DataSure 0.4.0

IPA Data Management System Dashboard

DataSure

DataSure is IPA's Data Management System Dashboard - a comprehensive tool for survey data quality monitoring and high-frequency checks (HFCs) in research projects.

Built for data managers, survey coordinators, and research teams, DataSure provides real-time monitoring of survey data quality with interactive dashboards, automated checks, and flexible reporting capabilities.

Key Features

• 📊 Data Quality Monitoring: Real-time dashboards for comprehensive survey data analysis
• 🔍 Automated Checks: 10 specialized quality check modules including duplicates, outliers, GPS validation, and missing data analysis
• 📈 Interactive Visualizations: Charts and maps for data exploration and quality assessment
• 🔗 Multi-Source Integration: Direct SurveyCTO API connection plus CSV/Excel file support
• ⚙️ Flexible Configuration: Project-based settings with customizable check parameters
• 📋 Comprehensive Reporting: Export capabilities for different audiences and formats
• 🎯 Enumerator Performance: Monitor data collection team productivity and quality metrics

Installation

Step 1: Install uv from terminal

# WINDOWS
winget install astral-sh.uv

# MACOS/LINUX
brew install uv

Step 2: Install datasure with uv

# install
uv tool install datasure

# ON WINDOWS: update windows path after installation
uv tool update-shell 

Step 3: verify installation

datasure --version

Getting the latest release

# if datasure is already install, get latest version with
uv tool upgrade datasure

Quick Start

1. Launch the application:

   datasure
   

2. Create your first project and configure data quality checks

3. Import survey data:

   • Connect directly to your SurveyCTO server
   • Upload CSV or Excel files from local storage

4. Monitor data quality with interactive dashboards organized into specialized check modules

5. Generate reports and export results for your research team

System Requirements

• Python: Version 3.11 or higher
• Operating System: Windows, macOS, or Linux
• Memory: Minimum 4GB RAM (8GB recommended for large datasets)
• Storage: 1GB free space for application and data cache
• Internet: Required for SurveyCTO integration and updates

Data Quality Check Modules

DataSure includes 10 specialized modules for comprehensive survey data quality monitoring:

Module	Purpose
Summary	Overall project progress and completion tracking
Missing Data	Identify patterns in incomplete responses
Duplicates	Find and manage duplicate survey entries
GPS Validation	Verify location data accuracy with interactive maps
Outliers	Identify unusual responses requiring review
Enumerator Performance	Monitor data collection team productivity
Progress Tracking	Real-time survey completion monitoring
Descriptive Statistics	Data distribution analysis and summaries
Back-checks	Verification workflow support
Custom Checks	Configure additional quality checks per project

Core Capabilities

Data Import and Management

• SurveyCTO Integration: Direct API connection with form metadata and authentication
• Local File Support: CSV and Excel upload with automatic type detection
• Multi-Project Organization: Manage multiple surveys simultaneously
• Data Preparation: Cleaning and transformation workflows

Interactive Dashboards

• Real-time Monitoring: Live updates as new data arrives
• Customizable Views: Configure dashboards per project requirements
• Export Options: Generate reports in PDF, Excel, and other formats
• Automated Alerts: Notifications for quality issues requiring attention

Performance and Scalability

• High-Performance Processing: DuckDB backend for fast analytical queries
• Large Dataset Support: Optimized for datasets with hundreds of thousands of records
• Intelligent Caching: Reduces processing time and API calls
• Cross-Platform Compatibility: Works on Windows, macOS, and Linux

Getting Started - Application Usage

Using DataSure

Once DataSure is installed, you can begin monitoring your survey data quality:

1. Launch the Application

datasure

The web interface will open in your default browser (typically at http://localhost:8501).

2. Import Data

• Import Data Page: Start here to connect your data sources
• SurveyCTO Integration: Connect directly to your SurveyCTO server with authentication
• Local Files: Upload CSV or Excel files from your computer
• Multiple Datasets: Import and manage up to 10 datasets per project

3. Prepare and Configure

• Prepare Data Page: Preview your imported datasets in separate tabs
• Configure Checks Page: Set up High-Frequency Checks (HFCs)
  • Enter a page name for your quality monitoring dashboard
  • Select the dataset to analyze
  • Configure check parameters and thresholds
  • Save settings to create your HFC page

4. Monitor Data Quality

• HFC Dashboard: Access your configured quality check page
• Interactive Tabs: Each check type has its own tab (Summary, Missing Data, Duplicates, etc.)
• Settings Expanders: Configure specific parameters for each check
• Real-time Updates: Dashboard refreshes as new data becomes available

5. Export and Share

• Generate reports for different audiences
• Export findings in various formats
• Monitor trends over time

Command Line Options

# Show version information
datasure --version

# Launch with custom host/port  
datasure --host 0.0.0.0 --port 8080

# View all available options
datasure --help

Data Storage and Cache

DataSure automatically manages data storage and caching for optimal performance:

Cache Directory Locations

• Development Mode: ./cache/ (in project root)
• Production Mode:
  • Windows: %APPDATA%/datasure/cache/
  • Linux/macOS: ~/.local/share/datasure/cache/

What's Stored

• Project configurations: HFC page settings and form configurations
• Database files: DuckDB databases for processed survey data
• SurveyCTO cache: Cached form metadata and server connections
• User settings: Check configurations and preferences

Cache directories are created automatically - no manual setup required.

Support and Resources

Getting Help

• GitHub Issues: Report bugs and request features
• Email Support: [e-mail]
• Documentation: See RELEASENOTES.md for latest updates

Version Information

• Current Version: See RELEASENOTES.md for the latest release information
• Version History: Track all changes and improvements
• Upgrade Instructions: Follow installation commands above to get the latest version

Contributing

We welcome contributions from the research community! DataSure is developed by Innovations for Poverty Action (IPA) with input from data managers and survey coordinators worldwide.

Ways to Contribute

• Report Issues: Found a bug or have a feature request? Open an issue
• Suggest Features: Share ideas for new data quality checks or workflow improvements
• Share Use Cases: Help us understand how DataSure fits into different research workflows
• Code Contributions: Developers can contribute code improvements and new features

For Developers

If you're interested in contributing code or setting up a development environment, see our comprehensive CONTRIBUTING.md guide which includes:

• Development environment setup
• Code quality standards and testing requirements
• Package building and distribution workflows
• Release process and documentation guidelines
• Technical architecture and development patterns

Community Standards

• Use clear, descriptive language when reporting issues
• Follow our code of conduct and treat all contributors with respect
• Help create a welcoming environment for researchers and developers from all backgrounds

Authors and Acknowledgments

DataSure is developed and maintained by the Global Research & Data Science (GRDS) team at Innovations for Poverty Action (IPA). Contact GRDS at [e-mail].

Core Development Team

• Ishmail Azindoo Baako
• Wesley Kirui
• Niall Keleher
• Dania Ochoa
• Laura Lahoz

License and Contact

• License: MIT License - see LICENSE file for details
• Repository: https://github.com/PovertyAction/datasure
• Organization: Innovations for Poverty Action (IPA)
• Contact: [e-mail]

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DataSure - Ensuring data quality for better research outcomes.