This volume, the 23rd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems,focuses on information and security engineering. It contains five revised and extended papers selected from the proceedings of the First International Conference on Future Data and Security Engineering, FDSE 2014, held in Ho Chi Minh City, Vietnam, November 19-21, 2014. The titles of the five papers are as follows: A Natural Language Processing Tool for White Collar Crime Investigation; Data Leakage Analysis of the Hibernate Query Language on a Propositional Formulae Domain; An Adaptive Similarity Search in Massive Datasets; Semantic Attack on anonymized Transactions; and Private Indexes for Mixed Encrypted Databases.

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 10th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains seven full papers chosen following two additional rounds of reviewing from revised and extended versions of a selection of papers presented at DEXA 2012. Topics covered include formal modelling and verification of web services, incremental computation of skyline queries, the implication problem for XML keys, lossless data compression, declarative view selection methods, time awareness in recommender systems, and network data mining.

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.

This, the 38th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of six papers selected from the 68 contributions presented at the 27th International Conference on Database and Expert Systems Applications, DEXA 2016, held in Porto, Portugal, in September 2016. Topics covered include query personalization in databases, data anonymization, similarity search, computational methods for entity resolution, array-based computations in big data analysis, and pattern mining.

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 19th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains four high-quality papers investigating the areas of linked data and big data from a data management perspective. Two of the four papers focus on the application of clustering techniques in performing inference and search over (linked) data sources. One paper leverages graph analysis techniques to enable application-level integration of institutional data and a final paper describes an approach for protecting users' profile data from disclosure, tampering, and improper use.

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 44th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six fully revised and extended papers selected from the 35th conference on Data Management – Principles, Technologies and Applications, BDA 2019. The topics covered include big data, graph data streams, workflow execution in the cloud, privacy in crowdsourcing, secure distributed computing, machine learning, and data mining for recommendation systems.

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 special issue contains extended and revised versions of 4 papers, selected from the 25 papers presented at the satellite events associated with the 17th East-European Conference on Advances in Databases and Information Systems (ADBIS 2013), held on September 1-4, 2013 in Genoa, Italy. The three satellite events were GID 2013, the Second International Workshop on GPUs in Databases; SoBI 2013, the First International Workshop on Social Business Intelligence: Integrating Social Content in Decision Making; and OAIS 2013, the Second International Workshop on Ontologies Meet Advanced Information Systems. The papers cover various topics in large-scale data and knowledge-centered systems, including GPU-accelerated database systems and GPU-based compression for large time series databases, design of parallel data warehouses, and schema matching. The special issue content, which combines both theoretical and application-based contributions, gives a useful overview of some of the current trends in large-scale data and knowledge management and will stimulate new ideas for further research and development within both the scientific and industrial communities.

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.

This volume, the 36th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains eight revised, extended papers selected from the 3rd International Conference on Future Data and Security Engineering, FDSE 2016, and the 10th International Conference on Advanced Computing and Applications, ACOMP 2016, which were held in Can Tho City, Vietnam, in November 2016. Topics covered include big data analytics, massive dataset mining, security and privacy, cryptography, access control, deep learning, crowd sourcing, database watermarking, and query processing and optimization.