WhaleVis turns centuries of whale sighting data into an interactive map

Newswise – even though they are The largest animals on earthWhale tracking is difficult. So experts often refer to historical whale sighting data for current research. The data set it stores International Whaling Commission (IWC) contains detailed information on commercial whaling – more than 2.1 million records, mostly from 1880 until the IWC banned whaling in 1986. For researchers, however, distilling this data can prove its own challenge.

A University of Washington team has created an online interactive map called WhaleVis that allows whale researchers to visualize IWC data on global whaling catches and whale-watching routes. From this, researchers can estimate the animals' spatial distribution and whaling effort.

By comparing historical data and current information on trends, scientists can better understand how whale populations have changed over time, where they have been, and how best to protect those that are still alive.

The UW team presented his research On October 25, St IEEE VIS Conference in Melbourne (Narm), Australia. The tool is online, but users must have permission from the IWC to access it.

“Scientific data is a really important aspect of big data, but scientists around the world have access to completely different hardware and software. They may not be able to use large servers to process huge data sets quickly,” said the senior author Battle of Leylan, UW assistant professor in the Paul G. Allen School of Computer Science and Engineering. “So when we created WhaleVis, we had to ask: How do we develop a tool that can visualize millions of data points, but that doesn't rely on super-powerful servers?”

The team approached this in several ways. First, instead of plotting more than 2 million points on a global map at once, taxing a computer's processor and creating a “hairball visualization”—an unintelligible mess of lines and dots—the researchers collected whale catches in batches. For example, one big blue dot in the South Atlantic Ocean on South Georgia Island means the catch of 130,611 whales, most of them fin whales. As the researchers continue to develop the tool, they will allow users to zoom in on parts of the map to access more detail.

Second, they built the tool for web browsers, rather than as a standalone application, so that it would run on a variety of computing platforms.

“It was important to make this data accessible so that it could be easily used to generate actionable insights,” said the lead author. Ameya Patil, a UW doctoral student at the Allen School. “Tools like this make information more tangible and understandable.”

WhaleVis came about through the UW Calculations for the environmentAn initiative that brings together computer and climate scientists to collaborate. Trevor Branch, a co-author of the paper and a UW professor in the School of Aquatic and Fisheries Sciences, has been working with the IWC dataset and wanted help visualizing it, particularly in a way to estimate how much effort was spent on each whale. catch. Battle and Patil were looking for a project that combined environmental science with data visualization, and the IWC dataset fit the bill.

“Being able to visualize data like this helps us answer a lot of questions,” Branch said. “For example, it is difficult to distinguish between the two subspecies of blue whales – the massive Antarctic blue whales and the pygmy blue whales, which are about 20 feet shorter. Visualizing the expeditions that caught large whales versus pygmies allows us to clearly and quickly see the boundary between these two subspecies.

In its current iteration, WhaleVis uses the density of expeditions in certain areas to give scientists an approximation of each whale hunt. If researchers can quantify this effort—that is, the time and distance between catches on these expeditions—it will provide a better understanding of the size, density, and location of historic whale populations.

In the future, the team plans to refine the methods for estimating whale effort, normalizing for factors such as the time between captures on each expedition. The researchers also plan to add interactive predictive modeling for different scenarios and apply the methods used on WhaleVis to other animal populations.

“From a researcher's point of view, what's already on the Internet is very, very cool,” Branch said, “and it's beyond anything that's been available before. “It's only when you start playing with the data with beautiful visualizations that you discover some of the anomalies and surprises.”

Zoe Randy, a doctoral student in quantitative ecology and resource management, also co-authored this paper. This research was funded by the Computing Environment Initiative at the University of Washington and the National Science Foundation.

Contact for more information Patil on [email protected]fight on [email protected]and branch on [email protected].