Doina Caragea, Jie Bao, Jyotishman Pathak, Adrian Silvescu, Carson Andorf, Drena Dobbs, Vasant Honavar
{"title":"Information Integration from Semantically Heterogeneous Biological Data Sources.","authors":"Doina Caragea, Jie Bao, Jyotishman Pathak, Adrian Silvescu, Carson Andorf, Drena Dobbs, Vasant Honavar","doi":"10.1109/DEXA.2005.118","DOIUrl":null,"url":null,"abstract":"<p><p>We present the first prototype of INDUS (Intelligent Data Understanding System), a federated, query-centric system for information integration and knowledge acquisition from distributed, semantically heterogeneous data sources that can be viewed (conceptually) as tables. INDUS employs ontologies and inter-ontology mappings, to enable a user to view a collection of such data sources (regardless of location, internal structure and query interfaces) as though they were a collection of tables structured according to an ontology supplied by the user. This allows INDUS to answer user queries against distributed, semantically heterogeneous data sources without the need for a centralized data warehouse or a common global ontology.</p>","PeriodicalId":88909,"journal":{"name":"International Workshop on Databases and Expert Systems Applications : proceedings","volume":"2005 ","pages":"580-584"},"PeriodicalIF":0.0000,"publicationDate":"2005-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/DEXA.2005.118","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Databases and Expert Systems Applications : proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEXA.2005.118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
We present the first prototype of INDUS (Intelligent Data Understanding System), a federated, query-centric system for information integration and knowledge acquisition from distributed, semantically heterogeneous data sources that can be viewed (conceptually) as tables. INDUS employs ontologies and inter-ontology mappings, to enable a user to view a collection of such data sources (regardless of location, internal structure and query interfaces) as though they were a collection of tables structured according to an ontology supplied by the user. This allows INDUS to answer user queries against distributed, semantically heterogeneous data sources without the need for a centralized data warehouse or a common global ontology.