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An ontology to assess data quality domains. A case study applied to a health care entity
| dc.contributor.author | Urrutia-Sepúlveda, Angélica | |
| dc.contributor.author | Chavez, Emma | |
| dc.contributor.author | Motz, Regina | |
| dc.date.accessioned | 2017-10-16T13:05:46Z | |
| dc.date.available | 2017-10-16T13:05:46Z | |
| dc.date.issued | 2017 | |
| dc.identifier.uri | http://repositorio.ucm.cl/handle/ucm/559 | |
| dc.description.abstract | Data integration can extend scenarios in applications designed to fulfill the requirements of decision support systems. However, a critical aspect in database development is to determine the quality of the data sources. Thus, it is important to have an automatic mechanism to be able to measure the quality of the data source, where the level of quality depends on the amount of data with technical anomalies that exist in the upgrade process. This article aims to define a flexible process to asses data quality, which does not depend of the application domain, and has a declarative specification based on the use of domain ontologies and data quality metrics. As a prove of concepts a description of the use of the ontology and the possible metrics to use are proposed in a case study that applies to the health care domain. For the case a Semantic Web Rule Language (SWRL) was used. | es_CL |
| dc.language.iso | en | es_CL |
| dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Chile | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | * |
| dc.source | IEEE Latin America Transactions, 15(8), 1506-1512 | es_CL |
| dc.subject | Data quality | es_CL |
| dc.subject | Health informatics | es_CL |
| dc.subject | Ontologies | es_CL |
| dc.subject | Quality metrics | es_CL |
| dc.title | An ontology to assess data quality domains. A case study applied to a health care entity | es_CL |
| dc.type | Article | es_CL |
| dc.ucm.facultad | Facultad de Ciencias de la Ingeniería | es_CL |
| dc.ucm.indexacion | Scopus | es_CL |
| dc.ucm.indexacion | Isi | es_CL |
| dc.ucm.uri | ieeexplore.ieee.org/document/7994799/ | es_CL |
| dc.ucm.doi | doi.org/10.1109/TLA.2017.7994799 | es_CL |
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