EAPS DataMine FAIR (Findable, Accessible Interoperable and Reusable) Climate Data Course

11 modules

About

This is a 1 credit course and it will involve reading, discussion, learning principles FAIR data science principles and applying them within a computational environment.  The course should not be too much work, but it will still be challenging and take effort, so I recommend that you actively engage in the learning, including asking questions (in class or via email) and taking notes, and staying up to date on the homeworks/assignments.  I understand that everyone’s schedule is busy and things happen. So please contact me when something is going on if it is impeding your ability to do well in the class, I’m happy to show some flexibility, but communication is key.  You can always email me at huberm@purdue.edu and I will try to respond within 48 hours, if not sooner.

Features
Type Course
Level Foundation

Registration is required to access materials.

Modules

  • EAPS DataMine FAIR: Overview of FAIR Science

    Module 1

  • EAPS DataMine FAIR: Practical Unix Skills

    Module 2

  • EAPS DataMine FAIR: Jupyter Notebooks 1

    Module 3

  • EAPS DataMine FAIR: Jupyter Notebooks 2

    Module 4

  • EAPS DataMine FAIR: R examples 1

    Module 5

  • EAPS DataMine FAIR: R examples 2

    Module 6

  • EAPS DataMine FAIR: Containers and Virtual Environments

    Module 7

  • EAPS DataMine FAIR: Identifiers

    Module 8

  • EAPS DataMine FAIR: PURR and Other Repositories

    Module 9

  • EAPS DataMine FAIR: Getting our code and data together

    Module 10

  • EAPS DataMine FAIR: Putting your data and code "out there"

    Module 11

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