Use case #2Organising Laboratory Data Workflows

How should we store and process raw laboratory data? How do we replace copy and paste of datasets with reproducible, reliable and harmonised data organisation and processing workflows?

The context

The safe storage of output files from the many pieces of electronic equipment in the modern laboratory is not trivial. Data generated by equipment of different ages, complexity and using very different software and reporting formats needs to be saved, without laborious and error-prone manual copy-pasting and in a secure and traceable manner for future access and use.

The challenge

Establish an automated process to upload the output raw files from the equipment into a cloud-based system that is platform independent in order to make the data easily transferable. The solution should allow the user to examine the datasets online or to access them easily via API linking. Furthermore, it should support annotation of the uploaded datasets, thereby ensuring an easy starting point for researchers who are not directly involved in data generation but would like to work with the uploaded datasets.

The solution

First, we outlined the general steps involved and provided a detailed procedure for EdelweissDataTM implementation. Our workflow offers considerable advantages over current practices of data storage and sharing. To facilitate the usage of proposed workflows, Jupyter Notebooks handle the datasets generated in validated test methods for skin sensitisation.