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Essential Computer Tools for Researchers
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An introduction to the essential tools for organizing, managing, and sharing computational projects
Developer Environment
No upcoming dates
This topic provides an introduction to essential tools for organizing and managing computational research projects and sharing code and data with other scientists. You will learn to use Visual Studio Code to write and organize code, Git and GitHub for version control and project management, Sciebo for sharing data and other project materials, and the terminal and package managers for creating reproducible computational environments. Together, these tools can make research more reproducible, facilitate collaboration, and improve day-to-day productivity.
Prerequisites
Expected and helpful background knowledge for joining an event on this topic.
Background
- Helpful: Comfort navigating files and folders in a file explorer
- Not required: Experience with Python, Git, or package managers
Computational research projects bring together code, data, documentation, and software dependencies. Keeping these components organized makes projects easier to understand, share with collaborators, and revisit later.
In this topic, you will learn how several essential tools support different parts of that work: Visual Studio Code for writing and organizing code; Git and GitHub for version control and project management; Sciebo for sharing data and other project materials; and the terminal and package managers for creating reproducible computational environments.
Why This Matters
Small habits around files, environments, and version control shape how easy a project is to understand months later. Computing essentials are not separate from research; they are the scaffolding that keeps analyses, data, notes, and collaboration from becoming brittle. This topic builds a shared vocabulary for project folders, Git history, package managers, data sharing, and handover-ready documentation.
Questions We Can Explore Together
- What folder structure would make my current project easier for collaborators to navigate?
- How do I write a README that explains data, code, and expected outputs clearly?
- When should I use Git, GitHub, Sciebo, or another storage tool for project files?
- How can I capture enough metadata now so future analysis choices are traceable?
- What should be on a handover checklist when a student or postdoc leaves a project?
Events
Explore upcoming dates and details from previous events.
Essential Computer Tools for Researchers
Starts at
An introduction to the essential tools for organizing, managing, and sharing computational projects
Essential Computer Tools for Researchers
Starts at
An introduction to the essential tools for organizing, managing, and sharing computational projects
Essential Computer Tools for Researchers
Starts at
An introduction to the essential tools for organizing, managing, and sharing computational projects
Essential Computer Tools for Researchers
Starts at
An introduction to the essential tools for organizing, managing, and sharing computational projects
Essential Computer Tools for Researchers
Starts at
An introduction to the essential tools for organizing, managing, and sharing computational projects
Essential Computer Tools for Researchers
Starts at
An introduction to the essential tools for organizing, managing, and sharing computational projects
Essential Computer Tools for Researchers
Starts at
An introduction to the essential tools for organizing, managing, and sharing computational projects
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Essential Computer Tools for Researchers
Starts at
3 sessions
An introduction to the essential tools for organizing, managing, and sharing computational projects
iBehave PhD Retreat
Starts at
Customized programming workshops for lab retreats, department events, and group training
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Code Explorers Club
Starts at
7 sessions
A student-led seminar series where researchers shared small, practical coding techniques through short peer-learning sessions.
Technology Radar
Our view of the tools and practices relevant to this topic. Recommendation and teaching availability are separate.
Provisional positions are editorial proposals awaiting group review.
Recommendation rings
- Recommend
A recommended choice for relevant research work. - Explore
Promising or used internally; suitability or teaching integration is still developing. - Assess
Worth investigating before trying or recommending.
Kinds of item
- Libraries
- Languages & frameworks
- Tools & platforms
- Practices
- Data formats
Select a point or an item below to read our view.
Items in this view
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Recommend
Distributed version control system for tracking changes in source code
Recommend
Provisional
Tools & platforms · Teaching
5 topics with recorded teaching · 20 recorded and scheduled offerings
Our View
Git is the industry standard for version control, enabling researchers to track changes, collaborate effectively, and maintain a complete history of their work. It's essential for reproducible research and collaboration.
Recorded in topic offerings; consult the dated event links for availability.
19 past offerings · 1 upcoming offerings
Related themes: Scientific Computing
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Interactive computing environment combining code, visualizations, and narrative text
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Provisional
Tools & platforms · Teaching
6 topics with recorded teaching · 17 recorded and scheduled offerings
Our View
Jupyter notebooks allow you to combine code, results, and explanations in a single document. This makes them perfect for exploratory data analysis, teaching, and creating reproducible research workflows. You can iterate quickly, visualize results inline, and document your thought process as you work.
Recorded in topic offerings; consult the dated event links for availability.
15 past offerings · 2 upcoming offerings
Related themes: Scientific Computing
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Lightweight markup language for writing readable documentation, notes, and web content.
Recommend
Provisional
Languages & frameworks · Teaching
1 topics with recorded teaching · 1 recorded and scheduled offerings
Our View
Markdown keeps writing close to plain text while still supporting structured pages, links, code snippets, and publication workflows.
Recorded in topic offerings; consult the dated event links for availability.
1 past offerings · 0 upcoming offerings
Related themes: Scientific Computing
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Comprehensive library for creating static, animated, and interactive visualizations
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Libraries · Teaching
6 topics with recorded teaching · 19 recorded and scheduled offerings
Our View
Matplotlib is the foundational plotting library for Python, offering complete control over every aspect of your figures. It's publication-ready out of the box and integrates seamlessly with NumPy and Pandas, making it essential for visualizing research data.
Recorded in topic offerings; consult the dated event links for availability.
15 past offerings · 4 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentArrays and Numerical ComputingDataframes and StatisticsDeveloper EnvironmentLocal Field Potential (LFP) Analysis(M)EEG AnalysisNeural Spike Analysis
Modern, fast package manager built on conda-forge
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Provisional
Tools & platforms · Teaching
2 topics with recorded teaching · 10 recorded and scheduled offerings
Our View
The repository already uses Pixi to manage its toolchain. Project dependency declarations, lock files, and tasks make it a practical candidate for reproducible research environments.
Recorded in topic offerings; consult the dated event links for availability.
9 past offerings · 1 upcoming offerings
Related themes: Scientific Computing
Related topics: Automating Research WorkflowsDeveloper Environment
Python testing framework for writing simple and scalable test cases
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Provisional
Libraries · Teaching
3 topics with recorded teaching · 5 recorded and scheduled offerings
Our View
pytest makes it easy to write tests for research code, catching errors before they affect results. Its simple syntax and powerful features help ensure reproducibility and build confidence when refactoring analysis pipelines.
Recorded in topic offerings; consult the dated event links for availability.
3 past offerings · 2 upcoming offerings
Related themes: Scientific Computing
Related topics: AI-Assisted Software DevelopmentAutomating Research WorkflowsDeveloper EnvironmentRobust and Reusable Software
General-purpose programming language widely used for scientific computing and research software.
Recommend
Provisional
Languages & frameworks · Teaching
10 topics with recorded teaching · 33 recorded and scheduled offerings
Our View
Python combines a readable language with a mature scientific ecosystem, making it a practical default for research data analysis, automation, and teaching.
Recorded in topic offerings; consult the dated event links for availability.
26 past offerings · 7 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: Programming and Data AcquisitionAI-Assisted Software DevelopmentArrays and Numerical ComputingAutomating Research WorkflowsCalcium Imaging AnalysisDataframes and StatisticsDeveloper EnvironmentLocal Field Potential (LFP) AnalysisMachine Learning(M)EEG AnalysisNeural Spike AnalysisRobust and Reusable Software
Record and reproduce the software environment used for an analysis or application.
Recommend
Provisional
Practices · Teaching
0 topics with recorded teaching · 0 recorded and scheduled offerings
Our View
Declared dependencies and lock files help collaborators rerun analyses and distinguish environment changes from changes in scientific results.
Covered through our computing environment and research workflow topics; individual offerings are not yet attributed to this practice.
0 past offerings · 0 upcoming offerings
Related themes: Neural Data AnalysisScientific Computing
Related topics: AI-Assisted Software DevelopmentArrays and Numerical ComputingAutomating Research WorkflowsCalcium Imaging AnalysisDataframes and StatisticsDeveloper EnvironmentLocal Field Potential (LFP) AnalysisMachine LearningRobust and Reusable Software
Modern, extensible code editor with excellent Python support
Recommend
Provisional
Tools & platforms · Teaching
2 topics with recorded teaching · 11 recorded and scheduled offerings
Our View
VS Code combines the simplicity of a text editor with powerful IDE features. Its Python and Jupyter extensions provide an excellent environment for scientific computing, with features like interactive debugging, code completion, and integrated terminals.
Recorded in topic offerings; consult the dated event links for availability.
11 past offerings · 0 upcoming offerings
Related themes: Scientific Computing
Related topics: Programming and Data AcquisitionAI-Assisted Software DevelopmentDeveloper Environment
Explore
Package and environment manager for Python and scientific software
Explore
Provisional
Tools & platforms · Teaching
2 topics with recorded teaching · 11 recorded and scheduled offerings
Our View
Useful for existing conda-based workflows and scientific package compatibility. Compare it with Pixi when designing new reproducible project environments; the group should review which approach to teach as its default.
Recorded in topic offerings; consult the dated event links for availability.
11 past offerings · 0 upcoming offerings
Related themes: Scientific Computing
Related topics: Automating Research WorkflowsDeveloper Environment
Data and model versioning tool for machine learning and reproducible data pipelines.
Explore
Provisional
Tools & platforms · Teaching
1 topics with recorded teaching · 1 recorded and scheduled offerings
Our View
DVC gives Git-like workflows for files that are too large or too changeable to store directly in Git repositories.
Recorded in topic offerings; consult the dated event links for availability.
1 past offerings · 0 upcoming offerings
Related themes: Scientific Computing
Related topics: Automating Research WorkflowsDeveloper Environment
Web-based platform for hosting and collaborating on Git repositories
Explore
Provisional
Tools & platforms · Teaching
5 topics with recorded teaching · 18 recorded and scheduled offerings
Our View
GitHub is the de facto standard for sharing and collaborating on code. It provides excellent tools for code review, issue tracking, and project management. Most scientific software is hosted on GitHub, making it essential for reproducible research.
Recorded in topic offerings; consult the dated event links for availability.
18 past offerings · 0 upcoming offerings
Related themes: Scientific Computing
Related topics: AI-Assisted Software DevelopmentArrays and Numerical ComputingAutomating Research WorkflowsDeveloper EnvironmentRobust and Reusable SoftwareWebsite Development
Git-based collaboration platform for repositories, issues, reviews, project boards, and automation.
Explore
Provisional
Tools & platforms · Teaching
1 topics with recorded teaching · 1 recorded and scheduled offerings
Our View
GitLab combines code hosting, project coordination, and CI/CD in one place, making it useful for research groups that need transparent collaboration around shared software.
Recorded in topic offerings; consult the dated event links for availability.
0 past offerings · 1 upcoming offerings
Related themes: Scientific Computing
Related topics: Automating Research WorkflowsDeveloper EnvironmentRobust and Reusable SoftwareWebsite Development
Online whiteboard for collaborative planning, mapping, retrospectives, and visual project coordination.
Explore
Provisional
Tools & platforms · Not currently taught
0 topics with recorded teaching · 0 recorded and scheduled offerings
Our View
Miro can help research teams make project structure visible before it becomes code, especially when mapping stakeholders, workflows, priorities, or release plans.
Relevant to the topic landscape; no explicit recorded offering is currently attributed to this item.
0 past offerings · 0 upcoming offerings
Related themes: Scientific Computing
Related topics: Developer Environment
Tool for parameterizing and executing Jupyter notebooks programmatically
Explore
Provisional
Tools & platforms · Teaching
2 topics with recorded teaching · 3 recorded and scheduled offerings
Our View
Papermill lets you run the same analysis notebook with different parameters, making it easy to process multiple subjects, conditions, or datasets. It's perfect for batch processing while keeping your analysis in the familiar Jupyter format.
Recorded in topic offerings; consult the dated event links for availability.
2 past offerings · 1 upcoming offerings
Related themes: Scientific Computing
Related topics: Automating Research WorkflowsDeveloper Environment
Secure cloud storage for research data in German universities
Explore
Provisional
Tools & platforms · Teaching
2 topics with recorded teaching · 10 recorded and scheduled offerings
Our View
Sciebo provides GDPR-compliant cloud storage hosted in Germany, specifically designed for academic use. It offers generous storage quotas and integrates well with university authentication systems, making it ideal for storing and sharing research data.
Recorded in topic offerings; consult the dated event links for availability.
10 past offerings · 0 upcoming offerings
Related themes: Scientific Computing
Related topics: Arrays and Numerical ComputingAutomating Research WorkflowsDeveloper Environment
Microsoft-supported way to run Linux command-line environments directly on Windows.
Explore
Provisional
Tools & platforms · Teaching
1 topics with recorded teaching · 1 recorded and scheduled offerings
Our View
WSL helps Windows users participate in Linux-oriented research workflows without needing a separate machine, making command-line tools, package managers, and pipeline software easier to use.
Recorded in topic offerings; consult the dated event links for availability.
0 past offerings · 1 upcoming offerings
Related themes: Scientific Computing
Related topics: Automating Research WorkflowsDeveloper Environment
Video conferencing platform for online workshops
Explore
Provisional
Tools & platforms · Not currently taught
0 topics with recorded teaching · 0 recorded and scheduled offerings
Our View
Supports participation in the group’s online offerings. It is a teaching infrastructure choice rather than an analysis skill that all researchers need to learn.
Relevant to the topic landscape; no explicit recorded offering is currently attributed to this item.
0 past offerings · 0 upcoming offerings
Related themes: Scientific Computing
Related topics: Developer Environment
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