Instructors
Prof. Dr. Tilmann Rabl , Prof. Dr. Felix Naumann
Description
This all-to-all collaborative lecture series will feature presentations by distinguished researchers from German universities on the topic of database research. Besides an overview of topics in the field, we will introduce excellent database research groups in Germany. The lecture series is a collaboration of many database research groups and will be offered at multiple universities in parallel. The format will be hybrid with local and remote presentations and a parallel student poster session at all participating universities - a national DB event.
Recordings of the presentations are available on Tele-Task.
Agenda
The course will be held in HS 1, Tuesdays, 5pm.
| Date | Topic | Lecturer |
| 26.10.2021 | Opening & Stream Processing | Tilmann Rabl (HPI) |
| 09.11.2021 | Software-Defined Data Protection: Low Overhead Policy Compliance at the Storage Layer is Within Reach! | Zsolt István (TU Darmstadt) |
| 16.11.2021 | In-Process OLAP | Hannes Mühleisen (CWI) |
| 23.11.2021 | Tail Latencies in the DB/OS Stack | Stefanie Scherzinger (Uni Passau) |
| 30.11.2021 | Flexible Vector Processing for Data Science Engines | Wolfgang Lehner & Dirk Habich (TU Dresden) |
| 07.12.2021 | PL/SQL and UDFs are Lousy - But we can do something about it | Torsten Grust (Uni Tübingen) |
| 14.12.2021 | Learned DBMS Components | Carsten Binnig (TU Darmstadt) |
| | Break | |
| 04.01.2022 | Data Infrastructures | Volker Markl (TU Berlin) |
| 11.01.2022 | Data Structure Engineering | Viktor Leis (Uni Erlangen) |
| 18.01.2022 | Efficient Event Stream Processing | Matthias Weidlich (HU Berlin) |
| 25.01.2022 | Multi-Source Data Matching and Clustering | Erhard Rahm (Uni Leipzig) |
| 01.02.2022 | Data Provenance | Melanie Herschel (Uni Stuttgart) |
| 08.02.2022 | Data Profiling & Closing | Felix Naumann (HPI) |
| 15.02.2022 | Student Poster Session | |
General information
Time and Location: The presentations will be held in a hybrid fashion. Some of them may be conducted fully online, which we will announce beforehand.
You can access the course on Moodle.
The course is graded and has 3 ECTS.
Deliverables
Lecture summary
You have to write a summary for one lecture. Depending on the number of participants, this will be done in groups. Each lecture will be assigned to one person or group.
All summaries will be published on the course website. The summary should give a quick and engaging overview of the talk (10-15 min reading time). We will ask the presenters to review your summary and help you with questions.
Individual Poster Project
You have to prepare an A1 poster, with one of the following contents depending on your study level. You will be able to present your poster at the final session.
Bachelor Students: Based on one or more of the lectures, you can either prepare a technology landscape or explain a data science or data engineering process. Both should be as detailed as possible.
Master Students: To extend technology or methodology presented in one or multiple of the lectures, you should prepare a research project proposal. The poster should highlight goal, problem, and solution of your proposal and the connection to the lecture.
Mark Breakdown
- 50% - Lecture summary
- 50% - Individual poster project
