Prof. Dr. Felix Naumann

Thorsten Papenbrock

Research Assistant, PhD Candidate

für Softwaresystemtechnik
Prof.-Dr.-Helmert-Straße 2-3
D-14482 Potsdam
Room: G-3.1.09


Phone: +49 331 5509 294
Email:  thorsten.papenbrock(a)hpi.de
Profiles: Xing
Research: GoogleScholar, DBLP, ResearchGate



Research Interests

Data Profiling:

Solving computationally complex tasks is a challenge and a central activity in data profiling. This involves primarily the discovery of metadata in many gigabyte-sized datasets, which is why algorithms developed for this purpose need to be efficient and robust. Because data profiling offers such a plethora of challenging, yet unsolved tasks, I have chosen it as my primary research area. I am in particular interested in the discovery of data dependencies, such as inclusion dependencies, unique column combinations, functional dependencies, order dependencies, matching dependencies, and many more.

Data Cleansing:

Data is one of the most important assets in any company. Therefore, it is crucial to ensure its quality and reliability. Data cleansing and data profiling are two essential tasks that - if performed correctly and frequently - help to guarantee data fitness. In this area, I am particularly interested in (semi-)automatic duplicate detection methods and normalization techniques as well as their efficient implementation.

Parallel and Distributed Systems:

Due to the complexity of many tasks in IT, a clever algorithm alone is often not able to deliver a solution in time. In these cases, parallel and distributed systems are needed. Especially when facing ever larger datasets, i.e., big data, we need to consider technologies such as map-reduce (e.g. Spark and Flink), actors (e.g. Akka), and GPUs (e.g. CUDA and OpenCL) to implement scalability into our solutions.



  • Database Systems I (2013, 2014, 2015, 2016, 2017)
  • Database Systems II (2013)
  • Data Profiling and Data Cleansing (2014)
  • Information Integration (2015)
  • Data Profiling (2017)


  • Advanced Data Profiling (2013)
  • Proseminar Information Systems (2014)

Bachelor Projects:

  • Data Refinery - Scalable Offer Processing with Apache Spark (2015/2016)

Master Projects:

  • Joint Data Profiling - Holistic Discovery of INDs, FDs, and UCCs (2013)
  • Metadata Trawling - Interpreting Data Profiling Results (2014)
  • Approximate Data Profiling - Efficient Discovery of approximate INDs and FDs (2015)
  • Profiling Dynamic Data - Maintaining Matadata under Inserts, Updates, and Deletes (2016)

Master Thesis:

    • Discovering Matching Dependencies (Andrina Mascher, 2013)
    • Discovery of Conditional Unique Column Combination (Jens Ehrlich, 2014)
    • Spinning a Web of Tables through Inclusion Dependencies (Fabian Tschirschnitz, 2014)
    • Multivalued Dependency Detection (Tim Draeger, 2016)

    Online Courses:

    • Datenmanagement mit SQL (openHPI, 2013)


    • A Hybrid Approach for Efficient Unique Column Combination Discovery. Papenbrock, Thorsten; Naumann, Felix (2017).
    • Data-driven Schema Normalization. Papenbrock, Thorsten; Naumann, Felix (2017).
    • Fast Approximate Discovery of Inclusion Dependencies. Kruse, Sebastian; Papenbrock, Thorsten; Dullweber, Christian; Finke, Moritz; Hegner, Manuel; Zabel, Martin; Zöllner, Christian; Naumann, Felix (2017).
    • RDFind: Scalable Conditional Inclusion Dependency Discovery in RDF Datasets. Kruse, Sebastian; Jentzsch, Anja; Papenbrock, Thorsten; Kaoudi, Zoi; Quiane-Ruiz, Jorge-Arnulfo; Naumann, Felix (2016).
    • Data Anamnesis: Admitting Raw Data into an Organization. Kruse, Sebastian; Papenbrock, Thorsten; Harmouch, Hazar; Naumann, Felix in IEEE Data Engineering Bulletin (2016). 39(2) 8--20.
    • A Hybrid Approach to Functional Dependency Discovery. Papenbrock, Thorsten; Naumann, Felix (2016).
    • Approximate Discovery of Functional Dependencies for Large Datasets. Bleifuß, Tobias; Bülow, Susanne; Frohnhofen, Johannes; Risch, Julian; Wiese, Georg; Kruse, Sebastian; Papenbrock, Thorsten; Naumann, Felix (2016). 1803-1812.
    • Holistic Data Profiling: Simultaneous Discovery of Various Metadata. Ehrlich, Jens; Roick, Mandy; Schulze, Lukas; Zwiener, Jakob; Papenbrock, Thorsten; Naumann, Felix (2016). 305-316.
    • Scaling Out the Discovery of Inclusion Dependencies. Kruse, Sebastian; Papenbrock, Thorsten; Naumann, Felix (2015).
    • Data Profiling with Metanome (demo). Papenbrock, Thorsten; Bergmann, Tanja; Finke, Moritz; Zwiener, Jakob; Naumann, Felix in Proceedings of the VLDB Endowment (2015). 8(12) 1860-1871.
    • Divide & Conquer-based Inclusion Dependency Discovery. Papenbrock, Thorsten; Kruse, Sebastian; Quiane-Ruiz, Jorge-Arnulfo; Naumann, Felix in Proceedings of the VLDB Endowment (2015). 8(7) 774-785.
    • Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms. Papenbrock, Thorsten; Ehrlich, Jens; Marten, Jannik; Neubert, Tommy; Rudolph, Jan-Peer; Schönberg, Martin; Zwiener, Jakob; Naumann, Felix in Proceedings of the VLDB Endowment (2015). 8(10) 1082-1093.
    • Progressive Duplicate Detection. Papenbrock, Thorsten; Heise, Arvid; Naumann, Felix in IEEE Transactions on Knowledge and Data Engineering (TKDE) (2015). 27(5) 1316-1329.
    • Ein Datenbankkurs mit 6000 Teilnehmern. Naumann, Felix; Jenders, Maximilian; Papenbrock, Thorsten in Informatik-Spektrum (2013). (12)
    • Duplicate Detection on GPUs. Forchhammer, Benedikt; Papenbrock, Thorsten; Stening, Thomas; Viehmeier, Sven; Draisbach, Uwe; Naumann, Felix (2013). 165--184.
    • Black Swan: Augmenting Statistics with Event Data. Lorey, Johannes; Naumann, Felix; Forchhammer, Benedikt; Mascher, Andrina; Retzlaff, Peter; ZamaniFarahani, Armin; Discher, Soeren; Faehnrich, Cindy; Lemme, Stefan; Papenbrock, Thorsten; Peschel, Robert Christoph; Richter, Stephan; Stening, Thomas; Viehmeier, Sven (2011). 2517-2520.