January 2024 - August 2025
Redesigning how researchers navigate a complex data table and export viral genomic information
Product designer: me
Subject matter experts: 3
Developers: 2
Product owner: 1
8% increase in help documentation usage
34% increase in filter usage
38% gains in underutilized filters
For users:
Faster task completion
Reduced search and dowload errors
For business:
Reduced filter-related support tickets
Enhanced platform reputation
Project Overview
Redesigning the Results Table — the core feature for viral data search, filtering, and export
The Results Table is NCBI Virus's core feature where thousands of scientists daily search, analyze, and export viral genomic data. With over 25 filters and multiple columns for querying millions of viral sequences, the interface had become difficult to navigate.
As sole designer, I led the redesign to improve how researchers find and export the data they need.
Results Table before
Results Table after
Challenge
Researchers couldn't navigate overloaded filters and columns to view and export data
After years of feature additions, the Results Table had grown to 25+ filters and columns with no clear organization. Researchers couldn't find the filters or identify which columns they needed, spending excessive time searching or missing useful features entirely.
The interface had become a barrier to efficient research, preventing scientists from analyzing and exporting accurate datasets for their studies.
The filters and columns are overwhelming — I can't tell if my data is right.
Bioinformatics Scientist
Problem Discovery
Data analytics revealed disorganized filters, poorly-ordered columns, and wasted space
Data analytics showed:
01
Random filter order:
The 25+ filters in the side panel had no logical structure. High-usage filters were buried in the middle while rarely-used ones sat at the top, ignoring user needs.
02
Column confusion:
Default column arrangements didn't reflect researcher priorities, forcing constant reordering.
03
Unused Shortcuts and Details Panel
Many shortcut links went unused despite occupying valuable screen real estate. Researchers were not aware of the Details Panel's existence, and those who were found it annoying and an extra step in their workflow.
Usage analytics: filters panel, popular searches and details panel
User Insights
Scientists want the most efficient path to filter, analyze, and export their results
User research helped us understand the typical user journey:
Filter/Refine Results → Analyze Data → Export
Scientists want the most efficient path to filter, analyze, and export their results—everything else creates friction.
Based on user interviews and survey results, we identified two additional problems:
04
Unclear functionality for filters and columns:
Researchers didn't understand what filters did, couldn't track which ones they'd applied, and struggled with column customization.
05
Export process confusion:
Too many export options were not transparent for users and didn't reflect the steps they were taking.
User feedback: filters & column organization, download discovery
User feedback: applied filters & table size
User feedback: navigation & column management
User feedback: download flow complexity
Defining Success
Better filter organization, streamlined exports, and reduced support requests
We defined three measurable goals based on the problems we discovered:
01
Better filter organization and discoverability
Filters grouped and ordered in ways that match researchers' mental models, allowing people to find the right filters faster.
02
Streamlined download process
Researchers can navigate through download options more efficiently.
03
Reduced support requests about filters
Reduced support requests about filter location, understanding their functionality, and download processes including bulk download and programmatic access
Results Table prototype demo
Exploring Options
Side panel versus in-column filtering for Results Table
I considered two approaches for organizing the overwhelming filter system:
01
Remove the filter panel entirely and allow people to filter directly within table columns.
02
Keep the filter panel but organize filters based on importance or logical groupings that make sense for researchers.
Option 1: filters within the columns
Option 2: filters in the side panel
Design Solutions
Implementing intuitive filters and columns, clear exports, and focused workspace
I proposed four key improvements based on our research findings:
01
Fixed the filter chaos
Grouped related filters together and ordered them by how often researchers use them.
Renamed filters to match users' mental models. Added explanations for each filter and links to help documentation so researchers understand what each filter does.
Added filter tags on top of the table to show which filters are currently applied, helping researchers keep track of their selections.
Filters fefore
Filters after
02
Reorganized columns logically
Arranged columns in the order researchers need them.
Columns can be reordered by dragging in the selection menu
Selection of columns before
Selection of columns after
Download menu before
Export menu after
03
Streamlined export process
Renamed "Download" to "Export" and moved it to the first position among action buttons.
Made the export pathway transparent so users know exactly what steps are involved before clicking.
Download button before
Export button after
04
Cleaned up the interface, redesigned Details Panel
Removed shortcuts nobody used and added a full-screen mode for the table so researchers can focus on their data without distractions.
Sequence Details are now accessible via the "+" cell instead of clicking the record. This eliminates the extra step that users found annoying and allows clicking on the accession to navigate to a different page as expected.
Details panel access before
Details panel access after
Details panel before
Details panel after
Impact and Insights
Launched core improvements show increased researcher engagement
Impact:
Limited developer resources required gradual rollout over several months. Results show 8% increase in help documentation usage, 34% increase in filter usage, 38% gains in underutilized filters, and fewer support tickets about filter locations.
Key learnings:
Clearer naming and contextual help successfully guide researchers to more effective data discovery. The experience taught me to design within severe technical constraints while still delivering value.
Unifying scattered dashboards to boost researcher insights
Making sense of data through visualizations