Summary and Schedule
This is a new lesson built with The Carpentries Workbench.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Introduction to Data Management |
Why is data management important? How do computers organise files and folders? What is a file system? How can I use a graphical file explorer to navigate my data? |
| Duration: 00h 30m | 2. Choosing the Right File Structures |
Why does folder organisation matter? What makes a good folder structure? How can I identify problems in an existing file structure? How can I move, rename, and delete folders using a file browser? How can I organise a project so that it is easier to understand and maintain? |
| Duration: 01h 15m | 3. Naming Files Well |
What makes a good filename? How much information should be included in a filename? Why are naming conventions important? How can filenames support batch processing and automation? How can I rename one file or many files using a graphical file browser? |
| Duration: 02h 00m | 4. Documenting Your Data |
How can I remember what my data is and where it came from? What information should I document about a project? Where should documentation be stored? What is a README file? How can I create project documentation using a graphical file browser? |
| Duration: 02h 45m | 5. Choosing Where to Store Your Data |
Where should I store my research data? What are the advantages and disadvantages of different storage options? How can I make data accessible to collaborators? How can I ensure research data is backed up and secure? What additional considerations apply to sensitive or restricted data? How can I make data accessible when publishing research? |
| Duration: 03h 30m | 6. Storing and Transferring Data Efficiently |
Why do some datasets take up more storage than others? How can I measure the size of my data? What is file compression and when should I use it? When is changing file format an appropriate solution? What are the best ways to transfer data between collaborators? How can I reduce storage requirements without losing important information? |
| Duration: 04h 20m | 7. What to Store and When to Remove |
How do I decide which research data to keep and which to delete? How long am I required to retain my research data? What are the risks and hidden costs of keeping everything forever? How do I permanently delete data across different systems? |
| Duration: 05h 15m | 8. Best Practices for Tabular Data |
What makes a tabular dataset “bad” or difficult to work with? How do inconsistent column names, missing values, and stacked sub-tables cause errors in research? How can I clean and standardise messy spreadsheet data using standard tools like Excel? How can I track changes and apply version control to data files? |
| Duration: 06h 15m | 9. Choosing a Data Storage Format |
How does a file extension determine how data is stored and
read? What factors should I consider when choosing a data format for my research? What are the differences between discipline-specific and domain-agnostic formats? What are the risks of converting files between different formats? |
| Duration: 07h 15m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
This workshop requires participants to have access to a computer - either laptop or desktop which has graphical file viewer software. This is available by default on Windows, MacOS and most flavours of linux.
If you do not have access to a computer and are attending an in person version of the workshop please check with your instructors running the course so they can find a workable solution. This course may be run in a computer cluster room so long as all participants have login access to the cluster room computers.
Data Sets
Download the data zip file and unzip it to your Desktop. If you have difficulties doing this please ask your instructor for help.