Physical Sciences Data Infrastructure (PSDI)

CCP5 is collaborating with the Physical Sciences Data Infrastructure (PSDI) on the creation of both technical and training resources. The CAMML – Chemistry and Materials Machine Learning School 2025 training course is being run by the Physical Sciences Data Infrastructure (PSDI) initiative in collaboration with AIchemy, with support from STFC-SCD, PSDS, CCP5 and CCP9 as a follow up to the very popular 2023 Machine learning for Atomistic Modelling Autumn School. This training is targeted towards PhD students, in particular those in the Materials and Molecular Simulations field, who have experience of coding but are not highly experienced with machine learning. The aim of this training is to introduce attendees to the latest methods of machine learning for the atomistic simulation of materials. Know more: https://lnkd.in/gj6db2Np

⚛️ The Physical Sciences Data Infrastructure (PSDI)'s webinar series provide updates on our exploratory pathfinder work, and on relevant tools and technologies that have been developed by members of our community. ⚛️ This record contains a more detailed version of the presentation that was presented at the "Breaking Data Silos – From static documents to living data" webinar presented by Samuel Munday (Data Revival) on 26th February 2026 - https://lnkd.in/dB-D7wfZ ⚛️ The slides are available on zenodo: https://lnkd.in/g7dU8xAc 🎥 Recording of the webinar is available here: https://lnkd.in/gR2VkDjZ

🔋 On March 26-27, the #BETUnit researcher Marco Cecchetti was in Ireland to partecipate in the QUB-PSDI Workshop on Flow Battery Reproducibility organized by Queen's University Belfast and Physical Sciences Data Infrastructure (PSDI). 💫 The workshop gathered the partecipants of the multi-institution study on #replicability challenges on redox flow battery #testing, providing updates on the on-going activities, building the community and working together to establish lessons learnt and to explore possible future iterations of the #project #RFB #redoxflow #batteries #battery #reproducibility

Let's talk ERNs! Electronic Research Notebooks (ERNs) help researchers document, manage, and share their work. At their core, ERNs are digital platforms designed to replace traditional paper lab notebooks, allowing scientists to record experiments, store data, and organise findings in a structured and searchable format. One of the key advantages of ERNs is efficiency. Instead of flipping through pages, researchers can quickly search, tag, and retrieve information. They also support integration with datasets, code, and analytical tools, making it easier to maintain a complete and reproducible research record. Collaboration becomes more seamless too! Teams can access and contribute to shared notebooks in real time, regardless of location. Compared to traditional notebooks, ERNs offer improved data security, version control, and compliance with research standards. They reduce the risk of data loss and make it easier to track changes over time. We conducted an event recently where the Electronic Research Notebook (ERN) community met online and shared tales of ERN’s adoption success across the community. You can find the slides & recording here: https://lnkd.in/eNiRcQNH

Register here: https://lnkd.in/gk-2Rsbv This webinar illustrates how BioSimDR transforms scattered biomolecular simulation data into interoperable, provenance-rich resources for broader reuse. This session is intended for researchers generating, analysing, or reusing biomolecular simulations who want to improve transparency and reproducibility in their workflows. All details & registration link: https://lnkd.in/gPC9hh95

We are pleased to announce a one-day workshop at the University of Bath dedicated to the NMR data analysis of paramagnetic metal complexes in solution, supported by quantum chemistry calculations. 📅 Date: Monday, 30 March  ⏰ Time: 10:00 am – 4:00 pm  📍 Location: 1 South 0.01, Department of Chemistry, University of Bath    🤔 What to Expect The morning session features expert guest speakers covering both experimental and computational aspects of paramagnetic NMR (pNMR): ✨ Prof. Dr. Markus Enders (Heidelberg University) ✨ Dr. Lucas Lang (Technische Universität Berlin) 🚨 Spaces are limited. To secure your spot, please complete the Expression of Interest form: https://lnkd.in/gjVrTUu2 For any specific enquiries, please contact Dr Elena Suturina at e.suturina@bath.ac.uk

Was great to be able to represent Physical Sciences Data Infrastructure (PSDI) this morning after being asked to speak by Dr Josh J. Bailey at Queen's University Belfast at their Flow Battery Workshop. A culmination of the last 6 months work they have done with support from PSDI. Aside from a few technical hiccups we had some excellent discussion around infrastructure and reproducibility and what that means for different people and where PSDI supports this currently in the physical sciences Slide pictured courtesy of James Gebbie-Rayet and Jas K. Photo courtesy of Agnes Jasinska of the Digital Curation Centre