{"title":"基于本体的数据集成框架","authors":"Li Dong, Huang Linpeng","doi":"10.1109/ICICSE.2008.96","DOIUrl":null,"url":null,"abstract":"This paper presents an ontology-based data integration framework that is capable of deriving an ontology from a collection of XML schemas in a semiautomatic manner and integrating heterogeneous XML sources at the semantic level. The ontology in our system is constructed following a layered approach where an intermediate model is introduced to explicate the underlying semantics of XML schemas and to reduce the complexity of ontology derivation. This two-phase approach is performed semi-automatically by applying a set of heuristic rules and by interpreting mapping information defined by users. The resulting ontology serves as a global semantic view over a set of data sources to be integrated. Moreover, we also adopt a data warehousing approach to populate this ontology with data from XML instance documents automatically. The proposed framework has been implemented and evaluated using off the-Web XML schemas.","PeriodicalId":333889,"journal":{"name":"2008 International Conference on Internet Computing in Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"A Framework for Ontology-Based Data Integration\",\"authors\":\"Li Dong, Huang Linpeng\",\"doi\":\"10.1109/ICICSE.2008.96\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an ontology-based data integration framework that is capable of deriving an ontology from a collection of XML schemas in a semiautomatic manner and integrating heterogeneous XML sources at the semantic level. The ontology in our system is constructed following a layered approach where an intermediate model is introduced to explicate the underlying semantics of XML schemas and to reduce the complexity of ontology derivation. This two-phase approach is performed semi-automatically by applying a set of heuristic rules and by interpreting mapping information defined by users. The resulting ontology serves as a global semantic view over a set of data sources to be integrated. Moreover, we also adopt a data warehousing approach to populate this ontology with data from XML instance documents automatically. The proposed framework has been implemented and evaluated using off the-Web XML schemas.\",\"PeriodicalId\":333889,\"journal\":{\"name\":\"2008 International Conference on Internet Computing in Science and Engineering\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-01-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Internet Computing in Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICSE.2008.96\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Internet Computing in Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICSE.2008.96","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents an ontology-based data integration framework that is capable of deriving an ontology from a collection of XML schemas in a semiautomatic manner and integrating heterogeneous XML sources at the semantic level. The ontology in our system is constructed following a layered approach where an intermediate model is introduced to explicate the underlying semantics of XML schemas and to reduce the complexity of ontology derivation. This two-phase approach is performed semi-automatically by applying a set of heuristic rules and by interpreting mapping information defined by users. The resulting ontology serves as a global semantic view over a set of data sources to be integrated. Moreover, we also adopt a data warehousing approach to populate this ontology with data from XML instance documents automatically. The proposed framework has been implemented and evaluated using off the-Web XML schemas.