HAB.education

STEAM Education with High Altitude Balloons

Balloon Data Visualization

Historical data visualization tools from HAB.education (2015-2017). These tools demonstrate how high altitude balloon data can be collected, processed, and visualized for educational purposes using interactive D3.js charts.

Flight Data Comparison

Interactive D3.js visualizations comparing balloon flight data from different launches. Click the "Animate?" buttons to see the data visualization in action, just like the original HAB.education site.

Flight Data Comparison

Compare data from our HAB_0 and Loyola launches. Both flights were launched from the same location in Damiensville, IL, about one year apart (March 2015 and April 2016).

Select Axes for Comparison

Loading HAB_0 data...

HAB_0 Launch

Date: March 14, 2015

Location: Damiensville, IL

Max Altitude: 109,113 ft

Duration: ~123 minutes

Loading Loyola data...

Loyola Launch

Date: April 16, 2016

Location: Damiensville, IL

Max Altitude: 106,632 ft

Duration: ~101 minutes

Data Analysis

Temperature Differences

The Loyola launch showed slightly cooler temperatures at ground level (22°C vs 25°C), likely due to seasonal differences between March and April.

Pressure Variations

Both flights show similar pressure-altitude relationships, following the standard barometric formula with slight variations due to weather conditions.

Humidity Patterns

The Loyola launch had higher humidity levels throughout the flight, indicating different atmospheric moisture content between the two launch dates.

Historical Data Tools

Flight Trajectory Analysis

Visualize balloon flight paths, altitude profiles, and landing predictions

  • GPS tracking data
  • Altitude vs. time graphs
  • Wind pattern analysis
  • Landing prediction models

Atmospheric Data Analysis

Analysis of temperature, pressure, humidity, and atmospheric composition

  • Temperature profile analysis
  • Pressure-altitude relationships
  • Humidity variations
  • Atmospheric layer identification

Sensor Data Visualization

Historical data visualization from various sensors and instruments

  • Multi-sensor data overlay
  • Customizable time ranges
  • Data quality assessment
  • Sensor calibration analysis

Data Export & Sharing

Export data in multiple formats for further analysis and research

  • CSV and Excel export
  • JSON data format
  • PDF report generation
  • Open data sharing

Data Processing Workflow

The original HAB.education workflow for processing balloon data (2015-2017):

  • Data Collection: Import data from balloon sensors (CSV, Excel, or other formats)
  • Data Cleaning: Process and clean raw data for analysis
  • Data Transformation: Convert data to "tidy" format for visualization
  • Visualization: Create interactive charts and graphs
  • Analysis: Extract insights and patterns from the data
  • Reporting: Generate reports and share findings

R-based Data Processing

The original workflow used R for data processing:

  • Import data into R (read.xlsx, or convert to CSV)
  • Melt the data frame using timestamp as ID variable (reshape2 package)
  • Add dataframe$cat=HAB_### to melted data frame
  • Append melted dataframe to existing balloon data
  • Rename variables to match existing dataset names
  • Recast data back to normal format

Historical Data Tools

The original HAB.education site (2015-2017) featured interactive data processing tools that allowed users to upload their own balloon flight data in CSV format. These tools enabled students and researchers to:

  • Upload CSV Data: Users could upload their own balloon flight data files for analysis
  • Real-time Processing: The system would automatically parse and validate the uploaded data
  • Interactive Visualization: Generate custom charts and graphs from uploaded data
  • Data Export: Download processed data in various formats for further analysis
  • Sample Data: Access to sample CSV files showing the expected data format

These tools were built using R for data processing and D3.js for visualization, making atmospheric science data analysis accessible to students and educators. The tools supported various sensor data including temperature, pressure, humidity, GPS coordinates, and atmospheric composition measurements.

Educational Resources

Data Collection Methods

Learn about sensors and instruments used in high altitude balloon experiments

  • Temperature and pressure sensors
  • GPS tracking systems
  • Camera and imaging equipment
  • Data logging systems

Data Analysis Techniques

Statistical and visualization methods for atmospheric data

  • Time series analysis
  • Altitude vs. atmospheric parameters
  • Data quality assessment
  • Pattern recognition

Educational Applications

How balloon data can be used in STEAM education

  • Physics and atmospheric science
  • Data literacy and statistics
  • Engineering and design
  • Scientific methodology

Community Resources

Tools and resources for balloon data analysis

  • Open source software
  • Data sharing platforms
  • Educational materials
  • Community forums