{"title":"A framework for automatic schema mapping verification through reasoning","authors":"P. Cappellari, Denilson Barbosa, P. Atzeni","doi":"10.1109/ICDEW.2010.5452703","DOIUrl":null,"url":null,"abstract":"We advocate an automated approach for verifying mappings between source and target databases in which semantics are taken into account, and that avoids two serious limitations of current verification approaches: reliance on availability of sample source and target instances, and reliance on strong statistical assumptions. We discuss how our approach can be integrated into the workflow of state-of-the-art mapping design systems, and all its necessary inputs. Our approach relies on checking the entailment of verification statements derived directly from the schema mappings and from semantic annotations to the variables used in such mappings. We discuss how such verification statements can be produced and how such annotations can be extracted from different kinds of alignments of schemas into domain ontologies. Such alignments can be derived semi-automatically; thus, our framework might prove useful in also greatly reducing the amount of input from domain experts in the development of mappings.","PeriodicalId":442345,"journal":{"name":"2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010)","volume":"376 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDEW.2010.5452703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
We advocate an automated approach for verifying mappings between source and target databases in which semantics are taken into account, and that avoids two serious limitations of current verification approaches: reliance on availability of sample source and target instances, and reliance on strong statistical assumptions. We discuss how our approach can be integrated into the workflow of state-of-the-art mapping design systems, and all its necessary inputs. Our approach relies on checking the entailment of verification statements derived directly from the schema mappings and from semantic annotations to the variables used in such mappings. We discuss how such verification statements can be produced and how such annotations can be extracted from different kinds of alignments of schemas into domain ontologies. Such alignments can be derived semi-automatically; thus, our framework might prove useful in also greatly reducing the amount of input from domain experts in the development of mappings.