🏋️ Exercise: Exploring the FAIRness of datasets#

Objectives#

  • Familiarise you with finding datasets in different repositories

  • Assessing the FAIRness of a dataset should help you reflect on:

  • What should you do or not do when you publish the data of your project?

  • Did you identify things missing in this dataset that you would definitely provide when you publish yours?

  • Allow you to explore how datasets are published in different repositories

Instructions#

  1. Choose a dataset that interests you just by reading the title

  2. Search for the dataset with the provided title. Feel free to use your usual search methods - no restrictions there

  3. Once you find the dataset (not the publication, not the report, you need to find the dataset) reflect on how Findable, Accessible, Interoperable, Re-usable (FAIR) you think this dataset is.

  4. You can download the following template to guide you with your assessment in this link

  5. If none of the titles we provide are interesting for you, you can search for datasets in the following data repositories using keywords that are relevant for your research field:

Datasets proposed for this exercise#

  • Dataset 1 - “Qualitative coding of 12 semi-structure interviews on food behaviour context and food reporting engagement”

  • Dataset 2: “Benefit of speed reduction for ships in different weather conditions”

  • Dataset 3 - “Mechanical overtone frequency combs”

  • Dataset 4 - “Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach”

  • Dataset 5 - “In-situ observations of water vapour and atmospheric delay from the ground-based GNSS network from 1996 to present”

  • Dataset 6 - “Grasp MultiObject”

  • Dataset 7 - “Mapping the spatial distribution and geographic shift of East African highland banana (Musa sp.) cropping systems in Uganda”