What is in it for me?

You might still not be convinced that the game is worth the candle. Your method for handling data might be perfectly fine for you: you've never lost any data, and you can understand your files well.

However, consider that you do not live in a bubble. You eventually need to:

• Share your work with others;
• Use other's data;
• Combine different datasets of your own work;
• Handle other people's data for, e.g., quality check;
• Find new people who are as interested to your experimental problem as you are.

If everyone produced FAIR data, all of these steps would be extremely easy to carry out and, in some cases, automatic.

Once you embrace FAIR data, you contribute and can tap into a large amount of data present online for your own reputation and benefit. Working with FAIR data is also more efficient: data analysis is faster with such data, and writing papers becomes a breeze.

If all of this still is not enough to convince you, consider that there are efforts to move away from bibliometric indexes to measure a researcher output and therefore evaluate them. These efforts, like COARA, will most likely replace such measures with things like FAIR quantification, research integrity, etc... Being ready for these changes will undoubtedly give you an edge in the future.