Tidy data (part 1): How to structure your data

We all know what well structured folders and data look like when we see them, but putting this into practice can sometimes be hard. This course will teach you the basic principles of structuring your data. Key parts are deciding on the correct data storage location, a good folder structure, file naming conventions and (semantic) file versioning. Last but not least, creating an overview of your data will make it easier to locate what you are looking for quickly.

At the end, we will put the theory into practice with a hands-on (applying these techniques to a fictive research example or on your own data).

After this session, you will learn how to make your data well-structured. This makes it easier for you to understand your data and increases efficiency and reproducibility! Files will actually make sense (no more "final_final_really_final_v2.doc"), and a squirrel will be jealous of how organized your stash is!

Not convinced yet? Some other reasons to structure your data are as follows: it avoids disaster, enables continuity in your work, and increases reuse (there is no need for recreation when the original version can be found). For more selfish reasons to work reproducibly, see Markowetz (2015).

Learning outcomes

After attending this training, participants will...

• be aware of the correct data storage locations for your research;
• understand best practices in structuring data;
• be able to implement best practices in folder structure, file naming and file versioning;
• be able to collaborate easier.

For whom?

• researchers
• 16 places available

When and where?

• December 5, 2024 - 10:00-12:00
• campus Diepenbeek, building D, TBD

Registration?

• Register here until November 27, 2024.
• After the registration deadline has passed, you will receive a calendar invite with all practical information for this course.
• Please cancel your registration at least one week in advance in case you cannot make it by sending an email to rdm@uhasselt.be (cf. cancellation policy).

Acknowledged by Doctoral Schools?

• DS Sciences & Technology: acknowledged as 'Research management' - course/workshop at developing general research skills.
• DS Behavioral Sciences & Humanities: acknowledged as 'Research management & communication skills' - course/workshop aimed at developing research (management) skills.
• DS Health & Life Sciences. For PhD students of the Doctoral School of Health & Life Sciences, a combination of different sessions (adding up to a half/full day) can be acknowledged together as (half) a transferable skills course.
• The training will be added automatically to the doctoral portfolio of the PhD students who signed the attendance list.