Contribute
Tutorials Building Blocks Examples About
Contribute
Building Blocks
Configure your computer
Statistics and ComputationGit and GitHub LaTeX MATLAB Pandoc Perl Python Python Packages R and RStudio Stata Text editors
Automation and WorkflowsAWS Client Command Line Tools Make Making Path Settings Permanent Snakemake TeamViewer
Task-specific ConfigurationsConfiguring Python for Web Scraping
Research InfrastructureLearn about the various ways to setup a research infrastructure
Develop your coding skills
Learn to CodeLearn Bash Commands Learn Python and Julia Learn R Learn Regular Expressions
TipsPrinciples for Good Coding
Collect your data
Web Scraping & APIsAvoid Getting Blocked While Scraping Extract Data From APIs Read & Write Data From APIs Scrape Dynamic Websites Scrape Static Websites
Workflows for Online Data CollectionAssess what Data is Available Calculate Sample Sizes for Web Scrapers Monitor and Safeguard Your Data Quality Online Data Collection and Management Safeguard Legal Compliance When Scraping
Store and document your data
Store DataChoose a Data Repository for Long-Term Storage Configure Environment Variables Download Data Programmatically Use AWS S3 Buckets
Document DataDocument New Data README Best Practices
Prepare your data for analysis
Data PreparationImport Large Datasets Into R Manipulate Data Clean Data Scraped From Social Media Data Preparation and Workflow Management
Analyze data
RegressionsRun a Regression Analysis
Machine LearningIn-depth Introduction to Machine Learning and R
Automate and execute your work
Automate your WorkflowUse Makefiles to Re-Run your Code Use this checklist to improve your project's structure Schedule recurring tasks (e.g., by day, hour) Share Large Temporary Files Use Software Environments to Ensure Replicability
Error HandlingMake Stata Crash when encountering Errors
Collaborate and share your work
Use GitHub to Share your WorkMake Your Code Citable with DOI The Most Important Git Commands You Should Know Versioning using Git and GitHub Work with Large Files on GitHub
Write your PaperWrite a Professional Research Paper with LyX Create Slides in No Time with LyX Get Started With Our LaTeX Templates Export Your Tables for Print-ready Publications Cheatsheet for LaTeX Math Commands
Publish on the WebBuild Interactive Dashboards With R Shiny

Be smart.
Conduct your research differently.

Tilburg Science Hub gives you the tools and guidance to be in control and save time in your empirical research projects.

Learn science the new way, with our online tutorials
Use our code snippets in your projects right away
Kickstart your project with our curated examples

Catch mistakes
early.

No code is perfect, and making mistakes is part of the process. Following the principles of reproducible science, you will be able to catch mistakes early. And fewer mistakes means faster progress.

Automate
your pipeline.

Have you ever considered how much time you've wasted waiting behind a screen for data preparation or results? When automating your project, you let the computer take care of it for you, while you can work on something else.

An efficient way of
collaborating.

Colleagues still using GitHub like Dropbox? Learn how to collaborate using code versioning the right way.

Reach a broader
audience.

Share your work the new way, with websites, dashboards, and videos.

A source of
inspiration.

Check out our examples from real-life research projects to help you get started with your own one.

Who we are


Tilburg Science Hub is an open-source project run by researchers from Tilburg University, in The Netherlands. We seek to enable students, researchers, and data science teams to set up, manage, and collaborate more efficiently on empirical research projects.