Experimental materials characterization profile
Minimum metadata profile for experimental materials characterization datasets, including sample description, method, instrument, measurement conditions, raw and processed data, calibration information and provenance links.
Resource type: Metadata profile
Hosted / supported by: FAIR Data Competence Center for Digital Materials Research
Purpose
This profile defines the minimum information needed to describe, interpret, publish and reuse experimental materials characterization datasets. It is intended for datasets produced by laboratory measurements, core facilities and experimental access services in materials science.
What it contains
The profile covers the investigated material or sample, preparation procedure, characterization method, instrument, measurement conditions, raw and processed data, calibration or reference information, data quality notes, provenance, authorship, licence and repository deposit information.
How it is used
Researchers, facility staff and data stewards use this profile when preparing experimental datasets for documentation, publication, DOI assignment, citation and reuse. It helps ensure that experimental results can be interpreted correctly and connected to the instrument, method, sample and measurement conditions.
Minimum metadata blocks
- Material or sample description
- Sample preparation procedure
- Characterization method
- Instrument or equipment used
- Measurement conditions and parameters
- Raw experimental data
- Processed data and derived results
- Calibration, standards or reference information
- Data quality notes
- Provenance links
- Authors and affiliations
- Licence and reuse conditions
- Repository record and DOI
Services using this resource
Thermomechanical testing and simulation of welding-related processes
Thermomechanical testing and simulation of welding-related processes is an integrated experimental-computational service for studying materials, welded joints and welding-related thermal and mechanical effects. The service provides access to …
Semiconductor materials, structures and device diagnostics
Semiconductor materials, structures and device diagnostics is an integrated experimental service for the characterization of semiconductor materials, thin films, nanostructures, multilayer structures and semiconductor-based devices. The service combines …
Magnetic properties measurement
Magnetic properties measurement is an experimental characterization service for studying the magnetic behaviour of metallic materials, alloys, thin films, nanostructured materials, functional magnetic materials and related material systems. …
Mechanical testing of metals, alloys and welded joints
Mechanical testing of metals, alloys and welded joints is an experimental access service for determining mechanical behaviour and performance of metallic materials, alloys, structural materials and welded samples …
FAIR packaging of experimental materials datasets
This service helps users prepare experimental materials datasets for publication, citation and reuse. It focuses on structuring raw and processed experimental data, documenting methods and instruments, preparing README …
Metadata and DOI support for materials data
Metadata and Digital Object Identifier (DOI) support for materials data is a critical aspect of open science, ensuring that datasets are findable, accessible, interoperable, and reusable (FAIR). DataCite, …
Repository deposit support
This service supports users in preparing and submitting repository-ready datasets for publication, citation and long-term preservation through DataverseUA or another suitable trusted repository.
Reproducible computational workflows with Jupyter / AiiDA
This service supports users in understanding and preparing reproducible computational workflows based on Jupyter notebooks, AiiDA workflow management and related computational materials science tools.
Відтворювані обчислювальні робочі процеси з Jupyter / AiiDA
Цей сервіс допомагає користувачам розуміти та готувати відтворювані обчислювальні робочі процеси на основі блокнотів Jupyter, керування робочими процесами AiiDA та пов'язаних з ними інструментів обчислювального матеріалознавства.