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FAIRmat Tutorial 8: Using NOMAD as an Electronic lab notebook (ELN) for FAIR data

<p>Approaching the era of big data-driven materials science, one crucial step to collecting, describing, and sharing experimental data is the adoption of electronic laboratory notebooks (ELN). At present, most synthesis data are not structured comprehensively or not even stored digitally but in handwritten lab books. The&nbsp;<a href="https://www.fairmat-nfdi.eu/fairmat" target="_blank" rel="noopener">FAIRmat project</a>&nbsp;is offering a solution by developing and operating the open-source software&nbsp;<a href="https://nomad-lab.eu/" target="_blank" rel="noopener">NOMAD</a>. NOMAD provides ELN functionalities that aim for a secure environment to protect the integrity of both data and metadata, whilst also affording the flexibility to adopt new synthetic processes or changes to existing ones without recourse to further software development.</p> <p>In this FAIRmat tutorial, we focus on the usage of NOMAD as an ELN which enables the users to generate data following the FAIR principles. We will show how we adopted NOMAD to capture data from synthesis and experiment and make use of an automated data workflow. The key point here is writing a data schema and its implementation in NOMAD. After defining the used terms, we will start explaining this process by writing a simple schema and then go on to more advanced usage of NOMAD, e.g. using the build in csv/xlsx-file parser, automatized data visualization, adding extra functionality by usage of base classes, referencing to other data entries in NOMAD, and searching your ELN data. The tutorial is aimed at both scientists new to NOMAD and structured data as well as data stewards. Each lecture of the tutorial will be followed directly by a Q&amp;A session and a hands-on tutorial.</p> <p><strong>Disclaimer:</strong> NOMAD is being continuously developed based on input and feedback from the scientific community. Hence the features, services or interface may have changed since the time of recording of this video. For up-to-date information please consult our latest tutorials and the NOMAD documentation <a href="https://nomad-lab.eu/prod/v1/docs/">https://nomad-lab.eu/prod/v1/docs/</a></p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4