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 (e.g. computing resources, services, metadata, data sources) 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 53rd issue of Transactions on Large-scale Data and Knowledge-centered Systems, contains six fully revised selected regular papers. Topics covered include time series management from edge to cloud, segmentation for time series representation, similarity research, semantic similarity in a taxonomy, linked data semantic distance, linguistics-informed natural language processing, graph neural network, protected features, imbalanced data, causal consistency in distributed databases, actor model, and elastic horizontal scalability.

This second issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems consists of journal versions of selected papers from the 11th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2009).

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. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the eighth issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains eight revised selected regular papers focusing on the following topics: scalable data warehousing via MapReduce, extended OLAP multidimensional models, naive OLAP engines and their optimization, advanced data stream processing and mining, semi-supervised learning of data streams, incremental pattern mining over data streams, association rule mining over data streams, frequent pattern discovery over data streams.

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. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 31st issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six revised selected papers from the 2nd International Conference on Future Data and Security Engineering, FDSE 2015, and the 9th International Conference on Advanced Computing and Applications, ACOMP 2015, which were held in Ho Chi Minh City, Vietnam, in November 2015. Topics covered include big data analytics, data models and languages, security and privacy, complex business services, and cloud data management.

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. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 41st issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains seven revised, extended papers selected from the 4th International Conference on Future Data and Security Engineering, FDSE 2017, which was held in Ho Chi Minh City, Vietnam, in November/December 2017. The main focus of this special issue is on data and security engineering, as well as engineering applications.

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. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 16th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of 7 papers, selected from the 30 papers presented at the International Conference on Advanced Computing and Applications, ACOMP 2013, held October 23-25, 2013, in Ho Chi Minh City, Vietnam. Topics covered include data engineering, information retrieval, query processing and optimization, energy-efficient resource allocation, and security and privacy.

This, the 24th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of seven papers presented at the 25th International Conference on Database and Expert Systems Applications, DEXA 2014, held in Munich, Germany, in September 2014. Following the conference, and two further rounds of reviewing and selection, six extended papers and one invited keynote paper were chosen for inclusion in this special issue. Topics covered include systems modeling, similarity search, bioinformatics, data pricing, k-nearest neighbor querying, database replication, and data anonymization.

This fifth issue of the LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems offers nine full-length focusing on such hot topics as data management, knowledge discovery, and knowledge processing.

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 (e.g., computing resources, services, metadata, data sources) 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 50th issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains five fully revised selected regular papers. Topics covered include data anonymization, quasi-identifier discovery methods, symbolic time series representation, detection of anomalies in time series, data quality management in biobanks, and the use of multi-agent technology in the design of intelligent systems for maritime transport.

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 54th issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains three fully revised and extended papers and two additional extended keynotes selected from the 38th conference on Data Management - Principles, Technologies and Applications, BDA 2022. The topics cover a wide range of timely data management research topics on temporal graph management, tensor-based data mining, time-series prediction, healthcare analytics over knowledge graphs, and explanation of database query answers.