V. Martins, J. Costa, Rafael Timóteo de Sousa Júnior
{"title":"Architecture of a Collaborative Business Intelligence Environment based on an Ontology Repository and Distributed Data Services","authors":"V. Martins, J. Costa, Rafael Timóteo de Sousa Júnior","doi":"10.5220/0004107000990106","DOIUrl":null,"url":null,"abstract":"Business Intelligence (BI) refers to a set of methodologies, methods, tools and software that are used in order to provide system solutions to support information analysis. The specifications and development of these system solutions are still limited to specific domain tables. Furthermore, in conventional BI solutions, it is necessary to promote massive data loads provided by other organizations in local repositories. Such massive loads can make the information not available on-time or cause errors due to misinterpreting received data. In this paper, we propose a systemic architecture that seeks solutions to these limitations. The architecture is based on a centralized ontology repository and uses distributed data services to provide data to generic analytical queries.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0004107000990106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Business Intelligence (BI) refers to a set of methodologies, methods, tools and software that are used in order to provide system solutions to support information analysis. The specifications and development of these system solutions are still limited to specific domain tables. Furthermore, in conventional BI solutions, it is necessary to promote massive data loads provided by other organizations in local repositories. Such massive loads can make the information not available on-time or cause errors due to misinterpreting received data. In this paper, we propose a systemic architecture that seeks solutions to these limitations. The architecture is based on a centralized ontology repository and uses distributed data services to provide data to generic analytical queries.
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