Module 4 - Realizing FAIR data#

In this module, we will focus on the realisation of FAIR data. We will explore some best practices and tools that can facilitate the implementation of the FAIR principles.

At the end of this module you should be able to:

  • Understand the importance of good data organisation and be aware of best practices around data organisation

  • Recognize the relevance of documentation and be familiar with diverse tools to document data

  • Identify relevant tools to advance towards FAIR data

  • Discuss data publication, best practices and restrictions

There is also an activity in this module you should complete:

✅ Watch the 📽️ videos about ‘Data organisation’, ‘Data Documentation tools’ and ‘Data access and Data publication’ and complete the corresponding quizzes.

Topic 1: Data Organisation#

In module 3, you learned that ‘Documentation’ is one of the main elements of the FAIR principles. Good data documentation starts with good organisation and file naming of the data of your project!

Good data organisation on your computer or your Project Data (U:) drive will allow you to make the data Findable both for yourself and for your collaborators who have access to the data. Making the data findable also indirectly improves the re-usability of the data. You need to be able to find the data before you can re-use it! Implementing a good folder structure, data organisation and a meaningful file naming convention is a simple first step towards making data FAIR.

In the next 📽️ video, we will go through some best practices to help you organise the data of your project efficiently. These best practices are using a good folder structure, tagging files (if possible) and an appropriate file naming convention to enhance the findability of the data in your directories.

Test your knowledge!#

Topic 2 - Documentation tools#

Now that you know more about how to organise your data and name your files, we can talk about documentation. Documentation is vital to making your work understandable, which is, in turn, necessary for your work to be reusable.

Documentation is important not only for data, but for your projects in general, including the code you write. Your documentation should provide context for your project and its data and should, for example, provide information about the data collection, structure, and ownership.

In the next 📽️ video we will talk about different methods and tools you can use to document projects, datasets, and code. We will also briefly talk about metadata.

Test your knowledge!#

Topic 3: Data access and Data publication#

In the next 📽️ video we will delve more into data access during and after a research project. You will also be introduced to the topic of data publication and data repositories.

Data access is one of the main elements of the FAIR principles you heard about in Module 3. Remember that it is important to reflect about data access at the beginning of your project to ensure that the right people have access to the right data.

One way to make the data of your project Findable and Accessible to a broad audience is to publish it in a data repository. Data repositories help you comply with the FAIR principles and make it easy to apply some of their main elements, such as Licences and Persistent identifiers.

Test your knowledge!#