Redesigning Signals — Turning Research Integrity into a User Experience
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Overview
In research, credibility isn’t optional — it’s oxygen.
But even the most valuable insights can get lost when the interface doesn’t guide understanding.
Signals was built to safeguard that credibility — a data intelligence platform that tracks retractions, citation patterns, and authorship integrity across global academic publications. Its mission: help researchers, publishers, and institutions identify high-risk studies and maintain transparency in science.
When the Signals team reached out to Product Rocket, their product already carried deep purpose — but its experience lagged behind its potential. Dense data layouts, small typography, and unstructured hierarchies made navigating critical research information feel harder than interpreting it.
Our goal was clear: transform Signals into a product that not only informs but empowers — one where research integrity feels both accessible and actionable.
The Challenge — When Complexity Clouds Credibility
For scientists, every click is a claim. But on the original Signals platform, clarity often lost to complexity.
Through our initial UX audit, we uncovered critical friction points that hindered trust and comprehension:
High visual clutter: Overlapping tags, bright accents, and dense layouts led to visual fatigue.
Lack of hierarchy: Each element shouted equally loud — making it hard to tell what mattered most.
Small, dense typography: Text-heavy lists required effort just to read, let alone interpret.
No filtering or sorting: Users scrolled endlessly to find specific studies, authors, or retraction types.
Redundant indicators: Overuse of “RETRACTED” labels created noise instead of clarity.
Inefficient navigation: A single, continuous page displayed everything — from citations to authors — with no clear structure.
Signals held enormous data integrity value. But its UX unintentionally created barriers for the very audience it aimed to serve — researchers, librarians, and scientific analysts.
To fix this, we needed to design for two things that rarely coexist easily: credibility and clarity.
Our Approach — Audit. Structure. Refine.
At Product Rocket, redesigns follow a three-phase philosophy: Audit the experience, structure the data, refine for human clarity.
Audit — Understanding the friction behind the facts
We started by mapping the full user journey: how a researcher searches for a paper, cross-checks retractions, or validates citations.
Every click, scroll, and hesitation became a data point.
We studied real metadata reports to understand what users truly care about — retraction reasons, self-citation patterns, institutional affiliations, and citation networks. These priorities became the foundation of our design logic.
Structure — Building hierarchy from chaos
We replaced the flat, endless list with a layered experience.
Core signals (like risk levels and citation counts) were elevated to the top, while deeper data (like author history or retraction notes) became expandable sections.
Our guiding principle:
Show what matters first. Reveal the rest progressively.
Refine — Designing for comprehension, not decoration
Once structure and rhythm were established, we focused on refinement — improving typography, spacing, and visual breathing room.
We softened the background, introduced clearer section dividers, and adjusted line lengths for academic-grade readability.
Every visual choice had a single purpose: make complex data feel approachable, trustworthy, and human.
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Enchantique brands. Where elegance converges with brand brilliance.
Design Solutions
Subtle Page Background
A soft, neutral tone separates main content from the screen edges, giving structure without distraction.
The result: a page that feels calm, focused, and naturally hierarchical — not like a wall of text.
Tabbed Navigation
All information — overview, citations, author data, retractions — once lived on one endless page.
We reorganized it into four logical tabs: Overview, Citing, Cited By, and Author Information.
This modular approach reduced scroll time by over 60% and made context-switching effortless.
Expandable Data Sections
Not every user needs every detail at first glance. We introduced expandable panels for “Retraction Notice,” “Institutional Background,” and “Citation Breakdown.”
This supports both skimming and deep reading — respecting each user’s research style.
Prominent Key Metrics
We added a concise top metrics bar highlighting the essentials:
Risk Level (e.g., High Risk)
Self-Citation Count
Author ORCID Presence
Retraction Count
Citation Graph Preview
Now, researchers can assess reliability in seconds, not minutes.
Filtering and Sorting
The new dynamic filters let users group results by signal type, author, or journal, and sort by Most Cited or Recently Retracted.
Signals evolved from a static database into an interactive research assistant.
Smarter Search Bar
We redesigned the search bar as the product’s true hero.
Now bold, centered, and context-aware (“Search by DOI or ISSN-L…”), it invites discovery rather than demands patience.
Optimized Reading Width
Scientific users read for precision.
We refined text columns to the optimal 50–75 characters per line, creating an academic-grade reading rhythm that increases focus and comprehension.
Results & Impact
Even during beta testing, the redesign produced measurable improvements:
60% faster time to find relevant information.
Higher perceived credibility, as users described the new layout as “more trustworthy.”
Reduced fatigue when scanning multiple retraction reports.
Stronger trust signals, achieved through consistent typography and restrained visual design.
Signals transformed from a dense data archive into a living dashboard of research integrity — faster, calmer, and far more transparent.
At Product Rocket, we believe design isn’t just about aesthetics. It’s about turning complexity into confidence.
In scientific contexts, every visual decision communicates truth or uncertainty. Over-designing can erode trust; minimalism, when purposeful, reinforces it.
We built Signals on five guiding principles
Hierarchy builds trust
When users know what to read first, they instinctively trust the data more.
Progressive disclosure matters
Showing only what’s relevant at first prevents overwhelm.
Accessibility is credibility
Font size, contrast, and spacing directly affect perceived reliability.
Whitespace isn’t empty — it’s functional
It gives the mind time to process and the eyes room to rest.
Consistency scales better than complexity
The new layout easily supports future features like topic clustering or AI-based scoring.
The Broader Impact
The redesigned Signals platform demonstrates how usability and scientific rigor can coexist. It’s proof that clarity doesn’t dilute data — it amplifies it.
Where many research tools drown users in numbers, Signals now guides them through meaning.
It invites trust not by simplifying truth, but by revealing it clearly.
From the first glance, users can see what’s true, what’s questionable, and what demands further scrutiny — all without friction or fatigue.
