Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXIV: Special Issue on Consistency and Inconsistency in Data-Centric Applications [Paperback]

This volume, the 34th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, constitutes a special issue consisting of seven papers on the subject of Consistency and Inconsistency in Data-Centric Applications. The volume opens with an invited article on basic postulates for inconsistency measures. Three of the remaining six papers are revised, extended versions of papers presented at the First International Workshop on Consistency and Inconsistency, COIN 2016, held in conjunction with DEXA 2016 in Porto, Portugal, in September 2016. The other three papers were selected from submissions to a call for contributions to this edition. Each of the papers highlights a particular subtopic. However, all are concerned with logical inconsistencies that are either to be systematically avoided, or reasoned with consistently, i.e., without running the danger of an explosion of inferences.

Basic Postulates for Inconsistency Measures.- Batch Composite Transactions in Stream Processing.- Enhancing User Rating Database Consistency through Pruning.- A Second Generation of Peer-to-Peer Semantic Wikis.- Formalizing a Paraconsistent Logic in the Isabelle Proof Assistant.- A Proximity-Based Understanding of Conditionals.- Inconsistency-Tolerant Database Repairs and Simplified Repair Checking by Measure-Based Integrity Checking.

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£*