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Using Linked Data in the Data Integration for Maternal and Infant Death Risk of the SUS in the GISSA Project

Published: 17 October 2017 Publication History

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.

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Cited By

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  • (2020)An RDF based approach for integrating data at different levels of abstractionProceedings of the Brazilian Symposium on Multimedia and the Web10.1145/3428658.3430981(81-88)Online publication date: 30-Nov-2020
  • (2020)Data from Multiple Web Sources: Crawling, Integrating, Preprocessing, and Designing ApplicationsSpecial Topics in Multimedia, IoT and Web Technologies10.1007/978-3-030-35102-1_8(213-242)Online publication date: 3-Mar-2020

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  1. Using Linked Data in the Data Integration for Maternal and Infant Death Risk of the SUS in the GISSA Project

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    cover image ACM Other conferences
    WebMedia '17: Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web
    October 2017
    522 pages
    ISBN:9781450350969
    DOI:10.1145/3126858
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    • SBC: Brazilian Computer Society
    • CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
    • CGIBR: Comite Gestor da Internet no Brazil
    • CAPES: Brazilian Higher Education Funding Council

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 17 October 2017

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    Author Tags

    1. linked data
    2. ontology
    3. public health system
    4. sus database

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    Webmedia '17
    Sponsor:
    • SBC
    • CNPq
    • CGIBR
    • CAPES
    Webmedia '17: Brazilian Symposium on Multimedia and the Web
    October 17 - 20, 2017
    RS, Gramado, Brazil

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    WebMedia '17 Paper Acceptance Rate 38 of 138 submissions, 28%;
    Overall Acceptance Rate 270 of 873 submissions, 31%

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    Cited By

    View all
    • (2020)An RDF based approach for integrating data at different levels of abstractionProceedings of the Brazilian Symposium on Multimedia and the Web10.1145/3428658.3430981(81-88)Online publication date: 30-Nov-2020
    • (2020)Data from Multiple Web Sources: Crawling, Integrating, Preprocessing, and Designing ApplicationsSpecial Topics in Multimedia, IoT and Web Technologies10.1007/978-3-030-35102-1_8(213-242)Online publication date: 3-Mar-2020

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