Data Science Centre

Managing, analysing and sharing data at scale

To foster both research and services, the EMBL Data Science Centre has been established to ensure that data generated  are expertly curated, annotated, managed, integrated, visualised, and shared.

The Data Science Centre aims to facilitate research advances in data science, offers internal and external services, tools and resources, develops common representations (data, conventions, workflows) and contributes to training and career development via the activities of our priority areas are focus of our activities.

The Data Science Centre collaborates with all EMBL sites to realise progress on the following priority areas as part of its workstreams, including internal and external training, integrated data management, scientific workflow sharing, AI, provision of public data services, and technical infrastructure. 


EMBL’s new Data Sciences Programme aims to connect data science centres focused on five priority areas at all EMBL sites. Credit: Spencer Philips/EMBL

The Data Science Centre aims to

    • Facilitate research advances in Data Science
    • Offer internal service: research support for biologists
    • Offer external service: critical tools & data resources
    • Develop common representations: data, conventions, workflows
    • Contribute to training & career development

“The exponential increase in the volume of biological data every 18 months is a challenge that many institutions face. It underscores the need for this Data Sciences Centre. We want to tackle data challenges by working together with our staff and fellows and ultimately share our solutions with others.”

Data Science Centre activities

Data management

In the future, you will find information on the data management efforts

Supported activities

AI and machine learning

Supporting world class research, building global collaborations, and helping to define the role of artificial intelligence (AI) and machine learning in the life sciences

Open Science

Openness, transparency, and the open publication of results in the form of research articles, software and data


In the future, you you will able to learn about upcoming and past data-science related events