🗃️ Tools & Languages
4 items
📄️ Containers
What Are Containers?
📄️ Data Types
Depending on your research questions, you may encounter various categories of data. Data type describes the kind of data and defines how it is stored, what operations can be applied to it, and what analysis or models are valid.
📄️ File formats
A file format specifies the way information is encoded in a file on disk. Depending on the type of data that are to be stored, different file formats are appropriate.
📄️ Git & Version Control
What is Version Control?
📄️ Computing Infrastructure
This page provides an overview of the different types of computing and storage infrastructure available to researchers at the Technical University of Munich. Whether you need high-performance computing resources, cloud-based solutions, or specialized AI systems, TUM and its partners offer a wide range of options to support your research.
📄️ Metadata
Metadata is often defined as "data about data." It refers to the structured information used to describe a data point or a dataset, covering its structure, content, and unique features. High-quality metadata is the key to ensuring your research remains findable and usable by both systems and other researchers (including your future self).
📄️ Operating systems
An operating system is the collection of software that manages a computer's resources and acts as a layer between the firmware and application (i.e. user-facing) software.
📄️ Repository Collections
A repository is a structured digital platform for storing, documenting, preserving, and sharing research data or publications, ensuring they remain accessible, citable, and reusable over time.
📄️ Workflow Management Systems
Workflow Management Systems (WMS) are tools designed to define, run, and monitor complex data-processing pipelines in a structured and reproducible way. They help automate multi-step analyses, manage dependencies between tasks, and ensure that results can be reliably regenerated. WMS are widely used in data science, bioinformatics, and large-scale computing to reduce manual work and human error. They also make it easier to scale analyses from a laptop to clusters or cloud platforms.