FAIR Data Competence Center for Digital Materials Research
FAIR Data Competence Center is a digital facility that supports FAIR data packaging, metadata preparation, README and DMP guidance, dataset citation and user training for research groups working with materials science data.
Hosting partner: Kyiv Academic University
Facility type: FAIR data competence center
Current status: Operational access node
Typical users
Research groups, data stewards, RI service providers, PhD students and project teams preparing datasets, metadata, README files, DMPs and FAIR publication packages.
Data outputs
Metadata records; README files; DMP-related documentation; licence statements; dataset citation information; DOI-ready packages; FAIR data packages; documentation for reuse and long-term preservation.
Access notes
Remote and virtual access. Users receive guidance on dataset preparation, metadata fields, README files, data management plans, licensing, repository deposit workflows and citation practices. Support can be provided through consultations, templates, training sessions and pilot data packaging cases.
Related resources
Computational materials dataset profile
Minimum metadata profile for computational materials datasets, including material system, software, workflow, input parameters, calculation settings, output files, provenance links and repository deposit requirements.
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.
Technology/process dataset profile
Metadata profile for technology and process-oriented datasets, including process parameters, materials, equipment, experimental or simulation conditions, measured outputs, documentation and reuse requirements.
README template for computational materials datasets
README template for documenting computational materials datasets, including workflow description, software versions, input and output files, parameters, provenance, authorship, licence and repository information.
README template for experimental materials datasets
README template for documenting experimental materials datasets, including sample preparation, measurement method, instrument settings, raw and processed files, calibration notes, data quality and reuse information.
DMP template for RI users
Data management plan template for RI users preparing computational, experimental or mixed materials science datasets for controlled storage, documentation, publication and reuse.
Metadata checklist for materials datasets
Checklist for verifying whether a materials science dataset contains the minimum metadata needed for interpretation, validation, repository deposit, citation and future reuse.
Dataset citation and acknowledgement template
Template for citing datasets, acknowledging RI services, facilities, software, workflows and data support activities used in preparing research outputs.
FAIR checklist for materials datasets
Checklist for assessing whether a materials science dataset is findable, accessible, interoperable and reusable, with attention to metadata, identifiers, licences, provenance and repository deposit.
Services using this facility
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, …
README and DMP support for RI users
This service helps RI users prepare README files and data management plan documentation for computational, experimental and mixed materials science datasets.
Training on digital materials workflows
This service provides introductory and practical training on digital materials research workflows, including computational modelling, experimental data preparation, FAIR data documentation and the use of RI resources and …
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.
Expert consultation for RI users
This service provides expert consultation for RI users preparing computational, experimental or mixed materials science workflows, datasets and documentation for service use, publication or future onboarding.
Support for pilot use case development
This service helps partners and research groups develop pilot use cases that connect research needs, partners, facilities, resources, services and expected FAIR outputs into demonstrable RI pilot chains.
Support for computational workflow planning
This service supports research groups in planning computational materials science workflows, including task definition, software selection, input preparation, output documentation, provenance capture and FAIR data publication planning.