Renato Freitas, C. Rocha, O. Braga, Gabriel Lopes, Odorico Monteiro, Mauro Oliveira
{"title":"Using Linked Data in the Data Integration for Maternal and Infant Death Risk of the SUS in the GISSA Project","authors":"Renato Freitas, C. Rocha, O. Braga, Gabriel Lopes, Odorico Monteiro, Mauro Oliveira","doi":"10.1145/3126858.3131606","DOIUrl":null,"url":null,"abstract":"Making good governance decisions is a constant challenge for Public Health administration. Health managers need to make data analysis in order to identify several health problems. In Brazil, these data are made available by DATASUS. Generally, they are stored in distinct and heterogeneous databases. TheLinked Data approach allow a homogenized view of the data as a unique basis. This article proposes a ontology-based model andLinked Data to integrate datasets and calculate the probability of maternal and infant death risk in order to give support in decision-making in the GISSA project.","PeriodicalId":338362,"journal":{"name":"Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3126858.3131606","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
Making good governance decisions is a constant challenge for Public Health administration. Health managers need to make data analysis in order to identify several health problems. In Brazil, these data are made available by DATASUS. Generally, they are stored in distinct and heterogeneous databases. TheLinked Data approach allow a homogenized view of the data as a unique basis. This article proposes a ontology-based model andLinked Data to integrate datasets and calculate the probability of maternal and infant death risk in order to give support in decision-making in the GISSA project.