ioChem-BD: Open-Data for Computational Chemistry and Materials Science - project poster 2nd OSCARS AGM 2026

Summary The Open-Data for Computational Chemistry and Materials Science: ioChem-BD project emerges from a growing recognition of the importance of Open Science in accelerating research and innovation in the fields of computational chemistry and materials science. With the rapid advancement of computational methods generating vast amounts of data, there is a critical need for effective data management and sharing practices. ioChem-BD aims to address this gap by fostering good practices in research data management and promoting the generation of FAIR data. By transforming digital repositories and introducing innovative services, the project seeks to create an engaging platform that not only facilitates data sharing but also cultivates a culture of transparency and reproducibility in research, ultimately accelerating chemical discoveries and enhancing collaboration across the scientific community. Research domains: Chemistry, computational chemistry and materials science Partner(s): Institut Català d'Investigació Química Project team member(s): Carles Bo, Moisés Álvarez, Jair Wells, Marc Gruber, Gabriela Dias, Robert López Challenge Open Science project, Open Science Service, Main RI concerned In the realms of computational chemistry and materials science, there is a pressing need to address the fragmented landscape of research data. Current practices in research data management often lead to inefficiencies in data sharing, limiting researchers’ ability to access and utilise valuable datasets. Moreover, the lack of adherence to FAIR data principles hinders the reproducibility of scientific findings and inhibits collaborative efforts. All this makes the need for a more integrated and adaptable data management solution increasingly evident. Solution The ioChem-BD project provides a comprehensive approach to overcoming these challenges by developing a robust platform that promotes FAIR data practices. Key objectives include assessing researchers’ real needs for FAIR data, developing software tools fostering user proficiency and data quality control features, and creating software tools to contribute to the adoption of FAIR data principles in the computational chemistry and materials science community. By integrating Semantics Data Models (SDM) into the repository, ioChem-BD ensures that data from various origins can be analysed collectively, enhancing the potential for insightful research outcomes. Additionally, the project will host workshops, talks and meetings with the community, to further improve data FAIRness and the platforms. Scientific Impact The impact of ioChem-BD extends across the scientific community, enhancing researchers' capabilities in data-driven research. By providing tools that support the analysis, transformation, and comparison of data, the platform aims to empower users to generate high-quality, representative datasets that can confirm both new and established hypotheses. Furthermore, the project envisions transforming the ioChem-BD platform into a virtual research environment (VRE) that promotes collaboration and innovation. Through this project, researchers will be equipped to produce impactful research that advances knowledge in computational chemistry and materials science, thereby contributing to the broader goals of Open Science and collaboration in the scientific community.