Research data management is becoming increasingly important. This is due to the growing variety of data types, formats, and volumes generated by scientific research. Furthermore, there is a rising need to make data accessible and understandable, necessitating the standardizing, managing, and planning of the data life-cycle. As a result, many funding agencies now mandate a data management plan...
Research data management starts with two critical element: how to store the information about research in a systematic way and what to store. The former is often shifted to database solutions without much ado, the latter requires common templates to be constructed for each experiment types. Though database solutions provide a searchable record, they often comes with multiple problems as well....
In this poster we will present basic data structures of the NOMAD (NOvel MAterials Discovery) Lab, the so called base sections. We will explain the three levels of schema, (1) the built in definitions in NOMAD, (2) the general application base sections, and (3) the user specific data schemas. The implementation of theses three levels will be illustrated by the use case of Pulsed Laser...