Kifah Owda
Product Live

Ontario Playground Finder

Helping families find playgrounds that actually fit their children — filtered by age group, equipment, surface material and the amenities that decide whether an afternoon works. Built on data the community collects itself.

Children playing on a lakeside playground in Ontario

Inside the app

Browsing, filtering and contributing — the three things a family actually does.

Map view with filters for playgrounds, splash pads and trails alongside recommended parks

Find a Park

Filter by age group, accessibility and amenities, with results on a live map.

Park detail page showing amenities, accessibility rating and parent reviews

Park Detail

Amenities, accessibility and parent reviews for a single park.

Multi-step form for submitting a new playground to the platform

Add a Park

A guided submission flow so the community can grow the map.

The Problem

Google Maps doesn't verify playground listings. There's no age-appropriateness data, no detail on equipment or facilities, and no way to tell a maintained site from a neglected one. Families fall back on asking parenting groups which playground suits a two-year-old — a question that gets answered from memory, one neighbourhood at a time.

The Solution

A dedicated community platform for playgrounds. Every record is collected through a structured field survey, so equipment type, target age group, condition, surface material and amenities are captured consistently — and published somewhere anyone can search before they leave the house.

ArcGIS dashboard showing equipment types by age group, equipment conditions, surface materials and a map of surveyed Ontario parks
The live dashboard — Click to explore it.
Role
Lead product designer and data engineer
Team
Solo
Timeline
2025 — ongoing
Organization
Personal / civic project

Background & Impact

Background

As the Lead Product Designer and Data Engineer, I bridged the gap between complex GIS datasets and human-centric UI — deciding what a parent actually needs to know, then designing a survey volunteers could fill in consistently.

The project started inside the Esri stack: ArcGIS Survey123 for field collection and an ArcGIS dashboard for public exploration. That validated the idea quickly, but the data model outgrew what the platform could express — so I moved the pipeline to fully Python, cleaning, reshaping and publishing the dataset myself.

Impact

Equipment Surveys
49 Equipment Surveys
Verified Parks
10 Verified Parks

Technical Foundation

  • ArcGIS Survey123

    Structured field collection for community contributors.

  • ArcGIS Dashboards

    The public map and breakdowns by age, condition and surface.

  • Python

    Cleaning and reshaping survey responses into the published dataset.

  • SQLite

    Local spatial storage — bounding-box filtering is all the product needs.

  • Figma

    Interface design for the browse, detail and submission flows.

Add a playground to the map

See it for yourself.

Explore the live work behind this case study.