ASABE Technical Library - Case Studies and Modules for Data Science Instruction

1.   Introduction   
Citation:   Copyright 2021  
Authors:   
Keywords:   data driven agriculture, active learning, problem-centered education, data science, agricultural and biological engineering.
(Free Abstract )    (Download PDF)

2.   Analyzing Sensor Data at the Source   
Citation:   Copyright 2021  
Authors:   Sierra Young
Keywords:   data science, instruction, sensors, calibration, measurements.
(Free Abstract )    (Download PDF)    (Course Material Download - 1.58 MB Zip file)

3.   Problem-Centered Data Science Education in the Agricultural and Biological Engineering Classroom: Analyzing Air Quality Index Data in R   
Citation:   Copyright 2021  
Authors:   Natalie Nelson
Keywords:   Active learning, problem-centered education, data acumen, agricultural and biological engineering, wildfires.
(Free Abstract )    (Download PDF)   (Course Material Part A Download - 30.3 MB Zip file)   (Course Material Part B Download - 6.6 MB Zip file)

4.   An Introduction to Automated Visual Sensemaking for Animal Production Systems   
Citation:   Copyright 2021  
Authors:   Divya Handa, Armin Moghadam, Abdullah Sourav, Ryan Jeon, Julia Chen, Joshua Peschel
Keywords:   Computer vision, Machine learning, Livestock, Video, R-CNN, Education.
(Free Abstract )    (Download PDF)   (Course Material Download - 1.01 GB Zip file)

5.   Row-Crop Field Machinery CAN Bus Data Collection   
Citation:   Copyright 2021  
Authors:   Santosh Kumar Pitla, CheeTown Liew
Keywords:   Machinery, Row-crops, CAN bus, Data, Analytics, Hands-on activities.
(Free Abstract )    (Download PDF)   (Course Material Download - 3 MB Zip file)

6.   Teaching Geospatial Programming and Data Science to AgriScience Students: Analyzing Real-world Weather Data in ArcGIS Notebooks   
Citation:   Copyright 2021  
Authors:   Dharmendra Saraswat, Gang Shao
Keywords:   Ag Informatics, data wrangling, agriscience, weather network data, interpolation, GIS.
(Free Abstract )    (Download PDF)   (Course Material Download - 22 MB Zip file)

7.   Python Programming in Digital Agriculture   
Citation:   Copyright 2024  
Authors:   Sneha Jha, James V. Krogmeier, Dennis R. Buckmaster, Ph.D., Andrew David Balmos
Keywords:   Data Analytics, Digital Agriculture, GitHub, Public Datasets, Python programming language, VS Code.
(Free Abstract )    (Download PDF)   (GitHub link to course material)