Our team succeeded in the Open Science II Mini-Projects call with three projects focused on FAIR physics and materials-science data.
The team of Petr Čermák from the Department of Condensed Matter Physics and the Materials Growth and Measurement Laboratory (MGML) succeeded in the Open Science II Mini-Projects call with all three submitted proposals. Two of them — LaueDB and PP2FAIR — received the maximum score of 85 points. The third project, DanCE: DANTEcore Case Example, received 81 points and was also recommended for funding.
The success of all three mini-projects confirms that research data management is becoming as essential to experimental physics infrastructure as the measurement instruments themselves. The projects connect laboratory practice, measurement automation, data standards, software development and the emerging National Data Infrastructure within the EOSC CZ initiative. Their shared goal is to ensure that data produced in physics laboratories are not merely local files stored on a disk, but become well-described, citable, interoperable and reusable scientific outputs.
LaueDB: a FAIR database of Laue diffraction images
Principal investigator: Štěpán Venclík
Project duration: 18 months
Evaluation score: 85 points
The largest of the supported mini-projects is LaueDB, which focuses on data from Laue diffraction. The Laue method is widely used for orienting single crystals, for example before experiments at large-scale research facilities. Yet these data often remain outside standard repository workflows: they are stored locally, in different formats, without unified metadata, and are difficult to reuse for further analysis or for training neural networks. LaueDB will change this. The project will create a new data and software framework for storing Laue images in the Physics Repository, specifically within the Crystallography community. It will include a metadata profile for Laue records, an API-based repository connection and an export workflow based on the NeXus format.
An important part of the project will be the extension of software tools for Laue analysis. These tools will be enhanced with the ability to convert the results of local analysis into a standardized data package and submit them directly to the repository. This will create a practical route from an experimental image and its analysis to a publishable FAIR record.
The third output of LaueDB will be a public benchmark dataset containing 1,000 annotated Laue images for 10 selected compounds. Each record will include the image, the reference crystal orientation and key experimental metadata. The dataset will serve as a basis for developing and comparing methods for automatic crystal orientation, including approaches based on machine learning.
PP2FAIR: converting PPMS data into open standards
Principal investigator: Tomáš Červeň
Project duration: 9 months
Evaluation score: 85 points
The second project to receive the maximum score is PP2FAIR – FAIRification of physical-property measurement data. The project addresses a common challenge in experimental laboratories: modern instruments generate large volumes of high-quality data, but their exports are often proprietary, inconsistent and lack the metadata needed for long-term storage and reuse. PP2FAIR will create an open-source tool for converting data from Quantum Design PPMS instruments into the NeXus format. The result will be a set of parsers, metadata mappings and validation steps that will make it possible to transform selected physical-property measurements into a form suitable for storage in an Invenio-based repository environment. The first version of the tool will focus on representative measurement types commonly produced in materials-physics laboratories: DC and AC magnetization, heat capacity, electrical and thermal transport, and torque magnetometry.
The goal is not merely to convert a few files once. PP2FAIR is intended to create a repeatable tool that can be further extended to additional measurement types and used in everyday data-management workflows. The project will connect the experimental infrastructure of MGML with the repository and metadata ecosystem of Open Science II, demonstrating a practical path towards turning laboratory data into well-described, validated and reusable outputs.
DanCE: DANTEcore Case Example
Principal investigator: David Sviták
Project duration: 3 months
Evaluation score: 81 points
The third supported project is DanCE: DANTEcore Case Example. Although smaller in scope, it is methodologically very important: its aim is to transform an existing scientifically valuable data package into an exemplary FAIR dataset. The project will focus on the dataset Magnetic structures of Na₂BaMn(PO₄)₂, which is linked to published research on the magnetic structures of this compound. The output will bring together data from sample preparation through individual measurements to processed data, scripts and links to the related article. Instead of a loosely assembled package of files, the result will be a curated, publicly citable dataset with a DOI, open metadata and a clearly described structure.
DanCE will also serve as a practical test of the DANTEcore metadata profile. Although it is the smallest of the three mini-projects, its significance is broader: DanCE will provide a concrete reference example of what a well-prepared FAIR dataset in materials physics can look like.
A shared goal: from measurements to reusable data
Together, the three projects cover the full practical chain of working with experimental data. LaueDB addresses the standardization and storage of diffraction image data, PP2FAIR converts instrument data from physical-property measurements into open formats, and DanCE demonstrates what a complete curated dataset linked to a published scientific result can look like. Their common aim is to move physics data from local and often informal storage towards long-term reusable scientific objects. Such data can be cited, checked, reanalysed, combined with other sources and used to develop new methods, including machine learning.
