The waters off Alaska in the North Pacific support the largest fisheries in the nation and provide sustainably caught seafood for the U.S. and the world. In 2015, Alaska’s fisheries sustainably harvested roughly over three million tons of fish and shellfish worth $4.3 billion dollars after processing. These fisheries include the largest U.S. fishery, pollock, and the renowned Bering Sea king and snow crab fisheries (from “The Deadliest Catch” TV show), and collectively represent over 60 percent of the total domestic production of seafood in the U.S. These fisheries support the economies of over 347 communities in Alaska and are integral to the maritime industry of greater-Seattle and the Pacific Northwest. Management of these fisheries employs the most innovative and sophisticated economic tools in the industry, and regulatory reporting requirements generate a wealth of social and economic data. As a resource for fisheries scientists, policymakers, and the public, the Economic Status of the Groundfish Fisheries of Alaska and the Economic Status of the BSAI King and Tanner Crab Fisheries reports are produced annually, using these data to characterize and interpret the state of Alaska fisheries.. The reports are produced using SQL, R/Sweave, ggplot2, but are currently limited to LaTeX documents containing static figures and tables of statistics.
The goal of this project is to assist NOAA’s Alaska Fisheries Science Center in developing an online platform employing advanced data visualization tools to enable stakeholders to access and understand information about the social and economic status and trends in Alaskan fisheries. The project would include development of interactive visualizations for non-technical audiences to explore relational, spatial, time-series, and other dimensions of the available data. Development will draw on insights from the visualization and analytics literature to optimize the form and content of visualizations for the intended audience and the nature of the data available. It is anticipated that the interactive user interface would employ software tools within or compatible with the R programming environment (e.g. rCharts, ggplot2, plotly, shiny), but alternatives can be considered.