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.

FAIRmat has received the European Digital Skills Award 2026 in the Digital Upskilling @ Work category. The prize was presented by the European Commission on June 30, 2026, in Brussels.

The European Digital Skills Awards honor initiatives that help equip people with the skills needed to thrive in an increasingly digital society and support the objectives of the European Digital Decade Programme 2030.

Selected from more than 220 applications from across Europe, FAIRmat was recognized for its contribution to strengthening digital competencies in research through a comprehensive approach that encompasses software development, community engagement, and training.  

Over the past five years, FAIRmat has built an ecosystem that supports data-driven research in materials science, physics, and chemistry. At its center is NOMAD, the consortium's open research data management platform, which enables researchers to organize, publish, and reuse scientific data according to the FAIR principles. Around this infrastructure, FAIRmat has developed extensive educational resources, hands-on training, workshops, seminars, and community events that help researchers integrate research data management into their everyday work.

Today, NOMAD hosts more than 20 million publicly accessible data entries and is used by researchers worldwide. At the same time, FAIRmat continues to expand its educational portfolio, working closely with universities, graduate schools, research infrastructures, and international partners to strengthen digital competencies across the scientific community.

This achievement reflects the collaborative work of our team and scientific community to make research data more accessible, reusable, and valuable for future discoveries.

Last week, the FAIRmat community came together for its eighth semi-annual Users Meeting, continuing a tradition of exchange, collaboration, and community building.

The program started with afternoon workshops, offering three hands-on tutorials and an expert panel discussion. The tutorials were designed for participants with different interests, goals, and levels of experience: whether they were first-time NOMAD users finding their footing, researchers looking to structure and share their data more effectively, or developers ready to build plugins and extend the platform, there was a path for everyone.

The expert panel, in contrast, focused on the strategic and organizational dimensions of Research Data Management (RDM) infrastructure. Bringing together speakers with experience across research groups, institutions, and collaborative networks, the session explored the practical realities of deploying and operating RDM platforms, using NOMAD Oasis as a concrete example. Through flash talks, a moderated discussion, and audience questions, participants gained insights into topics such as governance, sustainability, resource requirements, and institutional adoption, while those new to NOMAD Oasis received an introduction to how such systems are implemented in real-world settings.

A particular highlight of the first day was the Users-Meet-Developers exhibit, which featured 19 contributions, spanning RDM workflows, custom schemas, plugins, data analysis tools, and more. It showed a community that doesn't just use NOMAD, but actively shapes it.

The second day began with talks from researchers from different countries and scientific disciplines. Their contributions reflected the growing international community that has formed around the NOMAD ecosystem.

This eighth meeting also carried special significance: it marked the last one of the current FAIRmat funding period. Looking back, the meeting highlighted the remarkable growth of the NOMAD community and the many services, tools, and collaborations that FAIRmat has helped establish over the past years. As we prepare for the next phase, one thing is clear: bringing the NOMAD community together will remain a priority. The format may evolve, the program may find new areas of focus, but the spirit of these gatherings – open exchange, hands-on collaboration, and a shared commitment to making research data truly FAIR – will remain at the heart of what we do.

Thank you to all speakers, tutorial leads, exhibitors, and participants who made this meeting such a success!

From May 25 to 29, the FAIRmat team joined the European Materials Research Society (E-MRS) Spring Meeting 2026 at the Strasbourg Convention Centre – one of the field's flagship conferences for the international materials-science community.

Siamak Nakhaie, Ahmed Mansour, Hampus Näsström, and Claudia Draxl represented FAIRmat at the information booth throughout the week, welcoming researchers from across Europe and beyond. Many attendees had already heard about NOMAD and were eager to see it in action, getting a first-hand look at the platform through live demonstrations. In addition to researchers interested in getting started with the platform, the booth attracted existing NOMAD users who were looking for advice on more advanced topics and specific use cases. Ahmed Mansour also introduced NOMAD and FAIRmat services during the Industrial Forum, complementing FAIRmat's presence at the exhibition. 

Beyond the exhibition, FAIRmat was also well represented in the scientific program. In Symposium E – Data-based methods and AI for the development and processing of advanced materials – Hampus Näsström presented on the integration of machine learning workflows in NOMAD. FAIRmat spokesperson Claudia Draxl delivered the invited talk NOMAD – a Platform for Accelerating Materials Research. In addition, NOMAD was featured in several presentations by researchers from the broader community, highlighting its growing adoption and impact as a research data infrastructure for materials science. 

The visibility generated by NOMAD's presence throughout the conference encouraged many participants to visit the booth, where they could learn more about NOMAD and FAIRmat services. A recurring reaction among visitors was genuine surprise that such powerful tools are freely available.

Our participation in the E-MRS Spring Meeting 2026 was a great success. We look forward to continuing the exchange of ideas and experiences with the materials-science community at future events.

NFDI Consortium FAIRmat has been selected as one of 25 finalists for the European Digital Skills Awards (EDSA) 2026 in the Digital Upskilling @ Work category. The 25 finalists across all categories were officially announced on May 27 at a dedicated online session hosted by the Digital Skills and Jobs Platform. The selection recognizes FAIRmat's sustained efforts to build digital competencies in the research community: from hands-on training in research data management to tutorials, workshops, and educational resources around FAIR data practices and the NOMAD platform.

This year's EDSA call attracted 220 applications from across Europe, reflecting the growing momentum behind initiatives to strengthen digital skills. The awards recognize excellence in training, upskilling, and reskilling that support Europe's digital transformation and competitiveness, in line with the Digital Decade targets. The five award categories – Digital Upskilling @ Work, Digital Skills for Education, Inclusion in the Digital World, Women in ICT Careers, and Cybersecurity Skills – reflect the diversity of digital skills initiatives shaping Europe's future.

Being named a finalist is a recognition of the community-driven approach that has always been at the heart of FAIRmat's training and outreach activities. We thank everyone who has contributed to and participated in our educational offerings, this achievement belongs to the entire FAIRmat community.

Last week in Lausanne, the CECAM Flagship Workshop brought together method experts, research data management (RDM) specialists, and simulation code developers to explore how FAIR data practices can better support theoretical spectroscopy.

The program combined scientific presentations, roundtable discussions, and dedicated collaboration slots, with participants sharing perspectives from infrastructure initiatives, cutting-edge scientific applications, and simulation software development. The format was designed to move beyond exchange toward joint, community-driven work.

The hands-on session was a particular highlight, with participants working directly with the nomad-simulations schema. It sparked lively discussions and valuable feedback, leading to concrete ideas for improving how complex methods and workflows are represented – from refining the structure of GW calculations to exploring more consistent descriptions of Green's functions and response properties. The session underlined both the substantial progress already achieved and clear opportunities ahead.

The workshop fostered an open and forward-looking atmosphere, strengthening connections between researchers, infrastructure developers, and code authors. It set the stage for continued, community-driven development of FAIR data standards to make theoretical spectroscopy data more accessible, reusable, and impactful.

From April 13 to 16, 2026, the NFDI consortia MatWerk and FAIRmat hosted the research data management (RDM) Spring School at FAU Erlangen–Nuremberg. The event attracted participants from across Germany and provided an engaging learning environment, making it a great success.

The students showed a keen interest and enthusiasm for learning how to manage their research data in a way that aligns with the FAIR principles. They were engaged throughout the presentations and actively participated in the hands-on sessions, creating a dynamic and interactive atmosphere.

The program covered the basics of RDM, including key concepts, the FAIR data principles, and the application of AI/ML methods in materials science. Participants got to learn about the NFDI activities and tried out some tools developed within FAIRmat and MatWerk, like NOMAD, NOMAD CAMELS, PASTA ELN, and Coscine.

The FAIRmat team offered the "Getting Started with NOMAD" tutorial, during which participants learned how to upload, structure, share, and publish both experimental and computational data within NOMAD.

A particular highlight was the hands-on session in the electronics lab at FAU. Here, participants experienced a complete end-to-end research data workflow: from performing real measurements using NOMAD CAMELS, to generating structured data with rich metadata, and automatically transferring them into NOMAD Oasis. Then, they explored how to analyze the data within NOMAD using NORTH and document results within the NOMAD ELN. This demo showed how the NOMAD ecosystem can handle the whole research data lifecycle, from data acquisition to analysis and preservation.

In addition, participants visited the Interdisciplinary Center for Nanostructured Films (IZNF) at FAU, gaining insight into real-world research environments where large-scale data are generated and managed.

The spring school wrapped up with a session on artificial intelligence and machine learning, with a focus on the importance of managing research data effectively to support machine-readable, data-driven science.

A new publication in Nature Catalysis, "Enabling open and FAIR catalysis data with standardized data structures", highlights FAIRmat’s work on making catalysis data more open, structured, and reusable. The paper presents the concept and implementation behind the NOMAD Catalysis App, a web-based application that enables researchers to share, explore, and analyze catalysis data in a FAIR-compliant way, and provides a foundation for AI-driven discovery of more efficient and sustainable catalysts.

The work was carried out within FAIRmat with major contributions from Dr. Julia Schumann and scientific leadership by FAIRmat Principal Investigator Dr. Annette Trunschke. The collaboration brings together researchers from the Humboldt-Universität zu Berlin, the Fritz Haber Institute of the Max Planck Society, and the Helmholtz-Zentrum Berlin.

Released last summer, the NOMAD Catalysis App is integrated into the central NOMAD platform, and is available as a NOMAD plugin that can be installed on self-hosted NOMAD Oasis deployments. It allows researchers to explore catalysis datasets through an interactive interface. Users can search and filter data by parameters such as reactants and products, synthesis method, catalyst form, and reaction conditions. Data can be uploaded both manually and automatically via the API. The authors developed schemas, i.e., data structures, for typical datasets in catalysis. Furthermore, they designed Excel spreadsheet templates that can be directly parsed and allow users to enter their data in a format that is familiar to most researchers.

A key advantage of the app is its data visualization feature. Some plots are predefined, but users can also create their own graphical representations.

The publication marks an important milestone for FAIRmat and the catalysis research community. It shows how digital research infrastructures and standardized metadata can help make catalysis data more reproducible, interoperable, and ready for data-driven research.

The Catalysis App supports the exchange of catalysis data and lays important groundwork for future AI-driven analytics. At the same time, its value depends on active use by the community. Researchers are therefore encouraged to explore the tool, test its capabilities, and contribute data and feedback to help develop the application further and ensure that it continues to meet the evolving needs of researchers.

For full documentation, including installation, usage, and functionality, visit NOMAD Catalysis Plugin Documentation.