About Tilburg Science Hub
Tilburg Science Hub (TSH) is a platform helping individual researchers, data scientists and their teams to efficiently work on empirical research projects. It provides information about workflow and data management and tutorials that teach researchers how to organize and document their data and code, so the research becomes sustainable and reproducible. This in turn leads to time savings and transparency in the process.
Why was TSH developed?
We see two major reasons why it pays off to use professional tools to carry out empirical projects. First, the initial investment pays off very quickly. There are many tools that are tremendously helpful and many things can be automated, which also helps to avoid errors. Second, it increases transparency and contributes to reaching the goal of making science reproducible.
What does TSH offer?
Many of us face the same dilemma. We know that a small investment will have big returns, but we put off making it because we lack the time to make it now. TSH makes it easier to make this investment now by providing:
- information about all one needs to know to get started,
- code snippets ("building blocks"), and
This makes it much more attractive and fun to start now, because the initial investment becomes even smaller.
Curious to learn more? Then take a tour of Tilburg Science Hub now!
Who is TSH for?
First, (research master and PhD) students will be able to quickly become operational and learn not only about how to properly code a specific algorithm but also how to address specific marketing-related problems.
Second, academics will be able to (1) reproduce published work in a more efficient way and (2) identify codes that might be useful for them and appropriately use them and (3) potentially become contributors to the repository at little cost.
Third, companies interested in marketing analytics will be able to get efficient training to state-of-the-art marketing analytics tools (published in top marketing journals), and access to code which they could understand and adapt to their own situation.
Are you just starting out? Read our onboarding wiki to get started!
Who maintains TSH?
TSH is an open-source project. Its development has been financially supported by Tilburg School of Economics and Management (2019-...).
The project consists of:
- A Core Team who manages the platform. Currently, the platform is managed by Hannes Datta and Tobias Klein.
- A Lab of Research Assistants, Teaching Assistants, and Ph.D. students who further develop the platform and support researchers with their empirical projects.
- A group of Researchers who can benefit from the support of the Lab and implement our new way of working in their research projects.
Some material is based on the fantastic (open source) works of others - see below.
Want to contribute to this open-source initiative - as a researcher, student, research assistant or volunteer? Visit our GitHub repository to see how. Or read the Tilburg Science Lab Onboarding Guide to become part of Lab.
Meet Tilburg Education Hub
We also recently started a hub to the world of open education, through which you can access and share open education resources developed at Tilburg University. Learn more about our sister project, Tilburg Education Hub!
Feel free to reach out to us at tsh [at] tilburguniversity [dot] edu.
We are grateful to the following "sister" initiatives from which we have borrowed some of our content.
Installation Guide, Programming Practices for Research in Economics
University of Zurich, by Ulrich Bergmann, Lachlan Deer, Adrian Etter, Julian Langer, Ursina Schaede, Dora Simon, Max Winkler, Carlo Zanella & Christian Zünd.
Programming Practices For Economists
By Lachlan Deer, Adrian Etter, Julian Langer & Max Winkler.
Effective Programming Practices for Economists
A course by Hans-Martin von Gaudecker.
Managing Software Research Projects
A lesson by Software Carpentry.
Best Practices for Scientific Computing.
Wilson G, Aruliah DA, Brown CT, Chue Hong NP, Davis M, Guy RT, et al. (2014) PLoS Biol 12(1): e1001745.
Project Setup and Workflow Management
Code and data for the social sciences: A practitioner’s guide
Gentzkow, M., & Shapiro, J.M. (2014). Chicago, IL: University of Chicago.
Workshop material developed at Tilburg School of Economics and Management on managing data- and computation-intensive research projects.
By Hannes Datta.
Text and content are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.