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A Data Quality Model and an Evaluation Method for Health Data in Ecuador

  • Departamento de Ciencias de la Computacion Universidad de Cuenca

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Data represents an organization's most important asset; hence, data engineers must ensure that its storage and processing methods comply with quality specifications that ensure its accuracy, confidentiality, and other quality attributes that allow it to be used fully. Although there are many software quality models, they are disjointed from the quality of the data being handled. Likewise, there is a lot of talk about the quality of information, but only some contributions align with a formal standard and regulations. Consequently, this article presents a data quality model aligned with ISO 25012 and Ecuador's personal data protection law to serve as a tool for establishing dataset quality. Finally, using the quality model is exemplified through an evaluation process aligned with ISO 25040.

Original languageEnglish
Title of host publicationETCM 2024 - 8th Ecuador Technical Chapters Meeting
EditorsDavid Rivas-Lalaleo, Soraya Lucia Sinche Maita
Place of PublicationCuenca, Ecuador
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)979-8350391589
ISBN (Print)979-8-3503-9159-6
DOIs
StatePublished - 2024
Event8th IEEE Ecuador Technical Chapters Meeting, ETCM 2024 - Cuenca, Ecuador
Duration: 15 Oct 202418 Oct 2024

Conference

Conference8th IEEE Ecuador Technical Chapters Meeting, ETCM 2024
Country/TerritoryEcuador
CityCuenca
Period15/10/2418/10/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • law regulation
  • personal data protection

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