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.
What the user gets
Users receive guidance on how to translate a scientific modelling task into a documented computational workflow, select suitable tools, define input and output requirements, plan execution steps and prepare results for validation, reuse and repository deposit.
Service category: Training and Consultancy Service
Hosting partner: Kyiv Academic University
Related node / facility: FAIR Data Competence Center for Digital Materials Research
Resources used
- Quantum ESPRESSO
- AiiDA
- Jupyter-based workflows
- DataverseUA repository
- Computational materials dataset profile
- README template for computational materials datasets
- DMP template for RI users
- Metadata checklist for materials datasets
- Dataset citation and acknowledgement template
- FAIR checklist for materials datasets
Access modes
- Remote access
- Virtual access
- Collaborative access
- Pilot access
Typical data outputs
- Simulation input files
- Simulation output files
- Workflow provenance
- Notebook
- Metadata record
- README file
- Report
FAIR requirements
Computational workflow planning should define the scientific question, software and workflow components, input parameters, expected outputs, documentation needs, provenance capture method, metadata requirements and publication or preservation route.
User obligations
Users are expected to provide the modelling objective, material system, preferred software or methods, available input data, expected outputs, validation needs and information required to document the workflow and resulting datasets.