About Tilburg Science Hub
Tilburg Science Hub (TSH) is an online resource that helps individual researchers, data scientists, and teams to efficiently carry out data- and computation-intensive 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
- example workflows
- starter code
This makes it much more attractive and fun to start now, because the initial investment becomes even smaller.
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.
Who maintains TSH?
TSH is an open-source project. Its development has been financially supported by Tilburg School of Economics and Management (2019-...).
Want to contribute to this open-source initiative? Visit our GitHub page to see how.
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
- Software Carpentry's
Managing Software Research Projectslesson
- Wilson G, Aruliah DA, Brown CT, Chue Hong NP, Davis M, Guy RT, et al. (2014)
Best Practices for Scientific Computing. PLoS Biol 12(1): e1001745.
Project Setup and Workflow Management
- Gentzkow, M., & Shapiro, J.M. (2014). Code and data for the social sciences: A practitioner’s guide. Chicago, IL: University of Chicago.
- Workshop material developed at Tilburg School of Economics and Management on managing data- and computation-intensive research projects (Hannes Datta).
Material is licensed under a CC-BY-NC-SA license.