This tutorial is dedicated to the NOMAD artificial-intelligence (AI) toolkit, the platform for running (jupyter) notebooks to analyse with AI tools the data contained in the NOMAD Archive.
We will cover, in an interactive, hands-on fashion, the several aspects of the AI-toolkit: the query over the NOMAD Archive via the NOMAD API, the basic notebooks for learning AI methods, and the advanced notebooks, where the workflow of relevant publications, in which AI is applied to materials science, can be interactively reproduced and further explored. Furthermore, we will introduce the local AI-toolkit app that allows to run a local version of the notebooks, e.g., to combine own data with the NOMAD Archive data.
At the end of the first day, few tutorial notebooks will be suggested to be perused by the participants before the second day starts. In the second day, break-out rooms will be organized, and in each room one of the selected tutorial notebooks will be discussed.
|March 9 2022
|March 10 2022
John Henry Scott: Data-Centric Materials Science - The Critical Role of ELNs
José Márquez: Setting up eLabFTW for a simple lab
10:00 & 16:00 CET
Mark Greiner: ELNs in FAIR data management
Sherjeel Shabih: Integrating eLabFTW and NOMAD
10:30 & 16:30 CET
Christoph T. Koch: Demonstration of the eLabFTW and NOMAD in daily use
Markus Scheidgen: NOMAD ELN - ELN features integrated into NOMAD
11:15 & 17:15 CET