Science cluster
Summary
Unlocking the potential of experimental data, the project Findable Big Data from Various Material Characterisation Techniques enhances the findability of experimental datasets across photon and neutron (PaN) facilities and materials science laboratories through a foundational classification of experimental techniques. The integration of the PaNET ontology with the NeXus Ontology enables the establishment of a foundational classification of PaN experiment techniques, fostering semantic coherence across data catalogues and records within major European facilities and world-wide.
By bridging semantic gaps and establishing coherent classification systems towards ontology harmonisation, the project paves the way for seamless data discovery and analysis, empowering researchers to advance their Open Science initiatives across diverse materials characterization techniques.
Challenge
Open Science project, Open Science Service, Industry cooperation, Cross-domain/Cross-RI
In the realm of Open Science, the findability of experimental datasets presents significant challenges, particularly at PaN facilities, where data is abundant yet often dispersed across diverse platforms and repositories. The complexity of finding relevant data highlights the need for improved ontology harmonisation to optimise the data discovery process.
Solution
To improve the semantic clarity of dataset discovery, the project aims to extend and integrate the PaNET ontology into the research data management platform NOMAD, and to the metadata ecosystem of institutions, such as ESRF, or HZB. This will enhance FAIRification, by ensuring comprehensive descriptions of experimental endeavours and facilitating precise identification of the techniques utilised in each instance. This integration will improve the discoverability of datasets by providing comprehensive descriptions of experimental techniques, facilitating semantic interoperability, and establishing best practices for data management.
Our goals will be achieved by:
- Refining and enriching the PaNET ontology
- Connecting the NeXus-ET ontology and NeXus Application Classes to PaNET
- Extending the ESRF-ET ontology and connecting it to PaNET
- Integration of all this into NOMAD
Scientific Impact
The integration of the enhanced PaNET ontology into EOSC services, such as the PaN data portals and the NOMAD service developed by FAIRmat, represents a significant and exemplary milestone in advancing the accessibility and discoverability of experimental data. It enables researchers to easily find relevant experiments across different platforms and facilities.
The institutions involved in the project, from the German NFDI projects FAIRmat and DAPHNE4NFDI to the EFRI landmark ESRF, will contribute to the integration of PaNET into their respective search platforms, thus augmenting search capabilities and facilitating streamlined data discovery processes.
This enhanced data findability lays the groundwork for comprehensive analysis of experimental big data, also leveraging tools, such as the NOMAD's Artificial Intelligence Toolkit.
Principal investigator
Claudia Draxl is Einstein professor at the Humboldt-Universität zu Berlin. Her research interests cover theoretical concepts and methodology to gain insight into a variety of materials and their properties, with a focus on theoretical spectroscopy. In her group, the all-electron full-potential package exciting and the cluster-expansion package CELL are developed. Claudia Draxl is spokesperson of the NFDI consortium FAIRmat, which is developing NOMAD, a research data management service for collecting, organising, sharing, analysing, and publishing FAIR materials-science data.
