Marcian Seeger

Marcian Seeger is a research fellow and doctoral student in the Big Data Analytics group at Philipps-Universität Marburg. He is a computer scientist and dedicated researcher specializing in data profiling, database systems, and big data analytics.

Links

• GitHub
• LinkedIn
• ORCID
• Scholar /  dblp / ResearchGate

Publications

• Seeger, M., Schmidl, S. & Papenbrock, T.: Profiling Minimal Data Dependency Combinations. ACM Transactions on Knowledge Discovery from Data (TKDD), 2026:
  • [Paper][Project][DOI:10.1145/3799992]
• Müller, J., Seeger, M. & Papenbrock, T.: SPIND: Scalable Partial Inclusion Dependency Discovery. Proceedings of the International Conference on Extending Database Technology (EDBT), 2026:
  • [Paper][GitHub][DOI:]
• Seeger, M., & Papenbrock, T.: DPQL: Applications for Holistic Data Profiling. Proceedings of the conference on Database Systems for Business, Technology, and Web (BTW), 2025:
  • [Paper] [Project] [DOI:10.18420/BTW2025-08]
• Seeger, M., Schmidl, S., Vielhauer, A., & Papenbrock, T.: DPQL: the data profiling query language. Proceedings of the conference on Database Systems for Business, Technology, and Web (BTW), 2023:
  • [Paper] [Project] [DOI:10.18420/BTW2023-19]

Projects

• Metaserve
• EmergenCity
• LDS

Teaching

Master's Thesis:

• A Holistic Data Profiling Algorithm for the DPQL Engine (2026)
• Filter Operator Processing in the Data Profiling Query Language (2026)
• Distributed Partial Inclusion Dependency Discovery (2025)
• Partial Inclusion Dependency Discovery (2024)

Bachelor's Thesis:

• Metanome++ A System for Complex Metadata Profiling (2026)
• Metanome++ Efficient Management of Complex Metadata (2026)
• Structural Schema Matching with Similarity Flooding (2025)

Seminars

• StructureMatch