Summary and Schedule
Prerequisites
- Familiarity with MS Excel
- A spreadsheet editor such as LibreOffice, Microsoft Excel, or Google Sheets, able to read .xlsx files.
- A text editor such as Notepad++, or Textpad
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Introduction to FAIR Data Management for Long-term Agriculture Experiments | What will I learn from this lesson? |
| Duration: 00h 12m | 2. Why should we share long-term experiment data |
Why should you share data? What are the motivations for sharing LTE data? |
| Duration: 00h 24m | 3. FAIR Principles for long-term agricultural experiments data |
What are the FAIR Principles? Why should we care about FAIR principles for LTE data? Are FAIR data and Open data the same? |
| Duration: 00h 36m | 4. Metadata for long-term experiments |
What is metadata? Why do we need metadata for? What metadata should we collect for LTEs? |
| Duration: 00h 48m | 5. Organising data for long-term experiments | What are the principles for using spreadsheets for good data organisation? |
| Duration: 01h 00m | 6. Making LTE data FAIR | How do I make LTE data FAIR? |
| Duration: 01h 12m | 7. databases-for-lte-data |
How are databases different from spreadsheets? Why are databases useful for managing LTE data |
| Duration: 01h 24m | 8. Publishing LTE data |
What do you need to do to publish data? Where should you publish data? How do I update published LTE data? |
| Duration: 01h 36m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
Data Sets
This lesson uses four example datasets in MS Excel format and designed to illustrate common problems encountered with Excel. The datasets are based on four real long-term experiments from Kenya, Malawi and the UK, but for the purpose of this lesson, the data has been transformed. The example datasets do not contain real data, so please don’t use it for research!
Download the data zip file and unzip it to your Desktop