Supporting and Promoting Data Science
The primary objective of the Data Science Platform (DSP) is to make data science more accessible and inclusive across the Centre and the DTU community.
The DSP is built on four pillars: support, education, innovation, and tool development
Support provide researchers and core functions at the Centre with assistance in areas such as statistics, programming, analytics, and machine learning. DSP will adopt a collaborative approach to understand the research questions and then provide the best assistance. This collaboration will be defined as consultancy, training, or implementation, depending on the needs. Whenever possible, DSP will prioritize consultancy and training to empower researchers, especially young ones, to learn data science skills that are crucial for their careers.
Education develop a training program focused on data science literacy, guiding researchers through different levels to become data-aware and proficient in data science. The training program includes initiatives such a data science club that holds periodic meetings to help researchers develop their data literacy skills, data science and bioinformatics workshops, and pop-up meetings to present trending technologies.
Innovation seeks to introduce researchers to new computational biology methods and technologies, and modernize the data science landscape at the Centre. This pillar aims to help researchers stay ahead of the curve by learning the latest technologies and techniques.
Tool development aims to transform the outputs of the other pillars into standard tools that can be shared across the Centre and open sourced for the entire community to use. This will create a comprehensive set of tools easily accessible to researchers.
We have our own notes repository which you can find at biosustain.github.io/dsp_notes/. It contains technical notes related to our work and links to our teaching materials.
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