Welcome to the Database Research Group
The Database Research Group is part of the Department of Computer Science at the University of Salzburg, Austria.
In our research, we deal with all aspects of data management. We are attracted by applications that are heavily based on data but cannot leverage current systems due to the rich set of queries they need. The focus of our research is on queries over complex objects and massive data collections, data cleaning and integration, indexing techniques, query processing and optimization, distributed data management, and numerical computations in databases. Our research is triggered by problems that arise in concrete applications, for example, process mining, digital humanities, or cognitive neuroscience. The results of our research are new algorithms with performance guarantees, which are implemented and evaluated on the motivating application.
Nikolaus Augsten
Head of the Database Research Group
Martin Schäler
Deputy Head of the Database Research Group
News
Our paper “SeDA: Bridging the Gap between Efficient Syntactic and Precise Semantic Search of Similar Passages in Large Text Corpora” has been accepted at the International Conference on Very Large Data Bases (VLDB) 2026.
Our Ph.D. student Daniel Ulrich Schmitt received the Young Investigators Award 2025 at the Faculty of Digital and Analytical Sciences at the University of Salzburg. Daniel won the 1st price for his work “Efficient, Extensible, and Robust Similarity Queries” and more information can be found here.
Our paper “Extensible and Robust Evaluation of Similarity Queries” has been accepted at the International Conference on Very Large Data Bases (VLDB) 2025.
Our paper “Towards Practicable Algorithms for Rewriting Graph Queries beyond DL-Lite” has been accepted at the Extended Semantic Web Conference (ESWC) 2025.
Our paper “Open benchmark for filtering techniques in entity resolution” has been published at The VLDB Journal (Springer).
Our paper “Scalable Distributed Inverted List Indexes in Disaggregated Memory” has been accepted at the ACM International Conference on Management of Data (SIGMOD) 2024.
Our paper “A Two-Level Signature Scheme for Stable Set Similarity Joins” has been accepted at the International Conference on Very Large Data Bases (VLDB) 2023.
The reproducibility package of our paper “JEDI: These aren’t the JSON documents you’re looking for…” won the “Best Artifact Award” at the ACM International Conference on Management of Data (SIGMOD) 2023.
Our paper “Feedforward-Aided Course Designs for Similarity Search” has been accepted at the International Workshop on Data Systems Education (DataEd) 2023.
Our paper “Benchmarking the Utility of w-event Differential Privacy Mechanisms - When Baselines Become Mighty Competitors” has been accepted at the International Conference on Very Large Data Bases (VLDB) 2023.