Modern research methods produce large amounts of scientifically valuable data. Tools to process and analyze such data have advanced rapidly. Yet, access to large amounts of high-quality data remains limited in many fields, including catalysis research. Implementing the concept of FAIR data (Findable, Accessible, Interoperable, Reusable) in the catalysis community would improve this situation dramatically. The German NFDI initiative (National Research Data Infrastructure) aims to create a unique research data infrastructure covering all scientific disciplines. One of the consortia, NFDI4Cat, proposes a concept that serves all aspects and fields of catalysis research. We present a perspective on the challenging path ahead. Starting out from the current state, research needs are identified. A vision for a integrating all research data along the catalysis value chain, from molecule to chemical process, is developed. Respective core development topics are discussed, including ontologies, metadata, required infrastructure, IP, and the embedding into research community. This Concept paper aims to inspire not only researchers in the catalysis field, but to spark similar efforts also in other disciplines and on an international level.This publication is part of a Special Collection on "Data Science in Catalysis". Please check the ChemCatChem homepage for more articles in the collection.
The Front Cover illustrates the dynamics and complexity of catalysis. Handling data in catalysis research in a sharable and re‐usable way is an unsolved challenge. A concept is proposed by the initiative NFDI4Cat, a consortium in the German NFDI (National Research Data Infrastructure), that serves all aspects of catalysis research. Indicated in the picture is a vision of integrating all research data along the catalysis value chain, from molecule to chemical process. In their Concept, C. Wulf et al. discuss core topics and challenges. More information can be found in the Concept by C. Wulf et al.
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