This category is a space for the GeoLab community to share practical examples of how they are using GeoLab in research, teaching, and scientific computing workflows.
Whether you are exploring a new dataset, building a reproducible notebook workflow, teaching a course, or experimenting with cloud-based analysis, we encourage you to share your experience with the community.
What Belongs Here?
Examples of great posts for this category include:
- Research workflows and analysis pipelines
- Example notebooks or tutorials
- Data access and visualization examples
- Teaching or workshop activities using GeoLab
- Performance optimization tips
- Reproducible computing approaches
- Comparisons between local and cloud-based workflows
- Lessons learned while adapting workflows to GeoLab
You do not need to have a “perfect” workflow to post here — works in progress, experiments, and discussion-oriented posts are welcome too.
Why Share Workflows?
Sharing workflows helps:
- Other researchers learn new approaches
- New users get started more quickly
- Build reproducible and collaborative practices
- Demonstrate how GeoLab can support different scientific use cases
If you solved a problem or discovered an efficient approach, there’s a good chance others will benefit from it too.
Suggested Post Structure
To help others follow along, consider including:
What problem or question are you addressing?
Describe the scientific or technical goal.
What data or tools are you using?
Examples:
- Datasets
- Python/R packages
- Visualization tools
- External services
What does the workflow look like?
Share:
- Notebook screenshots
- Code snippets
- Processing steps
- Architecture diagrams
- Links to repositories or notebooks
What worked well (or didn’t)?
Help others understand:
- Benefits of the approach
- Limitations or challenges
- Performance considerations
- Lessons learned
Add Tags
Please add tags to help others discover relevant workflows.
Examples:
pythonvisualizationworkflowperformanceseismology
A Note on Reproducibility
Whenever possible, we encourage sharing:
- Example notebooks
- Public datasets
- Environment details
- Reproducible steps
This helps others build on your work and strengthens the collaborative value of the GeoLab community.
We’re excited to see how the community uses GeoLab — thanks for sharing your ideas and workflows!