The purpose of a BSS DataLab is:

1. to support and motivate the students' work with data
2. to provide students with a social community around data work

The BSS DataLab can be an extra resource for your teaching when it comes to digital methods and tools.

The students can find help with data management, data analyses and tools for this, while fellow students and library staff can contribute with guidance for the data part of the students' assignments and projects.

The students will have a physical location where they and other students can experiment and play with data.

As a teacher, you can actively use BSS DataLab in your planning of teaching and/or assignment/thesis supervision – or refer the students to the BSS Datalab when it fits into the course plan. If necessary, see BSS Datalab calendar.

As a lecturer, you are also welcome to contact the employees at BSS DataLab to hear more about the different activities.

As a teacher, you can use BSS DataLab in several ways:

Here you can find a brief description of some of the programs and tools you can get help with. 
Please contact the employee who is listed as contact if you have questions about programs, tools or methods.

Excel is the well-known spreadsheet program from Microsoft where data is organized into rows and columns.

The program provides a good overview of your data, and the many built-in functions help you process, analyze and visualize data.

Python is a versatile programming language which can be used for collecting, purification, analysis and visualisation of data.

The command-based approach scales well, and Python is therefore an obvious tool for larger datasets when more classic, visual programs fall short.

Python has a syntax that is easy to read and write, and it is therefore relatively easy to get started with.

The statistical programming language R comes with a wide range of uses, as well as the ability to extend functionality with a multitude of external packages.

You can use R to analyse data independently, but you can benefit from using R through the integrated development environment RStudio, which provides a good overview of data, variables, visualisations, files, etc.

Whisper is a tool you can use for automatic transcription of audio files based on a Large Language Model developed by OpenAI.

You can install Whisper on your own computer, but it is recommended to use Whisper Transcription through UCloud, which provides access to DeiC Interactive HPC for researchers and students. This solution will give you the most advantages with regards to both computing power and data security.

BSS Datalab can help you get started with Whisper. As a quick introduction, you can follow this guide to Whisper prepared by Aarhus BSS IT & Communication.