Open Data in Catalysis: From Today's Big Picture to the Future of Small Data - Mendes, Pedro S. F.; Siradze, Sébastien; Pirro, Laura; Thybaut, Joris W. (ChemCatChem, 2021)
Open science and data are yet to make a real breakthrough and research policies will have a critical role in it. The history and general context around open data is hence firstly addressed, including how researchers perceive the existing incentives, leading to recommendations on how to foster data sharing. Subsequently, the focus is on catalysis, with a particular emphasis on benchmarking the data sharing practices against other fields and surveying the type of data currently being shared. The current infrastructure, including data repositories, and standards formats is maped. The striking differences among different disciplines are discussed, serving as a basis to propose specific actions to promote data sharing in catalysis. Short‐term initiatives are needed to boost the amount of openly available data, particularly in heterogeneous catalysis, but a high degree of standardization in data formats will be needed to ensure optimal and automated data mining in the long run. Because of its unique, central role in understanding the catalytic action, kinetic catalytic data is of particular interest. As formats and mining tools are dependant on the type of data, kinetic catalytic data is firstly characterized. Guidelines for a standardized sharing format are proposed, taking into account the small, well‐structured nature of this type of data. To maximize the extraction of information, the low volume of kinetic catalytic data will be compensated by incorporating fundamental knowledge into statistics‐based tools. Whencoupled with knowledge generation tools, i. e. kinetic models, new insights at the active site and mechanism levels will be reached in an ever more automated and powerful way. Catalysis informatics: Sharing data enables scientists to join efforts worldwide to solve key scientific puzzles. For optimal data (re)usage, raw data should be shared in machine readable unified formats via open databases. Specific guidelines for data sharing in catalysis are discussed, together with relevant tools for data‐centric knowledge generation.