Dataset citation and acknowledgement template
Template for citing datasets, acknowledging RI services, facilities, software, workflows and data support activities used in preparing research outputs.
Resource type: Citation template
Hosted / supported by: FAIR Data Competence Center for Digital Materials Research
Purpose
This template helps users cite datasets and acknowledge the RI services, facilities, resources, software, workflows and data support activities used in preparing research outputs.
What it contains
The template includes recommended elements for dataset citation, DOI reference, authorship, repository record, facility acknowledgement, service acknowledgement, software and workflow acknowledgement, funding information and reuse statement.
How it is used
Researchers, data stewards and service providers use this template when preparing publications, dataset records, reports, presentations or pilot chain documentation. It helps ensure that datasets and RI contributions are properly credited and traceable.
Recommended use
Use this template when publishing a dataset, citing a dataset in an article, acknowledging use of an RI service, or documenting outputs from a pilot chain. The final citation and acknowledgement text should be checked against the repository record, DOI metadata and service provider requirements.
Services using this resource
FAIR packaging of computational materials datasets
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Metadata and DOI support for materials data
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Repository deposit support
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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
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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.
Навчання робочим процесам з цифровими матеріалами
Цей сервіс надає вступне та практичне навчання робочим процесам дослідження цифрових матеріалів, включаючи комп'ютерне моделювання, підготовку експериментальних даних, документування даних FAIR та використання ресурсів і послуг ДІ.
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.
Експертна консультація для користувачів ДІ
Цей сервіс надає експертні консультації користувачам ДІ, які готують обчислювальні, експериментальні або змішані робочі процеси, набори даних та документацію з матеріалознавства для використання в сервісі, публікації або у …