Year: 2026
Type: editorial
Abstract: Journal of Chemical Theory and Computation (JCTC) and the Journal of Chemical Information and Modeling (JCIM), reflecting our shared commitment to advancing reproducibility, transparency, and open science in theoretical and computational chemistry.The importance of sharing data, methods, and software is well established.In 2021, an editorial in JCIM (DOI: 10.1021/ acs.jcim.0c01389)emphasized the central role of data and method availability in ensuring reproducibility in computational chemistry and biology.That need has only grown more urgent.The scale of computational data continues to expand, workflows are becoming more complex, and artificial intelligence (AI) and machine learning (ML) are increasingly integrated into chemical research.In this rapidly evolving landscape, clear and practical expectations for data and code availability are essential.Open sharing benefits not only the broader scientific community but also the groups that generate these scientific assets.As articulated in the FAIR Guiding Principles, good stewardship ensures that data and related materials are findable, accessible, interoperable, and reusable.These practices make it easier to evaluate published results, reproduce key findings, and extend prior work to new systems and new questions.They also increase the long-term value of a study by preserving the underlying scientific record in forms that remain useful well beyond the original publication.When data, software, and workflows are shared in a clear and organized manner, they become durable contributions to the field.To support these goals, the data and software needed to reproduce the key results of an original research manuscript should be made available at the time of manuscript submission whenever possible.This policy will take effect on May first 2026.Reviews, Perspectives, and Editorials are exempt.Original research articles should include a Data and Software Availability Statement that clearly indicates where the
Authors: Rommie E. Amaro, Victor Batista, Jochen Blumberger, Yee Siew Choong, Clémence Corminboeuf, Zoe Cournia, Qiang Cui, Marco De Vivo, Francesco A. Evangelista, Yi Qin Gao, Debashree Ghosh, Xiao He, Olexandr Isayev, Syma Khalid, Johannes Kirchmair, John R. Kitchin, Haiyan Liu, Kevin J. Naidoo, Duc Nguyen, Ariane Nunes Alves, Giulia Palermo, Brett Savoie, Thereza A. Soares, Pratyush Tiwary, Guowei Wei, Xiao Zheng, Tong Zhu, Kenneth M. Merz, Laura Gagliardi
Institutions: University of California San Diego, Yale University, University College London, Universiti Sains Malaysia, École Polytechnique Fédérale de Lausanne, Academy of Athens, Biomedical Research Foundation of the Academy of Athens, Boston University, Italian Institute of Technology, Emory University, Peking University, Indian Association for the Cultivation of Science, East China Normal University, Carnegie Mellon University, University of Oxford, University of Vienna, University of Science and Technology of China, University of Cape Town, University of Tennessee at Knoxville, Brazilian Center for Research in Energy and Materials, University of California, Riverside, University of Notre Dame, Universidade de São Paulo, University of Maryland, College Park, University of Georgia, Fudan University, Cleveland Clinic, Cleveland Clinic Research, Michigan State University, University of Chicago
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W7155393139