This book offers readers a comprehensive guide to the evolution of the database field from its earliest stages up to the present-and from classical relational database management systems to the current Big Data metaphor. In particular, it gathers the most significant research from the Italian database community that had relevant intersections with international projects. Big Data technology is currently dominating both the market and research. The book provides readers with a broad overview of key research efforts in modelling, querying and analysing data, which, over the last few decades, have became massive and heterogeneous areas.

This book offers readers a comprehensive guide to the evolution of the database field from its earliest stages up to the present-and from classical relational database management systems to the current Big Data metaphor. In particular, it gathers the most significant research from the Italian database community that had relevant intersections with international projects. Big Data technology is currently dominating both the market and research. The book provides readers with a broad overview of key research efforts in modelling, querying and analysing data, which, over the last few decades, have became massive and heterogeneous areas.

This book constitutes the refereed proceedings of the European Conference on Logics in Artificial Intelligence, JELIA 2002, held in Cosenza, Italy in September 2002.The 41 revised full papers presented together with 11 system descriptions and 3 invited contributions were carefuly reviewed and selected from more than 100 submissions. The papers are organized in topical sections on multi-agent systems, evolution and changes, description logic and the semantic web, complexity issues, probabilistic logic, AI planning, modal logic and causal reasoning, theory, reasoning under uncertainty, satisfiability, paraconsisten reasoning, actions and caution, logic for agents, semantics, and optimization issues in answer set semantics.

This book constitutes the proceedings of the 26th International Symposium on Foundations of Intelligent Systems, ISMIS 2022, held in Cosenza, Italy, in October 2022. The 31 regular papers, 11 short papers and 4 industrial papers presented in this volume were carefully reviewed and selected from 71 submissions. They were organized in topical sections as follows: Social Media and Recommendation; Natural Language Processing; Explainability; Intelligent Systems; Classification and Clustering; Complex Data; Medical Applications; Industrial Applications.

Research has deeply investigated several issues related to the use of integrity constraints on relational databases. In particular, a great deal of attention has been devoted to the problem of extracting "reliable" information from databases containing pieces of information inconsistent with regard to some integrity constraints. In this manuscript, the problem of extracting consistent information from relational databases violating integrity constraints on numerical data is addressed. Aggregate constraints defined as linear inequalities on aggregate-sum queries on input data are considered. The notion of repair as consistent set of updates at attribute-value level is exploited, and the characterization of several data-complexity issues related to repairing data and computing consistent query answers is provided. Moreover, a method for computing "reasonable" repairs of inconsistent numerical databases is introduced, for a restricted but expressive class of aggregate constraints. An extension of this method for dealing with the data repairing problem in the presence of weak aggregate constraints which are expected to be satisfied, but not required to, is presented. Furthermore, a technique for computing consistent answers of aggregate queries in the presence of a wide form of aggregate constraints is provided. Finally, extensions of the framework as well as several open problems are discussed.