The business community in Oceanus is dynamic with new startups, mergers, acquisitions, and investments. FishEye International closely watches business records to keep tabs on commercial fishing operators. FishEye’s goal is to identify and prevent illegal fishing in the region’s sensitive marine ecosystem. Analysts are working with company records that show ownership, shareholders, transactions, and information about the typical products and services of each entity. FishEye’s analysts have a hybrid automated/manual process to transform the data into CatchNet: the Oceanus Knowledge Graph.
In the past year, Oceanus’s commercial fishing business community was rocked by the news that SouthSeafood Express Corp was caught fishing illegally. FishEye wants to understand temporal patterns and infer what may be happening in Oceanus’s fishing marketplace because of SouthSeafood Express Corp’s illegal behavior and eventual closure. The competitive nature of Oceanus’s fishing market may cause some businesses to react aggressively to capture SouthSeafood Express Corp’s business while other reactions may come from the awareness that illegal fishing does not go undetected and unpunished.
A key element in stopping illegal fishing is holding the people who own nefarious companies accountable. Thus, FishEye is keenly interested in developing visualization tools that work with CatchNet to identify the people who hold influence over business networks. That is especially difficult with varied and changing shareholder and ownership relationships.
FishEye analysts want to better visualize changes in corporate structures over time. Create a visual analytics approach that analysts can use to highlight temporal patterns and changes in corporate structures. Examine the most active people and businesses using visual analytics.
Using your visualizations, find and display examples of typical and atypical business transactions (e.g., mergers, acquisitions, etc.). Can you infer the motivations behind changes in their activity?
Develop a visual approach to examine inferences. Infer how the influence of a company changes through time. Can you infer ownership or influence that a network may have?
Identify the network associated with SouthSeafood Express Corp and visualize how this network and competing businesses change as a result of their illegal fishing behavior. Which companies benefited from SouthSeafood Express Corp legal troubles? Are there other suspicious transactions that may be related to illegal fishing? Provide visual evidence for your conclusions.
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.