PREMISE

With PREMISE, our goal is to advance open research data (ORD) practices in Materials Science by adhering to FAIR data principles. We aim to make open and reproducible research an integral part of the scientific process, rather than an extra step before publication. Specifically, we address the challenge of interoperability between data from simulations and experiments, an area lacking established research data management (RDM) practices.

Our approach involves developing machine-actionable metadata standards for seamless interoperability between experimental ELN-LIMS and WFMSs in Materials Science. To showcase our achievements, we will utilize two well-established ORD software platforms: openBIS for experiments and AiiDA+AiiDAlab for simulations. These demonstrations will not only serve as practical models for implementing our ORD concepts and standards in other ELN-LIMS and WFMS but also provide a functional solution for materials science researchers.

Additionally, by integrating our practices into these actively maintained platforms, we ensure their long-term sustainability. Once our funding concludes, the support for these software extensions will transition to their respective development teams.

To validate and refine our concepts, we will apply them to two research cases that heavily rely on experiment-simulation synergy:

  1. Microscopy and Spectroscopy Data Analysis: We will demonstrate the integration of data from experiments and simulations within a unified framework, enhancing data analysis and visualization in microscopy and spectroscopy.
  2. Autonomous Battery Assembly and Testing: We will implement our standards in the context of fully automated robotic experiments executed by a WFMS. Digital twins of experiments and samples will share common formats, standards, ontologies, and location (ELN-LIMS) with simulation data. This approach ensures a high level of reproducibility in results.

Through these examples, we will measure the tangible impact of our developed concepts on high-impact materials science research.