A Unified Research Data Infrastructure for Catalysis Research – Challenges and Concepts

Abstract

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.

Standardized Data, Scalable Documentation, Sustainable Storage – EnzymeML As A Basis For FAIR Data Management In Biocatalysis

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Electrochemical CO2 reduction toward multicarbon alcohols - The microscopic world of catalysts & process conditions

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