10–12 Oct 2023
virtual, details will be shared with you after registration
Europe/Berlin timezone

An End-to-End Framework for FAIR Data in Experimental Materials Science

Instructors: Nick Garabedian (KIT), Martin Held (Hereon), Ilia Bagov (KIT), Fabian Kirchner (Hereon)

Date: 12 October 2023
Time: 09:30 - 12:00
Room 1

The attributes of FAIR data facilitate, amongst others, an easier reproducibility of research experiments, and allow the more efficient linking of datasets from different research groups, institutes, and even scientific fields.

The following workshop presents a software framework and workflow, built within the scope of the Helmholtz Metadata Collaboration project called MetaCook, to expand a prior proof-of-concept and to turn it into a daily lab routine. Its purpose is to enable the generation, storage, and publication of FAIR datasets in the field of materials science. Additionally, in the workshop, the modularity of the framework will be exemplified by showcasing similar workflows with different software solutions.

The centrepiece of the framework is a software tool called VocPopuli. It enables the development of FAIR controlled vocabularies in a collaborative fashion. These vocabularies describe the experiments of interest for a given group, as well as, all other equipment, processes, and data which pertain to them. Afterwards, the vocabularies can be used by various other research data management tools. During the workshop example vocabularies will be used to create data entry templates with the software solutions Kadi4Mat, Herbie, and FS-DigitalBook. These three applications offer different functionality but the use of FAIR vocabularies ensures the semantic interoperability of the results. Building on all this, the workshop will finish by showing the chain of FAIR data production up to its publication on the open repository Zenodo.

Target group

Any scientists interested in implementing workflows for FAIR data production.
Objective of Workshop: The main goal of this workshop is to introduce researchers coming from any degree of FAIR data awareness into available methods for FAIR data collection.

Prerequisites 

It would be advantageous if participants have ideas about the contents of vocabularies that pertain to their research. Existing comparable vocabularies can also be helpful.

Registration

Register here