Use Cases

Overview of the DAPHNE4NFDI Use Case Workflows

General Description

The DAPHNE4NFDI consortium is a key player in advancing research data management in photon and neutron sciences. It enables more efficient data utilization by providing innovative solutions for the collection, storage, and processing of large datasets. By integrating state-of-the-art infrastructure with user-oriented solutions, researchers from various disciplines are supported in making data Findable, Accessible, Interoperable, and Reusable (FAIR principles). By using use cases as test fields, the consortium develops technical solutions to address real-world challenges. These use cases enhance research efficiency, foster interdisciplinary collaboration and innovation, and sustainably improve data reusability.

Each use case demonstrates how tailored data solutions fulfill specific scientific needs within a particular domain. These best-practice solutions serve as models that can easily be transferred to related scientific disciplines. The respective use cases have been realized through the integration of existing products, their domain-specific enhancement, and the complete development of new products. This underscores the consortium's ability to adapt IT infrastructure solutions precisely to domain requirements or create new approaches, illustrating how DAPHNE4NFDI bridges the gap between data generation and scientific application while paving the way for more efficient, transparent, and reproducible research.

The eleven use cases listed in the table below showcase the diversity of solutions and approaches. These examples highlight the importance of collaboration between research facilities, data providers, and end users, driving scientific breakthroughs across various fields.

11 Different Use Case Workflows

Nr. Name Description
1 X-ray imaging Biological matter: Advanced imaging techniques for non-invasive, high-resolution visualisation of biological tissue.
2 Correlation spectroscopy - XPCS Dynamics: Coherent X-ray scattering for the investigation of time-resolved processes in materials.
3 X-ray absorption spectroscopy Amorphous materials and catalysis: XANES/EXAFS techniques for analysing the structure and function of materials.
4 X-ray emission spectra, RIXS Chemical systems: Advanced emission spectroscopy to study chemical bonding and electronic structures.
5 Spectroscopy Correlated electron systems: Inelastic scattering techniques to study complex electronic interactions.
6 X-ray reflectivity Soft matter and interfaces: High-precision methods to study surface and interface properties.
7 Ultrafast/magnetic X-ray scattering Magnetic structures: Techniques for the investigation of ultrafast dynamics and magnetic phenomena.
8 Neutron-TOF diffraction Structure refinement: High-resolution neutron diffraction for precise structure characterisation.
9 Tomography Construction materials: neutron and photon tomography for material and structural analysis.
10 Diffraction & spectroscopy Proteins and food science: Combined diffraction and spectroscopy techniques for biomolecular research.
11 High-energy X-ray diffraction Elektrochemie und Katalyse: Fortschrittliche Beugungstechniken zur Untersuchung hochenergetischer Materialien.

Each use case has been carefully designed to address specific scientific challenges while leveraging the robust infrastructure and collaboration network of DAPHNE4NFDI. For example:

  • X-ray Imaging in Biological Matter: Addressing bottlenecks in data management for high-resolution imaging through the integration of metadata and processing tools.
  • X-ray Absorption Spectroscopy: Establishing certified, shared databases for amorphous materials and catalysis to ensure data quality and reusability.
  • Inelastic Scattering for Electron Systems: Developing vocabularies and tools for metadata capture and implementing ELNs to optimize workflows.

And we have developed a modular and scalable IT infrastructure in such a way that all these 11 different use cases can be addressed through a standardized process – only the details differ. In broad terms, the standardized process for all use cases is as follows:

Standardised Template for Use Case Workflows

1. Planning and Preparation

  • Drafting a peer-reviewed proposal to define the scientific question.
  • Documenting experimental parameters and preparing the samples.
  • Integrating persistent identifier services (e.g., IGSNs) for samples to ensure traceability.

2. Data Collection

  • Using advanced scientific instruments (e.g., synchrotrons, spectrometers, neutron sources) to collect raw data.
  • Directly integrating metadata acquisition into experimental workflows using electronic laboratory notebooks (ELNs).
  • Ensuring data quality and performing initial data processing on-site.

3. Data Management and Storage

  • Storing raw data in Nexus or ASCII format to ensure interoperability.
  • Utilizing metadata catalogs (e.g., SciCat) for structured data organization.
  • Providing data as "Open Data" to comply with FAIR principles.

4. Data Analysis and Modeling

  • Extracting, adapting, and modeling data using machine learning and tailored algorithms.
  • Validating results through fitting and modeling.
  • Storing and publishing analyzed data in publicly accessible databases.

5. Publication and Dissemination

  • Publishing scientific results along with open data, software tools, and sample information (IGSN).
  • Promoting transparency and reusability through detailed documentation and adherence to quality standards.

6. Feedback and Optimization

  • Collecting user feedback through workshops and surveys.
  • Adapting the process to incorporate new scientific insights and practical requirements.