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.
What the user gets
Users receive practical guidance on how to document computational steps, organise input and output files, capture workflow provenance, prepare notebook-based examples and connect computational results with FAIR data packaging and repository deposit workflows.
Service category: Training and Consultancy Service
Hosting partner: Kyiv Academic University
Related node / facility: FAIR Data Competence Center for Digital Materials Research
Resources used
- AiiDA
- Jupyter-based workflows
- Computational materials dataset profile
- Experimental materials characterization 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
- FAIR data package
FAIR requirements
Computational workflows should include sufficient information about software versions, input parameters, execution environment, workflow steps, output files, provenance links, authorship and repository-ready documentation for reuse and validation.
User obligations
Users are expected to provide the scientific task, software context, input parameters, relevant scripts or notebooks, expected outputs and sufficient information to document the workflow for reproducibility and future reuse.