Bielefeld Center for Data Science

Data science is an interdisciplinary and holistic approach that aims at turning data into knowledge and value. It includes

  • the extraction, preparation, exploration, transformation, storage and retrieval of quantitative (“structured”) and qualitative (“unstructured”) data

as well as

  • the explanation, interpretation and exploitation of results using techniques from
  • statistics, computer science and a wide range of application areas.

In addition, data science focuses on the (further) development of new methods and competencies as well as on research data management and data security.

Data Science-"Life Cycle"

Grafic Data Science Life Cycle

Bielefeld Center for Data Science (BiCDaS) is a university-wide initiative encompassing a wide range of disciplines interested in data science. It combines existing expertise in

  • statistics, machine learning and research data management

as well as in application areas such as (in alpha order)

  • biology, business administration, computer science, data management, economics, information technology, digital humanities, law, librarianship, linguistics, physics, psychology, public health and sociology

in order to turn quantitative (“structured”) and qualitative (“unstructured”) data into knowledge and value.

The center acts as a focal point for researchers and students who enjoy the profound exchange on new challenges and solutions in data science.

Key Elements of BiCDaS

Grafic Data Science Life Cycle


Lecture Series Data Science

This winter term we offer a lecture series on Data Science.


BiCDaS now on Twitter

You can find us now on Twitter. Check here for the latest news, info and resources on Data Science!

Past news

European Conference on Data Analysis 2017 (ECDA 2017)

Date: September 27th - 29th 2017
Place: University of Economics, Wrocław

Aim: The 41st annual meeting of the German Society for Classification (GfKl, also Data Science Society) is a central, international meeting of members of the community.

Konferenz Big Data made in Germany

Date: 29th to 30th June 2017
Place: HTW Berlin and Bode-Museum Berlin

Aim: Starting with a scientific meeting on prominent use-cases of big data in physics and astronomy and big data challenges in industry, the symposium will suggest recommendations for research policies. These recommendations will be debated in a panel discussion.

Workshop zur Datenschutz-Grundverordnung

Chair: Christoph Gusy and Frank Weiler
Date: 6th to 7th February 2017
Place: ZiF - Bielefeld University

Die Datenschutz-Grundverordnung (EU) Nr. 2016/679 (im Folgenden: DS-GVO) gilt derzeit als eines der wichtigsten Reformprojekte der EU.  
Program (PDF)


Big Data
Herausforderung für Wissenschaft und Gesellschaft

Chair: Jürgen Jost (Leipzig, GER), Michael Röckner (Bielefeld, GER)
Date: 25th October 2016
Place: ZiF - Bielefeld University