Open Science and Data Platform

OSDP serves members of the public and scientific communities who need to find, compare, and understand information across many record types. The scale of the platform made navigation and filtering a product problem, not just a visual one.

The design direction treated discovery as a sequence: establish what is available, help people narrow the field, then preserve enough context to understand the result.

People had difficulty retrieving useful information because:

• Navigation and filters exposed too much complexity at once.
• Large result sets created information overload.
• Important context was separated from the records people were trying to understand.

The result was a system that contained valuable information but made the path to that information harder to follow.

I led the UX work across information architecture, interaction design, filter behavior, and accessibility. I worked with the design and development team to turn a broad platform problem into clearer navigation patterns and reusable components.

My contribution was not only to redesign individual screens. It was to define how discovery should work across the platform as the number and type of records continued to grow.

• Make navigation and retrieval clearer across datasets, publications, monitoring stations, development activities, and content collections.
• Reduce the amount of information people need to process at each step.
• Preserve useful record context while helping people narrow large collections.
• Treat accessibility as part of the interaction model rather than a final compliance check.

Understand the information model

I mapped the relationships between record types, collections, filters, and contextual details to identify where the existing experience asked people to make too many decisions at once.

Test progressive disclosure

I used progressive disclosure to stage complexity. People could begin with a broad collection, refine the result set, and reveal additional context when it became useful.

Benchmark familiar patterns

I reviewed comparable data platforms, including Kaggle, to understand how other systems made large collections searchable without hiding important information.

Design for access from the start

Accessibility shaped the component direction and interaction patterns throughout the work. The goal was to make the system easier to navigate and understand for a wider range of people, not to add a separate accessibility layer after the interface was complete.

Make the information architecture visible

The platform needed to explain how its collections related to one another. Clearer navigation and record pathways helped people understand where they were before asking them to filter or compare results.

Reveal complexity in stages

The filter experience was designed to expose useful choices progressively. This reduced the initial cognitive load while keeping deeper refinement available for people who needed it.

Keep context close to the record

Finding a result was not enough. People also needed enough surrounding information to understand what the record represented and whether it was relevant to their task.

The documented outcome was a redesigned direction for the OSDP homepage, filter system, and site-wide information architecture, supported by more progressive and accessible interaction patterns.

The current project record does not include verified task-time, satisfaction, or adoption measurements. I am keeping those outcomes open rather than presenting intended improvements as measured results.

• Progressive disclosure is a system behavior, not just a component pattern.
• In large information systems, context is part of findability.
• Accessibility decisions become stronger when they shape the interaction model from the beginning.
• Good information architecture reduces the amount of interface explanation people need later.