Overview
King Abdullah University of Science and Technology's Reef Restoration Initiative needed software to track 20,000+ coral specimens across laboratory tanks and ocean nurseries. The existing system relied on CSV uploads, causing constant data lag and errors. I redesigned the platform to mirror how researchers actually work: creating spatial interfaces that match physical nursery layouts and streamlining coral movements from a 15-minute process to under 30 seconds.
Client
DigyCorp
What I did
Product Design
Timeline
Q2 - Q3 2025
The Problem
When I joined the project, I found a system that technically displayed data but gave researchers no way to change it. The existing dashboard showed tanks, corals, and nursery layouts, but every edit required downloading a CSV, opening it in Google Sheets or Excel, modifying the data manually, and uploading it back. Something as simple as moving one coral from one tank to another took 15 to 20 minutes. At a scale of over 17,000 coral fragments spread across 300+ tanks in three separate nurseries, each carrying complex metadata like species, genotype, growth stage, health status, and disease flags from AI powered camera monitoring, researchers were spending more time on data entry than actual restoration work.
The Solution
I spent the first week on site purely observing: how the facilities were structured, how corals moved between tanks and from the sea to on land nurseries, what data researchers tracked, and where their workflows broke down. From there, I designed a spatial interface that mirrored the physical layout of the nurseries one to one. Tanks were arranged in the same grid pattern as the real facility, and each tank's detail page reflected the exact tray arrangement inside it, so researchers could locate any coral the same way they navigated the lab. Every task that previously required a CSV round trip became a direct interaction. Moving a coral was now select, click move, choose a destination tank, confirm. Health monitoring, lineage tracking, disease flagging, and batch operations all became in platform flows. I also designed a built in task management system so researchers could assign and track work without switching to external tools. Task time dropped from 15+ minutes to under one minute, data accuracy jumped from below 80% to nearly 99%, and the research team went from dreading the system to relying on it daily.
Mirroring the real world
Researchers think spatially, "Array A, Tank 3, Tray 19, slot B4." Their mental model isn't a database. It's the physical layout of the facility they walk through every day. I designed the interface to mirror that structure exactly. The navigation follows the building hierarchy, so finding a coral on screen feels the same as finding it in the lab.
Each coral has a digital twin
Each coral in the system carries its own profile showing growth rate, mortality risk, and health status. Cameras mounted in each tank photograph the trays every hour, and an AI image recognition system analyzes the photos to update these metrics automatically. The researchers can see at a glance which corals are thriving and which ones are at risk.
Making movement effortless
The core workflow problem was moving corals between locations. In the old system, this meant exporting data, editing a spreadsheet, and uploading it back, a process that took 15 minutes and frequently introduced errors. I designed a step-by-step interface that mirrors how researchers actually think about transfers. Select the source corals. Choose a destination. Confirm with a visual preview.
Bringing the ocean into the interface
In-situ nurseries presented a different challenge. Unlike laboratory tanks, ocean sites are scattered across a coastline and researchers needed to see where things were geographically. The in-situ view combines a map with a list showing status and capacity for each site. Icons distinguish between structure types using the same visual language the team already uses in their planning documents.
The outcome
The system launched in late 2025. The researchers told us that what used to take 15 minutes now takes under 1 minute, a 15x speed-up. More importantly, they trust the data now, the accuracy jumped to near-perfect. Admin time dropped too, what used to require constant manual cleanup is now largely automated, cutting working hours from 4h to 1h daily, a 4x reduction.
15x faster
Coral transfers
4x less
Admin time
