☰ Professorship Database Technologies and Data Analytics ⁞
☰ Research Interests ⚗
- NoSQL Database Systems, Distributed Database Systems
- Machine Learning for Medical Data Analytics
- Security in Cloud Databases, Privacy-Preserving Query Answering
☰ NEWS ✱
New projects starting in 2023:
- PrivacyUmbrella: Privatheit von Daten sicherstellen durch Umfassende Bereitstellung von Anonymisierungsverfahren
funded by BMBF/European Union (NextGenerationEU) Forschungsnetzwerk Anonymisierung
in collaboration with Fraunhofer ITEM, Goethe-Universität Frankfurt, Universität Mainz and MCS Datalabs GmbH
- CryptScan: Machbarkeitsstudie zu Anomalieerkennung in firmenübergreifenden Netzverkehr und datenschutzkonforme und rechtssichere Speicherung funded by Land Hessen, Distr@l program
- NoSQLConcepts: Digitale Lernbegleitung in der Datenbanklehre funded by Goethe University, DigitTell (Digital Teaching and Learning Lab) program
☰ Positions for student assistants ⚑
We offer positions for student assistants with excellent skills in data analysis pipelines, CI/CD, web service development and distributed database systems.
☰ Topics for Master, Bachelor or Project Theses ✎
Several topics are available at GU Frankfurt in the areas of
❶ Query optimization in distributed database systems
❷ Analysis and management of medical data (e.g. genome analysis, digital pathology slides).
➤ Text Book
ADVANCED DATA MANAGEMENT
FOR SQL, NOSQL, CLOUD
AND DISTRIBUTED DATABASES
375 pages, 82 figures, 31 tables
e-ISBN (PDF) 978-3-11-044141-3
Advanced data management has always been at the core of efficient database and information systems. Recent trends like big data and cloud computing have aggravated the need for sophisticated and flexible data storage and processing solutions. This book provides a comprehensive coverage of the principles of data management developed in the last decades with a focus on data structures and query languages. It treats a wealth of different data models and surveys the foundations of structuring, processing, storing and querying data according to these models.
Starting off with the topic of database design, it further discusses weaknesses of the relational data model, and then proceeds to convey the basics of graph data, tree-structured XML data, key-value pairs and nested, semi-structured JSON data, columnar and record-oriented data as well as object-oriented data. The final chapters round the book off with an analysis of fragmentation, replication and consistency strategies for data management in distributed databases as well as recommendations for handling polyglot persistence in multi-model databases and multi-database architectures.
While primarily geared towards students of Master-level courses in Computer Science and related areas, this book may also be of benefit to practitioners looking for a reference book on data modeling and query processing. It provides both theoretical depth and a concise treatment of open source technologies currently on the market.
☰ Contact ✉