Anne Nijs, Richard M Hartshorn, Gerd Blanke, Ray J Boucher, Ian Bruno, Mercè Crosas, Sonja Herres-Pawlis, Guido F Herrmann, Simon Hodson, Richard J Kidd, Nicola Knight, Oliver Koepler, Leah R McEwen
High-quality research data are essential for reproducibility, trust, and innovation in the chemical sciences. While the FAIR principles have improved the findability and accessibility of data, intrinsic data quality, such as accuracy, completeness, and consistency, remains insufficiently addressed. This editorial calls for coordinated community action to strengthen chemical data infrastructures and to treat research data as a first-class scientific output. Building on successful models and through collaboration under organizations including CODATA and IUPAC, the chemical sciences community can advance interoperable standards and robust quality assessment to ensure that open, validated data drive future discovery and innovation.