Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Minimal belief and negation as failure
Artificial Intelligence
Reasoning about knowledge
Consistent query answers in inconsistent databases
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
The logic of knowledge bases
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On the semantics of updates in databases
PODS '83 Proceedings of the 2nd ACM SIGACT-SIGMOD symposium on Principles of database systems
Answering queries using views: A survey
The VLDB Journal — The International Journal on Very Large Data Bases
Data exchange: getting to the core
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On the decidability and complexity of query answering over inconsistent and incomplete databases
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Representing and reasoning about mappings between domain models
Eighteenth national conference on Artificial intelligence
Mapping data in peer-to-peer systems: semantics and algorithmic issues
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Data integration under integrity constraints
Information Systems - Special issue: The 14th international conference on advanced information systems engineering (CAiSE*02)
Efficient query reformulation in peer data management systems
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Locally consistent transformations and query answering in data exchange
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Logical foundations of peer-to-peer data integration
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Logic programs for consistently querying data integration systems
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Query rewriting and answering under constraints in data integration systems
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Query answering in peer-to-peer data exchange systems
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Consistent query answering in databases
ACM SIGMOD Record
ACM Transactions on Database Systems (TODS)
On reconciling data exchange, data integration, and peer data management
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Inconsistency tolerance in P2P data integration: An epistemic logic approach
Information Systems
Consistent Data Integration in P2P Deductive Databases
SUM '07 Proceedings of the 1st international conference on Scalable Uncertainty Management
Information Sharing Agents in a Peer Data Exchange System
Globe '08 Proceedings of the 1st international conference on Data Management in Grid and Peer-to-Peer Systems
ACM Computing Surveys (CSUR)
P2P OLAP: Data model, implementation and case study
Information Systems
Local and Distributed Defeasible Reasoning in Multi-Context Systems
RuleML '08 Proceedings of the International Symposium on Rule Representation, Interchange and Reasoning on the Web
Distributed Defeasible Contextual Reasoning in Ambient Computing
AmI '08 Proceedings of the European Conference on Ambient Intelligence
Reasoning with Inconsistencies in Propositional Peer-to-Peer Inference Systems
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Intensional First-Order Logic for P2P Database Systems
Journal on Data Semantics XII
Contextual Argumentation in Ambient Intelligence
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Distributed reasoning with conflicts in a multi-context framework
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Non-conservative extension of a peer in a P2P inference system
AI Communications
The semantics of consistency and trust in peer data exchange systems
LPAR'07 Proceedings of the 14th international conference on Logic for programming, artificial intelligence and reasoning
Aspects of inconsistency resolution in modular ontologies
Canadian AI'08 Proceedings of the Canadian Society for computational studies of intelligence, 21st conference on Advances in artificial intelligence
Consistent query answering: five easy pieces
ICDT'07 Proceedings of the 11th international conference on Database Theory
Intensional semantics for p2p data integration
Journal on Data Semantics VI
Comparing inconsistency resolutions in multi-context systems
ESSLLI'10 Proceedings of the 2010 international conference on New Directions in Logic, Language and Computation
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We study peer-to-peer data integration, where each peer models an autonomous system that exports data in terms of its own schema, and data interoperation is achieved by means of mappings among the peer schemas, rather than through a global schema. We propose a multi-modal epistemic semantics based on the idea that each peer is conceived as a rational agent that exchanges knowledge/belief with other peers, thus nicely modeling the modular structure of the system. We then address the issue of dealing with possible inconsistencies, and distinguish between two types of inconsistencies, called local and P2P, respectively. We define a nonmonotonic extension of our logic that is able to reason on the beliefs of peers under inconsistency tolerance. Tolerance to local inconsistency essentially means that the presence of inconsistency within one peer does not affect the consistency of the whole system. Tolerance to P2P inconsistency means being able to resolve inconsistencies arising from the interaction between peers. We study query answering and its data complexity in this setting, and we present an algorithm that is sound and complete with respect to the proposed semantics, and optimal with respect to worst-case complexity.