%0 Conference Paper %1 lenzerini2014quality %A Lenzerini, Maurizio %A Console, Marco %B Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence %D 2014 %K Consistency OBDA optique-project %P 1020-1026 %T Data Quality in Ontology-based Data Access: The Case of Consistency %X Ontology-based data access (OBDA) is a new paradigm aiming at accessing and managing data by means of an ontology, i.e., a conceptual representation of the domain of interest in the underlying information system. In the last years, this new paradigm has been used for providing users with abstract (independent from technological and system-oriented aspects), effective, and reasoning-intensive mechanisms for querying the data residing at the information system sources. In this paper we argue that OBDA, besides querying data, provides the right principles for devising a formal approach to data quality. In particular, we concentrate on one of the most important dimensions considered both in the literature and in the practice of data quality, namely consistency. We define a general framework for data consistency in OBDA, and present algorithms and complexity analysis for several relevant tasks related to the problem of checking data quality under this dimension, both at the extensional level (content of the data sources), and at the intensional level (schema of the data sources).

@inproceedings{lenzerini2014quality, abstract = {Ontology-based data access (OBDA) is a new paradigm aiming at accessing and managing data by means of an ontology, i.e., a conceptual representation of the domain of interest in the underlying information system. In the last years, this new paradigm has been used for providing users with abstract (independent from technological and system-oriented aspects), effective, and reasoning-intensive mechanisms for querying the data residing at the information system sources. In this paper we argue that OBDA, besides querying data, provides the right principles for devising a formal approach to data quality. In particular, we concentrate on one of the most important dimensions considered both in the literature and in the practice of data quality, namely consistency. We define a general framework for data consistency in OBDA, and present algorithms and complexity analysis for several relevant tasks related to the problem of checking data quality under this dimension, both at the extensional level (content of the data sources), and at the intensional level (schema of the data sources).}, added-at = {2014-10-15T14:55:55.000+0200}, audience = {academic}, author = {Lenzerini, Maurizio and Console, Marco}, biburl = {https://www.bibsonomy.org/bibtex/2c5ae43245ed7d140ed2d4a22e22a8bba/savo.fabio}, booktitle = {Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence}, interhash = {a78e94e9f9d54dd052bd4f5408e069e0}, intrahash = {c5ae43245ed7d140ed2d4a22e22a8bba}, keywords = {Consistency OBDA optique-project}, openaccess = {Yes}, pages = {1020-1026}, partneroptique = {UNIROMA1}, timestamp = {2016-12-01T19:12:25.000+0100}, title = {Data Quality in Ontology-based Data Access: The Case of Consistency}, wpoptique = {WP4}, year = 2014, yearoptique = {Y2} }