01. – 06. September 2019, GI-Dagstuhl-Seminar 19363

Algorithms for Big Data


Timo Bingmann (KIT – Karlsruher Institut für Technologie, DE)
Tim Conrad (FU Berlin, DE)
Ulrich Carsten Meyer (Goethe-Universität – Frankfurt am Main, DE)
Matthias Mnich (Universität Bonn, DE)

Auskunft zu diesem GI-Dagstuhl-Seminar erteilt

Heike Clemens


Gemeinsame Dokumente


This GI-Dagstuhl workshop targets algorithms and systems for big data, with the objective to discuss and identify current research challenges and prospective solutions in the areas of big data management, algorithmic research, machine learning, distributed systems, and applications. It is mostly directed towards young researchers, in particular promising master students and PhD students in computer science with a focus on the above mentioned areas and will provide a forum for exchange of ideas, discussing and validating master thesis and PhD topics in a broader setting, as well as for networking. In particular, we want to promote the exchange of algorithmic ideas that have their sources in different scientific fields; thereby, during the workshop we expect to discover new connections between methodologies and problems that so far have been looked at from separate angles.

Prior to the workshop, we will solicit open problems and questions from the invited participants on the topics of the workshop, which will be presented during the opening sessions. Afterwords, flexible work groups will form who then attempt to solve some of those questions. To further equip the workshop participants with knowledge, we will schedule introductory survey talks by renowned experts who will give an overview of the most important algorithmic techniques in their field. At the end of each day, we will have a short update session where each working group reports on their progress which they have achieved so far. Those progresses should also be shared in the joint documents, to encourage follow-up work on the discussed matters after the end of the workshop. We envision to publish the documents as a report, in order to share the results and identified research challenges with a broader community.

Motivation text license
  Creative Commons BY 3.0 DE
  Timo Bingmann, Tim Conrad, Ulrich Carsten Meyer, and Matthias Mnich

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