Mimir

Welcome to Mimir. This book explains a method of handling data production for smaller research laboratories in order to produce robust, annotated and machine-friendly data that follows the FAIR principles.

It explains ways to:

• Manage samples in day-to-day work;
• Write clear, complete and concise analysis protocols;
• Write relevant metadata for all kinds of data;
• Provide guidelines on how to handle long-term storage of produced data;

This book is aimed at smaller laboratories without an institutional open-data, FAIR-data or open-science support framework, so that they may start producing more collaborative, robust and cleaner data for both themselves and the wider public.

The book is divided in sections and it is meant to be read both from top to bottom and as a handbook, depending on your needs:

• The Background section contains information useful to get started if you have no idea what FAIR means, why you should produce FAIR data and other required background knowledge.
• The Before experiments section outlines things that should be handled before starting experiments, both in general (i.e. systems that should be in place) and in the specific (i.e. what steps should be performed before every experiment).
• The At the bench section outlines what should be done or kept in mind while working specifically at the bench.
• The At the PC section covers the practices that should be implemented while handling data after the measurements on the samples have been completed.