CENTRAL ARGUMENT
Environmental conservation and tech-sector development are not mutually exclusive. This project makes that case by using Silicon Valley — the tech hub most Taiwanese people already respect — as a documented precedent for what's currently at stake at Wufen Harbour River (五分港溪), Taipei's last unconcreted natural river bend, threatened by the proposed Beitou-Shilin Technology Park expansion tied to Nvidia's new R&D center.
The question being: what does this coexistence actually look like in practice, and how was it accomplished? Findings will be demonstrated via data visualization, as it's the tool best suited to make that answer comprehensible to a general audience when it turns counts, data, and spatial proximity into something a Taipei resident can see and judge for themselves, rather than take on faith from a complicated written policy report.
Silicon Valley functions here as a precedent, and it's not necessarily predictive of what will happen at Wufen River. Taiwan's regulatory environment, political economy, and ecological baseline differ from the Bay Area's significantly. Precedent-based argument still functions as legitimate and useful evidence to be taken into consideration for policy and/or urban planning.
Taiwanese residents (and potentially policymakers) evaluating the Beitou-Shilin proposal: this necessitates plain language, minimal jargon, and an imagery-forward approach. This project offers something the current debate lacks: a fully sourced, comparative visual case study, rather than an appeal resting on sentiment alone. This gives both audiences a concrete precedent to weigh Beitou-Shilin against, instead of an abstract "economic growth versus nature" framing. However, coming from academia, it should still meet academic rigour and transparency expectations (data notes, sourcing, and explicit limitation statements).
Dual-axis chart — GDP vs. cumulative wetland acreage
Large-scale economic growth and wetland protection coexisted at scale, over time
Waterbird nesting chart — species-level nest counts, 2005–2024
Restored wetland actually functioned as habitat, not just protected on paper
Annotated map — tech HQ proximity to wetland boundaries, with text annotations and imagery highlighting tech-environment alignments
Physical closeness and specific features of this co-existence
Qualitative research (articles, archival documentation) will also be conducted to provide necessary historical context, such as explaining how the Save the Bay movement's organizing tactics translated citizen action into the regulatory shift now visible in the Bay's environmental record.. Time permitting, this project will be supplemented by primary-source interviews (e.g., a current Save the Bay project lead) to add first-person testimony on how citizen organizing translated into the regulatory shift the data shows.
Most data will likely be selected from public-sector or nonprofit organisations with transparent methodology so every number in the project can be traced back to a citable source.
Flourish (dual-axis chart): the tool taught for this kind of continuous time-series work, provides the independent-axis scaling this chart needs.
Canva (annotated before/after imagery): previous familiarity makes this the fastest path to a polished result
ArcGIS StoryMap (maps + spatial narrative): provides precise coordinates, storytelling, and zoom-in interactions that a static chart can't deliver.
Framer (site host): plugins help ensure accessibility across the whole project
CRITERION
EVALUATION APPROACH
Before publishing: what's the strongest objection a skeptical reader could raise, and is it addressed in the visible text? Am I showing the data that best supports my argument, or the data that's actually representative? Does every chart carry a visible citation and a plain-language note on any data cleaning decisions?
Process Reflection Framework
Design and Aesthetics
Contrast-checked against WCAG AA; annotations limited for clarity rather than maximal coverage; one coherent visual system across all pages
Can a reader get the main point without reading the surrounding text? Does the chart avoid implying a stronger causal claim than the data supports (the specific standard set by the professor's feedback)? Are all data transformations (ex. aggregation, "." handling, missing survey years) disclosed?
EVALUATION CRITERIA
Effective Communication