Our DAPHNE4NFDI Annual Meeting 2025 will take place at the Helmholtz Zentrum Berlin (HZB) Campus Adlershof from
Monday, March 24th to Wednesday, March 26th 2025
Meeting points and options tbd
This talk will give an short overview what is brewing at HZB: it will cover the light source BESSY II and its ongoing uprade progam next to a short introduction of BESSY III. Then it will address the its data side:
data taking and processing illustrated by projects running at HZB.
Advances in synchrotron imaging and computed tomography (CT) enable non-invasive, high-resolution 3D visualization of samples, including biological tissues, surpassing standard methods. This innovation generates massive data volumes, requiring tailored solutions for data capture, management, storage, and repositories for processed data and analysis code. These solutions enhance transparency and maximize data reuse in biomedical research. We have been collaborating closely with scientists and IT experts from various synchrotron facilities, primarily at ESRF and PETRA III. We have established a consistent vocabulary and compiled a comprehensive list of parameters applicable across different imaging beamlines. The results of this work will be shared with other imaging beamlines and facilities. The LMU team, together with the tomography-user teams of Göttingen University and HZB, has finalized a metadata table and its description for generic (bio)synchrotron imaging and CT experiments for the white paper. Currently, the implemented or in-progress metadata recording is focused mainly on storing parameters up to the data acquisition phase. In collaboration with ESRF IT experts, we are currently discussing the extension of this list to include comprehensive post-processing metadata, at least up to CT data reconstruction, which is a common component of all CT experiments. Additionally, ESRF does not provide detailed sample metadata information. We are in the process of discussing with the ESRF IT team to integrate the IGSN link with ICAT to connect the corresponding experiments. The subsequent steps of image processing, data analysis, and quantification require significant collaboration within the community, as each application demands specific processing pipelines and tools. We aim to identify the common components of this workflow and propose a suitable metadata scheme. As part of our commitment to TA3, we are developing an image processing workflow tailored for the analysis of biological tissues, incorporating machine learning-based models for segmentation, analysis, and quantification. This processing pipeline will be shared with the broader user community (https://github.com/hfahad/U-NET-Synchrotron_CT-image_segmentation.git). Through collaboration among user groups, scientists, and IT experts from synchrotron facilities, the LMU team is working to establish a general FAIR data workflow for synchrotron imaging and CT experiments. The LMU team has finalizing the installation process of SciCAT on the LMU machine with coordinated efforts from LMU IT Services, the Leibniz Supercomputing Centre (LRZ), and the Helmholtz Centre Dresden-Rossendorf. Currently, SciCAT is undergoing further processing and will be initially available for our group and subsequently for our collaborators. The purpose of this implementation is to install and interface SciCAT with the existing catalog system, enhancing overall data management.
The DAPHNE4NFDI initiative is transforming data management for photon and neutron science by implementing FAIR (Findable, Accessible, Interoperable, Reusable) principles across various experimental techniques. At the P10 beamline of DESY, we have deployed SciCat for SAXS/XPCS experiments, enhancing metadata ingestion and data accessibility. In parallel, the development of Xana 2.0 introduces modernized XPCS data analysis with HDF5/NeXus support and parallelized I/O for large datasets.
Expanding these efforts to MHz-XPCS at EuXFEL, we focus on establishing this as a routine technique while embedding FAIR principles. Within DAPHNE4NFDI, we are also developing FUSE (FAIR Unified Scientific Environment)—a cloud-based platform that integrates diverse research data, ensuring interoperability and accessibility for XPCS experiments.
Beyond data management, effective outreach is crucial for maximizing impact. In TA4 of DAPHNE4NFDI, we explore Large Language Models (LLMs) for automating science communication, including event summarization and social media engagement. This AI-driven approach optimizes outreach strategies, making research more accessible.
Our contributions from the University of Siegen demonstrate how advanced data solutions and AI-powered communication are shaping the future of photon and neutron science.
In the frame of DAPHNE4NFDI, an X-ray absorption spectroscopy (XAS) reference database called RefXAS has been set-up where users are provided with well curated XAS reference spectra along with related metadata fields and online processing tools for visualizing the data. The developed online procedure enables users to submit a raw dataset along with its associated metadata via a dedicated website for inclusion in the database. The published data at the database can be easily linked to the raw data available at other repositories. Quality criteria formulated for the uploaded reference data at the database make users aware of the usability of the data. These quality criteria, which are unique to RefXAS, are further employed for automatic quality check of the uploaded data which is then followed by manual curation at the interface. Different XAS data formats can be uploaded to RefXAS. The output data format consists of all the important metadata provided during upload including quality criteria, curation details and bibliographic details of the data.
Inelastic scattering is a fundamental technique for probing lattice dynamics and magnetic excitations, serving as a cornerstone in materials science and condensed matter research. While it has historically been linked to neutron scattering, recent innovations in modern synchrotron facilities have facilitated the acquisition of complementary x-ray scattering data, which are vital for contemporary scientific investigations. This encompasses experiments conducted under high-pressure conditions on small single crystals and within materials that demonstrate substantial neutron absorption.
In use case 5, we aim to establish suitable metadata vocabularies specifically for Inelastic Neutron Scattering (INS) and Inelastic X-ray Scattering (IXS) techniques, alongside fostering the use of electronic laboratory notebooks (ELNs). This poster demonstrates our efforts in developing metadata schemas for a triple-axis spectrometer and provides an update on the status of the electronic lab notebook being developed at MLZ.
Within the soft matter and liquid interfaces X-ray reflectivity Use Case 6, we develop a FAIR data pipeline for X-ray reflectivity at beamline P08, PETRA III. This includes automating electronic lab notebooks (ELNs) [1], metadata ingestion from the control system and IGSN creation for samples. Collaborating with DESY beamline scientists, experimental control group, and IT, we are implementing automated metadata ingestion into SciCat, based on the proposed DAPHNE4NFDI metadata schema [2]. Here, we will present the current status of the data and metadata integration and the recently introduced PaN Reflectivity Database [3,4], aggregating high-quality photon and neutron reflectometry data. Additionally, we will show integration of machine learning solutions [5,6,7] for X-ray and neutron reflectometry, collaborating with large-scale facilities to including also for feedback to the instruments, including so-called closed loop experiments [8] and expanding research to include hard materials and magnetism.
References
[1] P. Jordt et. al., Supplementary Information for Publication: Specifications for Electronic Laboratory Notebooks (ELN) in the Photon and Neutron Community. Zenodo (2025)
[2] W. Lohstroh et al., DAPHNE4NFDI - Draft recommendations on metadata capture and specifications (1.0). Zenodo (2024)
[3] https://public-data.desy.de
[4] https://sisyphos.desy.de
[5] A. Greco et al., J. Appl. Cryst. 55, 362-369 (2022).
[6] V. Munteanu et al., J. Appl. Cryst. 57, 456-469 (2024).
[7] V. Starostin et. al., Sci. Adv. (2025), in print
[8] L. Pithan et al., J. of Synchr. Rad. 30, 1064 (2023)
Understanding ultrafast structural and magnetic dynamics in materials is essential for advancing fields such as spintronics, quantum materials, and laser-driven phase transitions. Time-resolved X-ray scattering techniques at free-electron lasers (XFELs) provide a powerful tool to investigate femtosecond-scale structural and spin-related phenomena in thin films and nanostructures. In particular, the combination of ultrashort infrared (IR) laser pulses as the pump and X-ray free-electron laser (FEL) pulses as the probe enables the direct observation of transient changes in magnetic order and lattice structure on timescales shorter than 100 fs.
In a typical pump-probe experiment, an intense IR laser pulse excites the sample, inducing electronic and structural dynamics, while a delayed FEL pulse probes the resulting changes via X-ray diffraction or resonant magnetic scattering. By systematically varying the time delay between the pump and probe, it is possible to capture the evolution of magnetization, spin textures, and lattice distortions with femtosecond temporal resolution. This approach has been instrumental in revealing light-induced phase transitions, demagnetization dynamics, and the coupling between electronic, magnetic, and structural degrees of freedom.
Our investigation utilizes the European XFEL (Hamburg) and FERMI@ELETTRA (Italy) for time-resolved X-ray scattering experiments to study ultrafast dynamics. Elettra's current Data Policy based on the FAIR principles, which the experimental data and metadata of peer-reviewed experiments are stored in an online catalogue, accessible to registered users after a three-year embargo period. For the detailed analysis, we consider experimental data collected by several scientific groups over several years. Collecting all data in the same format for comparison is a critical step in our research.
To enhance data processing and workflow efficiency, we are also working on Data And Metadata iNspection Interactive Thing (DAMNIT) for the HED beamline at EuXFEL. DAMNIT aims to provide an automated pipeline designed to streamline data organization, processing, and metadata handling for ultrafast X-ray experiments, ensuring robust data handling, metadata extraction, and rapid feedback for experiment optimization. Special consideration is given to the specific requirements of pump-probe experiments, where data acquisition must be synchronized with the optical laser and collected when the shutter is open. Therefore, the system is optimized to address these needs effectively. By integrating DAMNIT with our workflows, we aim to improve data accessibility, reproducibility, and compliance with FAIR principles within DAPHNE4NFDI.
The university group at RWTH Aachen specializes in neutron TOF powder diffraction method development, primarily driven by the new concepts of the neutron time-of-flight diffractometer POWTEX, developed in collaboration with Forschungszentrum Jülich at FRM-II/MLZ in Garching. Unfortunately, no free neutrons were available in 2024. Within the DAPHNE project, we are therefore spreading our methods to other neutron TOF diffractometers while generally aiming to allow a broader, more sustainable applicability of the new developments. This overall goal splits into the following tasks, addressing the different steps in the workflow from raw data to scientific result: 1. multidimensional data reduction using Mantid, 2. derive and include fundamental instrument description in NeXuS data files, 3. multidimensional Rietveld test-cases, 4. AIXtal, a web and cross-platform Rietveld platform for (not only) first-time users, 5. AI tools for structure solution and profile refinement of powder diffraction data.
Utilizing our Mantid routine PowderReduceP2D for high-pressure data collected from SNAP@SNS, ORNL, USA combined with the derived and iterated fundamental instrumental parameters of SNAP allowed us to test-case the multidimensional Rietveld refinement on high-pressure neutron TOF powder diffraction data of a PbNCN sample. While the details were recently published in [1], it is important to note three things: At first, it is very tedious to collect instrumental parameters from various sources while they should actually be part of the data file. At second, a detector coverage of only 1.3 sr (SNAP) vs. ≈ 9 sr (POWTEX) already allows to do multidimensional Rietveld, which is remarkable and underlines the general applicability. While the data reduction steps, with the exception of the one- or multi-dimensional binning, were as similar as possible, the scientific result of the multi-dimensional refinement does differ significantly from the conventional, one-dimensional Rietveld refinement.
Based on these results, we created a sample nexus file containing data fields for the fundamental instrumental parameters. This was presented and discussed at a workshop with the SNS diffraction department which also allowed us to collect the view from the facility perspective. Shaping the future of the Rietveld diffraction software was also recognized as a common interest, especially since the existing software has been mostly around for a long time and the future of the method needs to be clarified.
AIXtal v1 was developed as prototypic, modern web-platform, which allows first-time users to utilize the Rietveld method while partly hiding the complexity of the existing tools GSAS-II and FullProf for the case of conventional X-ray diffraction. The web interface now runs on WebAssembly, which promises performance gains, and moreover now runs not only in the WebBrowser but also natively on Windows, Linux to allow a local installation as well. The higher-performance GUI shall allow to process multidimensional neutron data in the future. While multidimensional Rietveld (GSAS-II 2D) is available as worker already, we only recently started working on GUI and plotting features for this case. The integration of AI methods into AIXtal, e.g. to predict the space group symbol or to support the refinement process, shall ease the structure solution and refinement from powder dat, not only for the unexperienced user.
[1] Y. Meinerzhagen, K. Eickmeier, P.C. Müller, J. Hempelmann, A. Houben, R. Dronskowski, J. Appl. Crystallogr. 2024, 57, 1436–1445, doi:10.1107/s1600576724007635.
Tomography at neutron and photon sources is a ubiquitous tool with applications for a large variety of research domains. On the way to FAIR data, this use case is focusing on the metadata specification of tomography data from both photon and neutron sources, incl. the discussions for a common *nxs specification.
Within Use Case 10 the ICSP@FAU group works towards an automated, generic and FAIR data workflow for research institutes handling data from various sources. Key components of the workflow are a local NOMAD Oasis1, which is hosted by a local computer center and the utilization of the NeXus2 standard wherever possible. We present how we utilize and customize our NOMAD Oasis to fit the FAIR requirements and support our scientific work from data collection to publication.
Key metadata requirements for biological samples studied within the Bio-SAXS part of Use Case 10 are identified by learning from the automatic data and metadata pipeline at EMBL’s SAXS beamtime (P12), PETRA III and the integrated SASBDB3 database, a federated database designed for biological SAXS and SANS data, offering curated, searchable experimental data along with relevant metadata. Yet, at most beamlines and especially lab sources no automatic metadata pipeline exists and metadata is often collected manually and separately from the raw data. Here, we present our efforts at CAU, EMBL and Uni Siegen to increase findability and accessibility by establishing data handling protocols including the creation of NeXus files and generation of persistent sample identifiers (IGSN) on an exemplary data publication of Bio-SAXS data4 collected at BL2, DELTA.
Progress on automated feature detection in 2D image data at Uni Tübingen will be presented by machine learning, focussing here on grazing incidence wide angle X-ray Scattering (GIWAXS) 5-7. The peak detection was already demonstrated to be able to track and process scattering features during in-situ synchrotron experiments6. Additionally, a labelled data set for benchmarking peak detection algorithms was published5.
References
1) https://nomad-lab.eu/nomad-lab/nomad-oasis.html
2) https://www.nexusformat.org/
3) E. Valentini et al. Nucleic Acids Research, 2015, Vol. 43, Database issue D357–D363.
4) S. C. Hövelmann et al. IUCrJ, 2024, 11, 486-493.
5) C. Völter et al. J. Appl. Cryst. (2025), in print
6) V. Starostin et al. Synchrotron Radiation News 35 (2022) 21
7) V. Starostin et al. npj Comput Mater 8 (2022) 101
Presentation on the activities of TA1, covering
- status of the ELNs
- metadata capture at the beamlines (manual and automated)
- best practices for metadata capture
- Sample PIDs
- data formats.
We present current updates on the development of snip – the user friendly collaborative lab book to document your current thoughts about the experiment online and live.
Recent improvements include:
Task Area 2 (TA2) aims to create raw- and curated open (Meta)data repositories and catalogs that align with FAIR principles across PaN radiation sources, universities, and other research institutions. The focus is on developing corresponding services to ensure FAIR data sustainability and achieve comprehensive usability of the data for the global scientific community in PaN Research. The repositories will not only contain raw and processed data but also detailed documentation of all processing, analysis steps, and sample descriptions. This approach enhances transparency, improving the quality, trustworthiness, and reusability of datasets used in scientific publications.
In this presentation, we will highlight the key achievements and deliverables of the current project status including an outlook to future developments planned for DAPHNE 2.0 as contributed by the TA2 members.
In this talk, we will present the SciCat project and its community, together with the core concepts adopted in the project. We will provide an update on the latest functionalities recently added, including the ones directly supported by the “DAPHNE4NFDI contribution for SciCat” effort. We will touch on the effort to improve documentation and to lower the barrier to adopt and deploy SciCat. Next, we will illustrate the project vision including the objectives to keep the project up to date with the latest technologies, improve user experience and foster innovation. We will conclude with few use cases illustrating best-practices on how to better support your data and metadata with SciCat.
This presentation provides an overview about the current status of SciCat at MLZ and the underlying infrastructure. Data acquisition and metadata capture are decoupled based on the RabbitMQ message broker. Information from various sources, such as the user office system, sample environment and the instrument are aggregated in the Networked Instrument COntrol System and transmitted in messages to our central Kubernetes cluster. Messages can be processed by secondary user services, e.g. the ingestor. The ingestor populates the SciCat catalogue with relevant metadata information from the experiment. A live demonstration using a virtual instrument will conclude the talk.
We will give an overview on activities within Task Area 3, with a focus on achievements, both by individual partners and on the global level, within the period since the last user meeting.
This part will cover software developments and maturation, as well as the establishment of a DAPHNE4NFDI software catalogue and activities to harmonise good software development and deployment practice.
The report will also give an outlook on future plans and challenges, affecting the remaining duration of the current DAPHNE4NFDI project, and visions for the next round ("DAPHNE-2.0"), in which we will cover topics such as implementation of machine learning methods, software integration into workflows and remote computing approaches.
The compositional optimization of new materials necessitates the high-throughput screening of a multitude of compositions, which must be investigated to elucidate the non-linear and non-monotonic structure-property-composition dependencies [1]. In this regard, data-driven material science enables researchers to accelerate the identification of new materials with desired properties for specific applications by efficiently exploring vast material spaces. Such high-throughput data-driven studies comprise two key elements: the combinatorial preparation of suitable sample libraries spanning wide compositional ranges, and the high-throughput screening of the structure and properties of the synthesized samples [2].
Surface-sensitive X-ray scattering methods available at modern X-ray sources, e.g. Grazing-Incidence Wide-Angle Scattering (GIWAXS), comprise a convenient tool for structural investigations of thin films with high screening rates and ultimate resolution. At the same time, the determination of the crystalline structure from the collected GIWAXS patterns represents a significant bottleneck of this approach as it is time- and resource-consuming, and frequently requires additional input from other methods. This makes it an ideal use case within TA3 in DAPHNE4NFDI.
In this work, we present a data analysis workflow for high-throughput and time-resolved in situ structural studies of thin films using GIWAXS. The workflow includes the following steps: data conversion and correction, metadata incorporation, Bragg peak detection, fitting and indexing [3-5]. We also present a universal data format used at all stages and a GUI software for convenient visualization of the final and intermediate results at any stage.
References:
1. A. Ludwig, npj Comput. Mater. 5 (2019), 70, https://doi.org/10.1038/s41524-019-0205-0
2. J. M. Gregoire, L. Zhou, J. A. Haber, Nat. Synth. 2 (2023), 493, https://doi.org/10.1038/s44160-023-00251-4
3. C. Völter et al., J. Appl. Cryst. (2025), in print
4. V. Starostin et al., Synchrotron Radiat. News 35 (2022), 21, https://doi.org/10.1080/08940886.2022.2112499
5. V. Starostin et al., npj Comput. Mater. 8 (2022), 101, https://doi.org/10.1038/s41524-022-00778-8
NFDI-MatWerk represents the communities of materials science and engineering, diverse in material scales, methodologies and technologies. A supporting infrastructure is built upon exemplary infrastructure use cases (IUCs), representing individual domain areas. Two such IUCs will be presented, also highlighting their use of ontologies in the materials science context:
IUC04 aims to ensure a model-driven (guided probing) collection of the relevant experimental and computational data to construct so-called defect-phase diagrams and their post-processing according to newly established simulation protocols. Another focal point is automatic semantic annotation of the computational data and its upload to an ELN system.
IUC17 has the aim of developing semantic representations describing crystalline structures and crystalline defects and their temporal evolution and to test if these descriptions are well designed and applicable for different types of simulations, experiments and microscopy. Another aspect covered is aiding domain scientists in implementing ontologies in their everyday research.
The built infrastructure services and solutions are currently in roll-out for the broader materials science and engineering community. To empower the community for FAIR research data management, NFDI-MatWerk is currently building several central services for learning, connecting and contributing to a FAIR data future.
The PUNCH4NFDI consortium has been working with developers at CERN to enable the use of the REANA workflow environment in a federated (and heterogeneous) infrastructure. While the access (Authentication) via the NFDI AAI is easy, the connection with different resource-management facilities required work. Within PUNCH4NFDI, we've connected the CoBALD/TARDIS resource manager (integrated now as module in recent REANA release) and also enabled the use e.g. of dCache storage space, albeit this is still ongoing. The use of storage resources via standard S3 protocol is available. Developing and deployment of more job controller interfaces, e.g. for SLURM clusters, is in the works.
During a ErUM data workshop, a workflow for processing of timepix3 raw data stream has been demonstrated together with HZB colleagues. The talk will give an overview of the REANA deployment within PUNCH4NFDI, and then provide some examples to discuss the advantages of a REANA component for standarized processing tasks of medium experiment data. This supports especially the "R" in FAIR.
We present an overview of research data management workflows for multidimensional characterization techniques using the NOMAD platform. Our approach focuses on efficiently handling large-volume datasets, particularly in HDF5 format, and developing specialized NeXus application definitions for emerging characterization methods. We demonstrate how cloud-based analysis tools can be seamlessly integrated into the entire workflow, illustrated by examples from electron microscopy and multidimensional photoelectron spectroscopy. By leveraging customized JupyterLab environments and desktop-based tools in the cloud, this strategy supports efficient, advanced analyses that remain tightly integrated with the NOMAD data infrastructure, eliminating the need to relocate large datasets and enhancing data shareability. Furthermore, we show how instrument inventories and sample metadata can be linked to specific measurements, enabling robust traceability and a comprehensive history throughout the entire experimental lifecycle.
The electronic laboratory notebook (ELN) Chemotion was developed to meet the specific needs of scientists in the field of chemistry regarding documentation, process description, and data analysis. Due to the interdisciplinary nature of many research groups in chemistry, various modules have been created in the past, enabling the use of the ELN in related fields and supporting interdisciplinary work far beyond chemistry. The greatest challenge in developing these modules, which extend beyond the traditional applications of chemistry, lies in the standardization and structuring of new content. To achieve standardization and structuring, close collaboration between developers and domain experts is initially required, followed by implementation within the broader scientific community. This article presents highlights from recent months that exemplify the expansion of chemistry-specific software and infrastructure into related scientific disciplines and showcase opportunities for integrating custom content. Most of the developments are in use within the community of NFDI4Chem and could also offer benefits for scientists assigned to NFDI4Cat and DAPHNE4NFDI.
Base4NFDI is the joint initiative of all 26 NFDI consortia and supports the development of basic services as common, interoperable solutions. This flashtalk is a short recap of two presentations given in advance on February 19 (https://doi.org/10.5281/zenodo.14894128) and February 25 (https://doi.org/10.5281/zenodo.14930141). It will quickly introduce the project along with four of its currently funded basic services:
PID4NFDI - a centralized infrastructure service for managing persistent identifiers within NFDI
DMP4NFDI - our basic service for data management plans (DMPs) and software management plans (SMPs) across NFDI
TS4NFDI - A Cross-Domain Terminology Service for NFDI
KGI4NFDI - Enabling Knowledge Graph Infrastructure for NFDI
Table 1: Physical Sciences in NFDI
Table 2: DAPHNE4NFDI integration to Base4NFDI (and vice versa)
Table 3: Quality insurance for public data bases & Quality control for curated reference databases
Table 4-1: LLMs Table 4-2: Machine learning
Table 5: Data processing/analysis workflows
Table 1: Physical Sciences in NFDI
Table 2: DAPHNE4NFDI integration to Base4NFDI (and vice versa)
Table 3: Quality insurance for public data bases & Quality control for curated reference databases
Table 4: LLMs
Table 5: Data processing/analysis workflows
Table 1: Physical Sciences in NFDI
Table 2: DAPHNE4NFDI integration to Base4NFDI (and vice versa)
Table 3: Quality insurance for public data bases & Quality control for curated reference databases
Table 4: Machine learning
Table 5: Data processing/analysis workflows
Modern photon science experiments generate vast amounts of high-resolution data, necessitating scalable computational solutions to ensure reproducibility, accelerate analysis workflows, and facilitate collaborative research endeavors. DECTRIS CLOUD offers a high-performance platform where scientists can deploy, share, and collaboratively use software, enhancing data curation through advanced visualization and analysis tools that facilitate better decision-making.
By integrating on-demand computing power, automated data pipelines, and secure cloud storage, DECTRIS CLOUD supports streamlined data analysis, reducing processing time while ensuring consistency across experiments. Researchers can share fully configured computational environments using DECTRIS CLOUD’s container-based approach, ensuring reproducibility by eliminating discrepancies between local setups. The platform’s real-time collaboration tools further enhance teamwork, enabling researchers to share data, monitor experiments, and refine analyses together, fostering user support in photon and neutron large-scale facilities.
This presentation will illustrate how DECTRIS CLOUD accelerates scientific discovery by providing an efficient, transparent, and collaborative platform for data analysis. We will demonstrate how cloud-enabled environments powered by DECTRIS CLOUD's advanced data curation and collaborative analysis capabilities can serve as an elastic extension of local infrastructure, improving efficiency, enhancing data integrity, and fostering transparent, collaborative research in large-scale scientific investigations.
We will give an overview on activities in Task Area 4. The task area “Outreach and dissemination” aims at informing and educating the DAPHNE4NFDI community by sharing the results obtained from the other task areas and initiate exchange and work out case studies. The starting point is the homepage www.daphne4nfdi.de where the community is informed about upcoming events, about progress of the projects and about helpful tools. This is supported by further tools like LinkedIn or the Zenodo community efforts. Meeting highlights during the past year have been the SRI2024, the user and status meetings, the DPG conferences, strategy workshops as well events of coordinatged programmes such as DFG collaboration research centres, priority programs or graduate schools. With the help of highlights, especially use cases, the engagement of the community in the project is fostered. In addition, we have successfully conducted the DAPHNE4NFDI lecture series. Further important aspects are the development of teaching material for a FAIR data management, lecture material for DAPHNE4NFDI-related topics etc. TA4 further aims at exploring new exciting topics for workshops/trainings, how DAPHNE4NFDI activities can be integrated in summer schools etc. Joint outreach and dissemination strategies are discussed as it requires the attention and input input from all DAPHNE4NFDI participants. The contribution will round up with a view on the next years including “DAPHNE2.0”.
Acknowledged contributors: Lisa Amelung, Svenja Hövelmann, Bridget Murphy, Özgül Öztürk, Christian Gutt, Amir Tosson, Frank Weber, Oliver Knodel, Paolo Dolcet and further TA4-participants
Task Area 5. The task area “External communication and policy” aims at defining common data policies, use cases and pilot workflows and standardised best practices with the aim of agreeing upon common standards. TA5 also encompasses cooperation with the other NFDI consortia, which are connected either by similar scientific questions and/or by issues of data management. Here we will also seek to coordinate and communicate with European user organisations, such as ESUO and ENSA, and the consortia of facilities, such as LEAPS and LENS. Participation in European projects (PaNOSC, etc.) that are closely linked to DAPHNE is envisaged, through partners or representatives of DAPHNE who are already active as observers.
After an intense discussion process within the European photon and neutron user communities and a joint meeting of their representing associations ENSA and ESUO, the paper „FAIR data – the photon and neutron communities move together towards open science” could be finished in April 2024. The publication by IUCrJ 01/2025 is well acknowledged by more than 1760 visits up to now. On national level, the data policies of DESY and MLZ were adapted along with FAIR and open science principles, ready to be agreed by the director’s boards.
The exchange within NFDI is an ongoing process, with activities of the consortia “Physics related sciences in NFDI” by frequent meetings, continuous exchange and a jointly organized series of related talks. DAPHNE4NFDI was invited to join similar activities of the Engineering sciences in NFDI, e.g. a joint contribution to the CoDRDI2025 conference. The data policies of DESY and MLZ were adapted along with FAIR and open science principles, ready to be agreed by the director’s boards. Interactions with other consortia – FAIRmat, 4Chem, 4Cat, and PUNCH are successfully established and now continued along topical and scientific issues.
The cooperation with Helmholtz infrastructures could be sustained and will be extended.
Within the EOSC Federation, Daphne4NFDI will be engaged not only as a part of NFDI as a national node, but also in the PaNOSC topical node selected out of 13 example nodes – continuing the established cooperation on European level.
Progress of work by colleagues from European XFEL focused on TA3 while affecting the other task areas as well. Developments of the DAMNIT system for near-online extraction and presentation of metadata and orchestration of data processing/analysis pipelines included the establishment of a web-frontend version, the preparation of an infrastructural change for a centralized database, and the prototyping of a data export interface, with the pioneering use case of communication with the Open-XPCS platform from Siegen university.
Other advancements presented will be the expanded treatment of PaNET terms for experiment techniques that are now also integrated to the data acquisition systems of our scientific instruments, the implementation of data management plans and their link to the Electronic Lab Notebook and other services at our facility, and finally work on a metadata collection, conversion and validation workflow for raw crystallographic diffraction data, which is expected to be of high interest to the DAPHNE4NFDI community.
Within DAPHNE4NFDI TA1, HZDR is developing tools for metadata capture with the aim to facilitate automatic processing of that metadata in the data management chain at HZDR. These tools (ShotSheet, SimulationLogger) are currently in testing at productive environments (TRL 7). Although the tools were developed for use cases at HZDR, they are also designed to be used elsewhere, e.g. at other partners of DAPHNE4NFDI. Therefore, the applications will be enhanced in terms of configurability and prepared for a first software publication.
Within DAPHNE4NFDI TA2, SciCat has been included into the data management chain at HZDR (currently on TRL 6) in order to provide means to expose scientific metadata to external search portals like the PANOSC data portal. So far, the data and software publication repository system of HZDR (RODARE, TRL 9) was connected to external portals within the EOSC like B2FIND or EUDAT, mainly employing bibliographic metadata for findability. SciCat enables now to also search with scientific metadata like experiment classification terms (e.g. PANET ontology) and many more. Metadata entries in SciCat can originate from the above-mentioned sources of DAPHNE4NFDI TA1 as well as from the ELN system at HZDR (MediaWiki, TRL 9). The transfer from ELN is on TRL 7, the transfer from the developed apps on TRL 2.
All these implementations and cross-connections are prototypes in order to demonstrate on actual data the functioning and to learn best practice before widening the scope for all scientific fields represented at HZDR. For the future of DAPHNE4NFDI, we plan to implement metadata standards (schemas) at the start of the data management chain. If standards exist, they should shape the metadata entry into the according form and determine data transfer and curation pipelines into the metadata repositories. A particular concern of ours is to make the underlying metadata standard in catalogues such as SciCat visible and, in particular, filterable in the future. Increasing the visibility of metadata standards in the repositories will promote the use of these standards and help to develop them further. Here we can utilize former and other projects like HELIPORT, HELPMI, NAPMIX or Semantic-X-Lab. HELIPORT allows to keep control of involved resources in an experiment, but also schemas, metadata catalogs, toolchains etc. HELPMI and NAPMIX started to define a metadata standard in the field where the metadata capturing tools have been developed, and these metadata standard drafts should be developed further. Semantic-X-Lab is a current project to extract metadata from various portals and related systems to create a comprehensive knowledge graph to reveal connections that were not previously obvious.
The ESRF Data Strategy aims at fully exploiting the potential of the 4th generation ESRF-EBS towards a fully data-centric approach. More specifically, it includes more efficient tools for data processing and data analysis, further development of metadata for an increased usability of data sets together with improved automation workflows and AI exploitation of data, as well as increased data FAIRness resulting in an increased re-use of data sets.
I will present the ESRF data strategy implementation status, introducing in particular recent software developments and how they fit into a consistent approach encompassing the entire data life cycle from beamline control (BLISS), advanced detector management (Lima2), e-Logbook, workflow management including feedback loops (EWOKS), remote data analysis (VISA), data catalogue (DRAC).
I will also briefly discuss the present status of the involvement of the ESRF in DAPHNE4NFDI. The ESRF is going to coordinate the future Photon and Neutron EOSC node which might offer new opportunities for increased collaboration with DAPHNE4NFDI and German National photon and neutron sources.
The European Spallation Source (ESS) aims to fully leverage the potential of its state-of-the-art neutron facility through a data-centric approach. This includes advanced tools for data acquisition, processing, and analysis, enhanced metadata frameworks for improved data usability, increased automation in workflows, AI-driven data insights, and strengthened adherence to FAIR principles to maximize data reusability.
Recent software developments supporting this strategy span the entire data life cycle, including the SciCat data portal, remote data analysis platforms, and automated workflow solutions. Additionally, ESS is actively engaged in European data initiatives, including collaborations within the EOSC framework and PaNOSC, fostering synergies for open science and data interoperability.
I will present the envisioned ESS data journey, highlighting our software components and their integration across the entire data life cycle, from proposal to publication.
Advances in neutron instrumentation and techniques offer new opportunities for researchers. At the same time there is an increasing demand to make measured data accessible to the wider community through improved research (meta)data- management, and for implementation of FAIR data principles by which data should be made Findable, Accessible, Interoperable and Reusable. The challenge is becoming even greater due to increasing data rates, multi-dimensional data sets and in-situ / operando experiments. New data management and analysis schemes are established, metadata capture for re-use with searchable catalogues is deployed, and on-the-fly data analysis and reduction are developed. Within the DAHNE4NFDI initiative such workflows along the whole data pipeline are exemplarily within use cases and systematically connected to prior and subsequent laboratory work. This presentation will give an overview of our activities at the Heinz Maier-Leibnitz Zentrum (MLZ) in Garching.
We are going to meet and work hands-on with selected use cases. The whole session includes a 15 minute break.
The session will begin with an introduction to PaN-Training by Oliver Knodel, followed by a short Q&A round regarding the six different use cases (see list below) and group formation. Each group will work on a dedicated use case. For this purpose, materials such as paper, cards, and pens will be available at the tables to model the use case. After this modeling step, the results will be transferred into PaN-Training, followed by a short presentation round of the outcomes. The event will conclude with a summary and outlook.
We have selected these six use case:
UC1: X-ray imaging
UC2: Correlation spectroscopy - XPCS
UC3: X-ray absorption spectroscopy
UC6: X-ray reflectivity
UC8: Neutron TOF diffraction
UC10: Diffraction & spectroscopy
Please bring:
Your Laptop