Harvest Chart by Type/Code
The Harvest Chart visualizes the weekly crop harvest of fruits and vegetables across the United States in an interactive data visualization. The design objective for the project was to answer a simple question: what produce is growing near me right now?
Using weekly crop harvest data reported by the USDA and NASS, along with supplemental crop season data from the NRDC and various state agricultural organizations, the weekly percentage of each crop’s full seasonal yield is visualized in a streamgraph that can be filtered by state and crop type. The Harvest Chart reveals the seasonal ebb and flow of each crop’s availability within a given region, and the aggregate seasonal harvest trends across multiple crops within a region. Each crop is assigned a representative color to be easily identified at a glance, with specific weekly values revealed when hovering over each crop’s stream. When filtering the data across multiple states concurrently (averaging each crop’s yield across states), one can explore crop availability across wider multi-state regions, telling a more comprehensive story of what local produce will likely be available at a farmer’s market during any given week of the year. Multiple sorting options are available, to sort crop alphabetically, by “peak” harvest week, or by crop color.
The Harvest Chart was initially conceived as a print design project, however, after collecting the data (about 110 crops, across 50 states, for each week of the year) and prototyping various visualization approaches, we ended up needing to develop custom software to efficiently and accurately explore various data permutations and visualization approaches. The web application was developed with Django to facilitate the data logic and a simple content management system, and the interface leverages the D3 visualization library. After creating a print design for the crop data of Northeast states in the US, the web application has now been publicly launched for anyone to explore.
The Harvest Chart was created as an experimental side project at Type/Code, a digital product studio, as part of an ongoing series of data visuzlation experiments.
More about the design process: https://medium.com/@thezekiel/designing-a-data-visualization-for-local-seasonal-produce-harvests-12f8b689b584?source=friends_link&sk=ebc18ec498a43d7b93a8035132cd8fe8
The entrant has supplied an additional file [1]
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CreditsZeke Shore - Project lead, Concept, Creative Direction; Chris Hakos - Development; Pei-Yi Ni - Design and Research; Meng Zhang - Design and Research; Michelle Gauthier - Research
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