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 20th issue of
Transactions on Large-Scale Data- and Knowledge-Centered Systems presents a representative and
useful selection of articles covering a wide range of important topics in the domain of
advanced techniques for big data management. Big data has become a popular term used to
describe the exponential growth and availability of data. The recent radical expansion and
integration of computation networking digital devices and data storage has provided a robust
platform for the explosion in big data as well as being the means by which big data are
generated processed shared and analyzed. In general data are only useful if meaning and
value can be extracted from them. Big data discovery enables data scientists and other analysts
to uncover patterns and correlations through analysis of large volumes of data of diverse
types. Insights gleaned from big data discovery can provide businesses with significant
competitive advantages leading to more successful marketing campaigns decreased customer
churn and reduced loss from fraud. In practice the growing demand for large-scale data
processing and data analysis applications has spurred the development of novel solutions from
both industry and academia.
