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Insight Hub

Central dashboard for research intelligence and analytics

Insight Hub

The Insight Hub is your central command center for research intelligence. It brings together analytics, visualizations, and AI-powered insights from across your systematic reviews and research projects.


Overview

The Insight Hub provides a unified view of your research landscape, helping you understand patterns, track progress, and make data-driven decisions about your evidence synthesis work.

FeatureDescriptionBenefit
Analytics DashboardReal-time metrics and KPIsMonitor review progress at a glance
Trend AnalysisPublication and citation trendsIdentify emerging research areas
Quality MetricsRisk of bias summariesAssess evidence quality quickly
Team PerformanceCollaboration statisticsOptimize team workflows

Dashboard Components

1. Review Progress Overview

Track the status of all your systematic reviews in one place:

  • Active Reviews: Currently in progress with completion percentages
  • Pending Actions: Items requiring your attention
  • Recent Activity: Latest updates across all projects
  • Milestone Tracking: Key deadlines and achievements

2. Evidence Landscape

Visualize your research evidence through interactive displays:

VisualizationWhat It Shows
Heat MapsStudy distribution by topic, year, or region
Bubble ChartsStudy characteristics and quality indicators
Timeline ViewsPublication trends over time
Geographic MapsStudy locations and populations

3. Quality Summaries

Aggregate quality assessments across your reviews:

  • Risk of Bias Distribution: Overall RoB across included studies
  • GRADE Certainty: Evidence certainty by outcome
  • Quality Trends: How quality varies by publication year
  • Methodological Patterns: Common strengths and limitations

Key Features

AI-Powered Insights

The Insight Hub uses artificial intelligence to surface important patterns:

Smart Alerts: Receive notifications when the AI detects significant patterns, anomalies, or opportunities in your research data.

Automated Insights Include:

  • Unexpected clustering of study findings
  • Potential publication bias indicators
  • Underrepresented populations or interventions
  • Emerging research themes

Comparative Analytics

Compare metrics across multiple reviews:

MetricComparison Capability
Screening efficiencyTime per study, agreement rates
Data extraction accuracyInter-rater reliability
Review timelinesPhase durations, bottlenecks
Team productivityIndividual and group statistics

Custom Dashboards

Create personalized views for different needs:

  1. Researcher View: Focus on methodology and findings
  2. Manager View: Emphasis on timelines and resources
  3. Executive View: High-level summaries and KPIs
  4. Auditor View: Quality assurance and compliance

Using the Insight Hub

Getting Started

  1. Navigate to Knowledge SuiteInsight Hub
  2. Select the reviews to include in your dashboard
  3. Choose your preferred visualization layout
  4. Configure alert preferences for AI insights

Customizing Your View

Widgets Available:

  • Progress bars and completion metrics
  • Interactive charts and graphs
  • Data tables with sorting and filtering
  • AI insight cards
  • Quick action buttons

Layout Options:

  • Drag-and-drop widget arrangement
  • Collapsible sections
  • Full-screen focus mode
  • Multiple saved layouts

Exporting Insights

Export your analytics for presentations and reports:

FormatBest For
PDFFormal reports and documentation
PowerPointPresentations to stakeholders
CSV/ExcelFurther analysis in spreadsheets
ImagesEmbedding in manuscripts

Best Practices

Effective Dashboard Use

  1. Regular Check-ins: Review the dashboard daily during active reviews
  2. Set Meaningful Alerts: Configure notifications for important thresholds
  3. Compare Across Projects: Use comparative views to identify best practices
  4. Share with Stakeholders: Export views for team meetings and reporting

Acting on Insights

When the AI surfaces insights:

  • Investigate Anomalies: Dig deeper into unexpected patterns
  • Document Decisions: Record rationale for methodology choices
  • Adjust Strategies: Modify approaches based on efficiency data
  • Celebrate Progress: Acknowledge team achievements shown in metrics
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