Berlin Big Data Center (Phase 2)

October 2018 – September 2021

This project was funded by the Federal Ministry of Education and Research on the basis of a decision by the German Bundestag

The Berlin Big Data Center (BBDC) was established in October 2014 to organize and intelligently process vast amounts of data through the merger of two fields: data management and machine learning. In addition, the BBDC explored data analysis languages/systems and scalable methods of machine learning with a focus on materials research, medicine, and information marketplaces. To highlight Big Data research in Berlin and to encourage networking and collaboration, the BBDC showroom was created.

For BBDC (Phase 2), the scalability of data (related to the number and diversity of data sources) and real-time processing of continuous data streams is explored. This requires a combination of signal processing, statistical, machine learning, and artificial intelligence applications.

Project Partners

  • TU Berlin
  • TUBS
  • ZIB
  • Charité
  • Beuth University of Applied Sciences Berlin
  • DFKI

Associate Project Partners

  • Polytechnic University of Milan
  • École Polytechnique Université Paris-Sarclay
  • University of Tokyo and National Institute of Informatics
  • TU Darmstadt
  • University College London
  • Fritz Haber Institute of the Max Planck Society
  • University of Luxembourg
  • University of Basel
  • University of California-Irvine
  • University of Tokyo and RIKEN AI Center


[1] Serhan Gül, Jan Timo Meyer, Cornelius Hellge, Thomas Schierl, and Wojciech Samek. “Hybrid video object tracking in H.265/HEVC video streams”. In: 2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP). 2016, pp. 1–5. DOI: 10.1109/MMSP.2016.7813363.
[2] Wikor Pronobis, Danny Panknin, Johannes Kirschnick, Vignesh Srinivasan, Wojciech Samek, Volker Markl, Manohar Kaul, Klaus-Robert Müller, and Shinichi Nakajima. “Sharing hash codes for multiple purposes”. In: Japanese Journal of Statistics and Data Science 1 (2016), pp. 215–246.
[3] Vignesh Srinivasan, Sebastian Lapuschkin, Cornelius Hellge, Klaus-Robert Müller, and Wojciech Samek. “Interpretable human action recognition in compressed domain”. In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2017, pp. 1692–1696. DOI: 10.1109/ICASSP.2017.7952445.