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 14th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains four revised selected regular papers. Topics covered include data stream systems, top-k query processing, semantic web service (SWS) discovery, and XML functional dependencies.

This, the 25th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five fully revised selected papers focusing on data and knowledge management systems. Topics covered include a framework consisting of two heuristics with slightly different characteristics to compute the action rating of data stores, a theoretical and experimental study of filter-based equijoins in a MapReduce environment, a constraint programming approach based on constraint reasoning to study the view selection and data placement problem given a limited amount of resources, a formalization and an approximate algorithm to tackle the problem of source selection and query decomposition in federations of SPARQL endpoints, and a matcher factory enabling the generation of a dedicated schema matcher for a given schema matching scenario.

Data management, knowledge discovery, and knowledge processing are core and hot topics in computer science. They are widely accepted as enabling technologies for modern enterprises, enhancing their performance and their decision making processes. Since the 1990s the Internet has been the outstanding driving force for application development in all domains. An increase in the demand for resource sharing (e. g. , computing resources, s- vices, metadata, data sources) across different sites connected through networks has led to an evolvement of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications prov- ing high scalability. Current decentralized systems still focus on data and knowledge as their main resource characterized by: heterogeneity of nodes, data, and knowledge autonomy of data and knowledge sources and services large-scale data volumes, high numbers of data sources, users, computing resources dynamicity of nodes These characteristics recognize: (i) limitations of methods and techniques developed for centralized systems (ii) requirements to extend or design new approaches and methods enhancing efficiency, dynamicity, and scalability (iii) development of large scale, experimental platforms and relevant benchmarks to evaluate and validate scaling Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and agent systems supporting 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.

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 48th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains 8 invited papers dedicated to the memory of Prof. Dr. Roland Wagner. The topics covered include distributed database systems, NewSQL, scalable transaction management, strong consistency, caches, data warehouse, ETL, reinforcement learning, stochastic approximation, multi-agent systems, ontology, model-driven development, organisational modelling, digital government, new institutional economics and data governance.

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 17th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of five papers, selected from the 24 full and 8 short papers presented at the 15th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2013, held in Prague, The Czech Republic, in August 2013. Of the five papers, two cover data warehousing aspects related to query processing optimization in advanced platforms, specifically Map Reduce and parallel databases, and three cover knowledge discovery, specifically the causal network inference problem, dimensionality reduction, and the quality-of-pattern-mining task.

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 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.

This, the 27th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of 12 papers presented at the Big Data and Technology for Complex Urban Systems symposium, held in Kauai, HI, USA in January 2016. The papers explore the use of big data in complex urban systems in the areas of politics, society, commerce, tax, and emergency management.

This volume, the 35th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five fully-revised selected regular papers focusing on data quality, social-data artifacts, data privacy, predictive models, and e-health. Specifically, the five papers present and discuss a data-quality framework for the Estonian public sector; a data-driven approach to bridging the gap between the business and social worlds; privacy-preserving querying on privately encrypted data in the cloud; algorithms for the prediction of norovirus concentration in drinking water; and cloud computing in healthcare organizations in Saudi Arabia.

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 22nd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six revised selected regular papers. Topics covered include algorithms for large-scale private analysis, modelling of entities from social and digital worlds and their relations, querying virtual security views of XML data, recommendation approaches using diversity-based clustering scores, hypothesis discovery, and data aggregation techniques in sensor netwo rk environments.