economy, especially in the fishing business. But mundane routines can be disrupted by a major event. Analysts at FishEye International, a non-profit organization that aims to find and prevent illegal fishing, need your help to better understand one such event.
FishEye has learned that SouthSeafood Express Corp has been caught fishing illegally. The scandal caused a major disruption in the close-knit fishing community. FishEye has been collecting data on ship movements and shipping records in hopes that they could assemble a cohesive store of knowledge that will allow them to better understand local commercial fishing behavior. FishEye processed open-source and commercial vessel tracking and shipping records into CatchNet: the Oceanus Knowledge Graph. Analysts examine and correct data as it is loaded but need your help to create analytical capabilities for this data.
FishEye analysts need your help to perform geographic and temporal analysis of the CatchNet data so they can prevent illegal fishing from happening again. Your task is to develop new visual analytics tools and workflows that can be used to discover and understand signatures of different types of behavior. Can you use your tool to visualize a signature of SouthSeafood Express Corp’s illegal behavior? FishEye needs your help to develop a workflow to find other instances of illegal behavior.
FishEye analysts have long wanted to better understand the flow of commercially caught fish through Oceanus’s many ports. But as they were loading data into CatchNet, they discovered they had purchased the wrong port records. They wanted to get the ship off-load records, but they instead got the port-exit records (essentially trucks/trains leaving the port area). Port exit records do not include which vessel that delivered the products. Given this limitation, develop a visualization system to associate vessels with their probable cargos. Which vessels deliver which products and when? What are the seasonal trends and anomalies in the port exit records?
Develop visualizations that illustrate the inappropriate behavior of SouthSeafood Express Corp vessels. How do their movement and catch contents compare to other fishing vessels? When and where did SouthSeafood Express Corp vessels perform their illegal fishing? How many different types of suspicious behaviors are observed? Use visual evidence to justify your conclusions.
To support further Fisheye investigations, develop visual analytics workflows that allow you to discover other vessels engaging in behaviors similar to SouthSeafood Express Corp’s illegal activities? Provide visual evidence of the similarities.
How did fishing activity change after SouthSeafood Express Corp was caught? What new behaviors in the Oceanus commercial fishing community are most suspicious and why?
Note: the VAST challenge is focused on visual analytics and graphical figures should be included with your response to each question. Please include a reasonable number of figures for each question (no more than about 6) and keep written responses as brief as possible (around 250 words per question). Participants are encouraged to new visual representations rather than relying on traditional or existing approaches.
Reflection Questions
Which version of the data did you choose to work with and why? Did you download more than one version and change course during the challenge?
Given the task to develop visualizations for knowledge graphs, did you find that the challenge pushed you to develop new techniques for visual representation?
Did you participate in last year’s challenge? If so, did your experience last year help prepare you for this year’s challenge?
What was the most difficult part of working on this year’s data and what could have made it more accessible?
VAST 2024 Submission Instructions
All VAST data is fully synthetic. Any resemblance to real people, places, or events is purely coincidental. Some elements of the 2024 VAST Challenge resemble data released for the 2023 VAST Challenge. Participants should not assume that there is any continuity and should not use any earlier or any external data for their submission. Mini-Challenge participants should only use data supplied for this mini-challenge in their submission. Data from other challenges should not be combined, except in the Grand Challenge.