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Data Management I

learning-objectives

  • Objective 1

  • Objective 2

  • Objective n

Description:

Input Data:

Input

Description

Example

Downloading data from the Discovery Environment

  1. If necessary, log into the CyVerse Discovery Environment.

  2. Click the Data icon (Data Icon) to browse your collection of files in the CyVerse Data Store.

  3. In the top left of the page, you should see your username with a dropdown arrow next to it; Click on your username, then click Community Data in the dropdown menu.

    Tip

    This dropdown menu allows you to navigate between your home directory in the Data Store (i.e. your username), and other CyVerse data collections such as files shared with you (i.e. “Shared with Me”), and files shared by the CyVerse community (i.e. “Community Data”). You may also access files located in your “Trash” folder.

  4. Select Community Data and navigate to the folder which will contain our example data:

    /iplant/home/shared/cyverse_training/cyverse_mooc/XXXXXX

  5. Click (Select) the checkbox next to the folder to select that file.

  6. Click on the More Actions button on the upper right and select the Download option to download the file to your local computer.

    Tip

    We don’t recommend downloading many (more than 10) or large (more than 2GB) files directly from the Discovery Environment since files transferred in this way will make use of HTML protocols which are slow and subject to failure for very large data sets. Cyberduck or iCommands (discussed below and in the Data Store Guide) are recommended for these uses.

Output/Results

Output

Description

Example

Self Assessment Questions

Question

Q1. What do the letters in FAIR refer to?

  1. Fixable, Assessable, Interpretable, Recyclable

  2. Fast Access In Repetition

  3. Findable, Accessible, Interoperable, Reusable

  4. Fixable, Automated, Intersectional, Reducible

Answer

Correct answer is C

Question

Q2. True or False, is FAIR data is the same as Open data?

Answer

False

Question

Q3. Which of the following are NOT true of the process of making your data FAIR?

  1. It will be the same regardless of discipline

  2. It may require some technical skills

  3. It can be easier with CyVerse

  4. It happens on a continuum, not a binary FAIR/not FAIR

Answer

Correct answer is A

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