Threats Modeling And Anomaly Detection In The Behaviour Of A System - A Review Of Some Approaches.- Incremental Schema Generation for Large and Evolving RDF Sources.- Optimizing Data Coverage and Significance in Multiple Hypothesis Testing on User Groups.- Efficiently identifying disguised missing values in heterogeneous, text-rich data.- Digital Preservation with Synthetic DNA. 

The LNCS journal Transactions on Large-scale Data and Knowledge-centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 51th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains four fully revised and extended papers selected from the 37th conference on Data Management - Principles, Technologies and Applications, BDA 2021. The topics cover a wide range of timely data management research topics on threats modelling, RDF schema generation, data coverage optimization, data quality and storage on synthetic DNA.

Covers data anonymization and symbolic time series representation Discusses anomaly-detection in time series Touches on data management in biobanks and the design of intelligent systems for maritime transport