Advancing catalysis research through FAIR data principles implemented in a local data infrastructure – a case study of an automated test reactor

Abstract

Findable, accessible, interoperable, and reusable (FAIR) data is currently emerging as an indispensable element in the advancement of science and requires the development of new methods for data acquisition, storage and sharing. This is becoming even more critical as the increasing application of artificial intelligence demands significantly higher data quality in terms of reliability, reproducibility and consistency of datasets. This paper presents methods for the digital and automatic acquisition and storage of data and metadata in catalysis experiments based on open-source software solutions. The successful implementation of a digitalization concept, which includes working according to machine-readable standard operating procedures (SOPs) is outlined using a reactor for catalytic tests that has been automated with the open source software tool EPICS (Experimental Physics and Industrial Control System). The process of data acquisition, standardized analysis, upload to a database and generation of relationships between database entries is fully automated. Application programming interfaces (APIs) have been developed to enable data exchange within the local data infrastructure and beyond to overarching repositories, paving the way for autonomous catalyst discovery and machine learning applications.