FAIRmat participated in NIAC2026, the annual meeting of the NeXus International Advisory Committee, held at DESY in Hamburg as a satellite meeting of NOBUGS 2026. The meeting brought together members of the international NeXus community to discuss the development, maintenance, and use of the NeXus data format.

As part of FAIRmat’s ongoing contribution to scientific data interoperability, Lukas Pielsticker represented FAIRmat and gave a talk on our experience with integrating NeXus into the NOMAD research data infrastructure. In particular, the presentation highlighted how FAIRmat uses NeXus to connect experimental data workflows with a broader FAIR data infrastructure and the practical experience gained from implementing NeXus-based workflows and tools in NOMAD.

Over the past years, FAIRmat has also worked closely with the NeXus community on standardization, contributing to the development and refinement of NeXus application definitions and related semantic and interoperability aspects. This work has helped connect established community standards with the requirements of a large-scale, machine-actionable data infrastructure such as NOMAD.

After five years of intense work, widespread acceptance by our community and, completely unexpected, the Digital Skills Award 2026, we are now ready to take the next big step.

Our focus will certainly stay on the development of NOMAD, our research data management platform that is used by thousands of scientists worldwide. We will further develop the broader NOMAD ecosystem in various directions, always in view of the growing role of artificial intelligence in our field. To optimally support the reuse of data, we have introduced a new Task Area, which is Enabling Data-driven Science. Also Data Modeling and Interoperability is now represented in a separate Task Area. Synthesis, Experiment, and Computation remain our domain-specific pillars.

Our broad research field is represented by an increased number of now 90 Principal Investigators. Among them, we welcome 11 PIs from abroad, connecting us to international developments. We also look forward to fruitful collaborations with other NFDI consortia.

We thank all the team members who contributed to FAIRmat during the first period and who are now moving on to our new challenges. And we warmly welcome the new colleagues joining FAIRmat, strengthening our activities that are bundled in our hub in Berlin. We are all enthusiastic about working together to take the NOMAD ecosystem to its next stage.

The recordings from the 8th FAIRmat Users Meeting, held on June 16–17, 2026, are now available online. The playlist includes the following presentations:

• Expert Panel: Deploying RDM Infrastructure across Research Organizations Using NOMAD Oasis
• Data @Big Chemistry: Deploying NOMAD Oasis as a User Platform – Mark Driver
• NOMAD Oasis for Electron Microscopy – Christoph T. Koch
• Scaling NOMAD Adoption Across Research Communities – Joseph Rudzinski
• Customizing NOMAD Oasis for Thin-film Research in Sustainable Energy Materials – Diego Alejandro Garzon
• Automating Research Workflows with NOMAD Actions – Ahmed Ilyas, Lev Ginzburg, and Sarthak Kapoor
• AI-Assisted Scientific Data Extraction – Sherjeel Shabih and Yaru Wang

Subscribe to the FAIRmat and NOMAD YouTube channel to stay up to date with newly published recordings.

Over the years, NOMAD users have developed a wide range of applications and workflows that demonstrate the potential of FAIR data and open research infrastructures. The NOMAD Gallery brings these examples together in one place. It is a growing collection of innovative features, uploads, and use cases enabled by the NOMAD ecosystem. By highlighting these success stories, the gallery aims to inspire the community, encourage knowledge exchange, and demonstrate the impact of FAIR data practices in materials science. 

We invite researchers, developers, and all members of the NOMAD community to contribute their own use cases. Whether you have created a new workflow, developed an application, uploaded and shared valuable datasets, or built a new tool, we would like to hear your story. By sharing your experience, you can increase the visibility of your research within the international materials-science community, inspire other researchers with your approach and results, and help others discover new ways to use NOMAD.

On July 13–14, FAIRmat participated in the workshop MatOSC: Shaping Together a Future EOSC Node for Materials in Lausanne, Switzerland.

MatOSC is a project preparing a future thematic node for materials science within the European Open Science Cloud (EOSC). The workshop brought together leading European research infrastructures, projects, and service providers to develop a shared vision for a future EOSC Node for materials science.

As the developers of the NOMAD platform, FAIRmat contributes its experience in building a scalable research data management (RDM) ecosystem for FAIR, machine-actionable materials data. Through close collaboration with the broader materials community, FAIRmat helps strengthen interoperability between repositories and services, improve the discoverability and reuse of materials data, and ensure that NOMAD can serve both as a comprehensive community RDM platform and as a key interoperable component within the future EOSC materials ecosystem. 

MaterialsCommons, a new European initiative, has officially started its work to create a federated digital infrastructure for advanced materials. The project aims to create a unified entry point to Europe's distributed materials data and digital services by connecting existing platforms, repositories, and tools. 

NOMAD, the research data management platform developed by FAIRmat, is among the first infrastructures to be integrated into MaterialsCommons, alongside Materials Cloud, MaterialDigital, CAPeX, and OPTIMADE.

Several members of the FAIRmat consortium are participating in the project, contributing their expertise in FAIR research data management, semantic interoperability, AI-ready data infrastructures, and digital tools developed for the materials science community.

By connecting digital resources, including data, services, and workflows, MaterialsCommons seeks to accelerate materials discovery, support industrial innovation, and strengthen Europe's competitiveness in advanced materials research.

Research data are key to advancing materials research in the age of artificial intelligence (AI). Through a Memorandum of Understanding, five Berlin research institutions have agreed to establish a long-term collaboration in the areas of research data, data infrastructures, and AI.

This collaboration brings together the NFDI consortium FAIRmat, based at Humboldt-Universität zu Berlin (HU), Helmholtz-Zentrum Berlin (HZB), Leibniz-Institut für Kristallzüchtung (IKZ), Paul-Drude-Institut für Festkörperelektronik (PDI), and Bundesanstalt für Materialforschung und -prüfung (BAM). Together, they are laying the foundation for cross-institutional collaboration and thereby strengthening Berlin as a hub for research and innovation. The shared goal is to make research data accessible across institutional boundaries, develop common data and metadata standards, and advance the use of artificial intelligence methods in materials research. The further development of the NOMAD research data platform is a key aspect of the collaboration.

The FAIRmat–HZB Symposium "Digital Future of Materials Science" provided the ceremonial setting for the signing of the Memorandum of Understanding. The symposium opened with a keynote lecture by the internationally renowned scientist Giorgio Rossi (University of Milan / NFFA), who highlighted the importance of shared research infrastructures for data-driven science. Claudia Draxl, Spokesperson for FAIRmat, then showed how the NOMAD platform is preparing materials research for new data-driven paradigms. Bernd Rech, Scientific Managing Director of HZB, discussed the opportunities and challenges that artificial intelligence presents for science and technology.

The President of HU Berlin, Julia von Blumenthal, emphasized the importance of the new collaboration in her speech: "Today, we are signing a Memorandum of Understanding that confirms our partnership at the institutional level – I am delighted that the heads of all four institutes are here to sign it in person. This step will help speed up our scientific progress and set the stage for staying at the forefront of artificial intelligence in materials science."

The symposium concluded with a panel discussion entitled "Driving the Cultural Change", addressing the changes needed for research data and artificial intelligence to realize their full potential for science.

"We are convinced that research data are among the most important resources of the 21st century. However, the transition to the digital age comes with challenges that we will address together with our partners. This Memorandum provides an important foundation for bringing our expertise together even more effectively," said Claudia Draxl.

The consortium FAIRmat has been granted a second funding period as part of the German National Research Data Infrastructure (NFDI). The decision, announced by the Joint Science Conference (Gemeinsame Wissenschaftskonferenz, GWK) on July 10, enables FAIRmat to continue developing digital infrastructure, tools, and services that support materials scientists in their data management.

Since the start of its first funding period in 2021, FAIRmat has built an ecosystem of comprehensive data infrastructure, in the center of which is the NOMAD platform. It enables researchers to manage metadata, document experiments and calculations, automate workflows, publish datasets, and organize structured research data for analysis and reuse. Today, NOMAD is used by thousands of researchers worldwide, making scientific data ready for the next generation of data-driven and AI-enabled research.

"Continued funding is an important recognition of the progress FAIRmat has made over the past five years and a commitment to the future," says Prof. Dr. Claudia Draxl, spokesperson of FAIRmat. "Research data management has become an essential component of modern research. The second funding period allows us to further expand our services, strengthen collaborations with researchers and partner institutions within and outside the NFDI, and continue building sustainable solutions that enable open, reproducible, and data-driven science. The entire team is looking forward to continuing our endeavor with even more enthusiasm."

For the second funding period, we will be expanding the NOMAD ecosystem as a scalable digital infrastructure to be even more powerful, with enhanced functionality supporting our broad community. To be most inclusive, the group of principal investigators is growing from 58 to 90, including 12 researchers from all over Europe and the US. The increasing international visibility is reflected by the European Digital Skills Award 2026 recently given to FAIRmat. NOMAD will also appear soon as a service within the European Open Science Cloud (EOSC).

To support FAIR research data management and complement the NOMAD digital infrastructure, FAIRmat has launched DMP4PS – a new online service that helps researchers create and manage Data Management Plans (DMPs) for condensed-matter physics, materials science, and related physical-sciences disciplines. The service was implemented through a DMP4NFDI incubator project within Base4NFDI, an initiative that supports the development of reusable research data management services across the NFDI.

A Data Management Plan describes how research data will be managed throughout a project, from data generation and documentation to storage, sharing, preservation, and long-term reuse. Preparing a DMP at an early stage helps establish clear research workflows and supports compliance with FAIR data principles. It is also increasingly required by major funding organizations, including the Deutsche Forschungsgemeinschaft (DFG), the European Commission, and the European Research Council (ERC).

Based on the open-source Research Data Management Organiser (RDMO), DMP4PS provides researchers with user-friendly templates and guidance tailored to the needs of the physical sciences. The available templates are aligned with FAIR research data management practices and common funder requirements, making it easier to prepare high-quality DMPs for research proposals and projects.

The recording of the latest FAIRmat Seminar is now available on our YouTube channel.

In his talk, "Polymer Informatics Accelerates and Improves Polymer Science", Prof. Christopher Künneth presents how machine learning models can be applied to predict polymer properties and support the design of bioplastics and organic battery materials. He also demonstrates how chemical language models streamline polymer discovery, enabling more efficient exploration of polymer chemistry. The seminar further discusses the broader potential of these approaches to accelerate materials development and their applicability to other complex materials systems.