Data freshness and data accuracy :a state of the art
Resumen:
In a context of Data Integration Systems (DIS) providing access to large amounts of data extracted and integrated from autonomous data sources, users are highly concerned about data quality. Traditionally, data quality is characterized via multiple quality factors. Among the quality dimensions that have been proposed in the literature, this report analyzes two main ones: data freshness and data accuracy. Concretely, we analyze the various definitions of both quality dimensions, their underlying metrics and the features of DIS that impact their evaluation. We present a taxonomy of existing works proposed for dealing with both quality dimensions in several kinds of DIS and we discuss open research problems.
2006 | |
Data freshness Data accuracy Data quality evaluation Data integration systems |
|
Universidad de la República | |
COLIBRI | |
http://hdl.handle.net/20.500.12008/3532 | |
Acceso abierto | |
Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-ND 4.0) |
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---|---|
author | Peralta Costabel, Veronika del Carmen |
author_facet | Peralta Costabel, Veronika del Carmen |
author_role | author |
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collection | COLIBRI |
dc.creator.none.fl_str_mv | Peralta Costabel, Veronika del Carmen |
dc.date.accessioned.none.fl_str_mv | 2014-12-02T16:07:39Z |
dc.date.available.none.fl_str_mv | 2014-12-02T16:07:39Z |
dc.date.issued.es.fl_str_mv | 2006 |
dc.date.submitted.es.fl_str_mv | 20141202 |
dc.description.abstract.none.fl_txt_mv | In a context of Data Integration Systems (DIS) providing access to large amounts of data extracted and integrated from autonomous data sources, users are highly concerned about data quality. Traditionally, data quality is characterized via multiple quality factors. Among the quality dimensions that have been proposed in the literature, this report analyzes two main ones: data freshness and data accuracy. Concretely, we analyze the various definitions of both quality dimensions, their underlying metrics and the features of DIS that impact their evaluation. We present a taxonomy of existing works proposed for dealing with both quality dimensions in several kinds of DIS and we discuss open research problems. |
dc.format.extent.es.fl_str_mv | 36 p. |
dc.format.mimetype.es.fl_str_mv | application/pdf |
dc.identifier.citation.es.fl_str_mv | PERALTA COSTABEL, V. "Data freshness and data accuracy : a state of the art". Reportes Técnicos 06-13. UR. FI – INCO, 2006. |
dc.identifier.issn.es.fl_str_mv | 0797-6410 |
dc.identifier.uri.none.fl_str_mv | http://hdl.handle.net/20.500.12008/3532 |
dc.language.iso.none.fl_str_mv | in |
dc.publisher.es.fl_str_mv | UR. FI – INCO. |
dc.relation.ispartof.es.fl_str_mv | Reportes Técnicos 06-13 |
dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-ND 4.0) |
dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
dc.subject.es.fl_str_mv | Data freshness Data accuracy Data quality evaluation Data integration systems |
dc.title.none.fl_str_mv | Data freshness and data accuracy :a state of the art |
dc.type.es.fl_str_mv | Reporte técnico |
dc.type.none.fl_str_mv | info:eu-repo/semantics/report |
dc.type.version.none.fl_str_mv | info:eu-repo/semantics/publishedVersion |
description | In a context of Data Integration Systems (DIS) providing access to large amounts of data extracted and integrated from autonomous data sources, users are highly concerned about data quality. Traditionally, data quality is characterized via multiple quality factors. Among the quality dimensions that have been proposed in the literature, this report analyzes two main ones: data freshness and data accuracy. Concretely, we analyze the various definitions of both quality dimensions, their underlying metrics and the features of DIS that impact their evaluation. We present a taxonomy of existing works proposed for dealing with both quality dimensions in several kinds of DIS and we discuss open research problems. |
eu_rights_str_mv | openAccess |
format | report |
id | COLIBRI_d1c641bb82f081aa16c99a2f6de4d330 |
identifier_str_mv | PERALTA COSTABEL, V. "Data freshness and data accuracy : a state of the art". Reportes Técnicos 06-13. UR. FI – INCO, 2006. 0797-6410 |
instacron_str | Universidad de la República |
institution | Universidad de la República |
instname_str | Universidad de la República |
language_invalid_str_mv | in |
network_acronym_str | COLIBRI |
network_name_str | COLIBRI |
oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/3532 |
publishDate | 2006 |
reponame_str | COLIBRI |
repository.mail.fl_str_mv | mabel.seroubian@seciu.edu.uy |
repository.name.fl_str_mv | COLIBRI - Universidad de la República |
repository_id_str | 4771 |
rights_invalid_str_mv | Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-ND 4.0) |
spelling | 2014-12-02T16:07:39Z2014-12-02T16:07:39Z200620141202PERALTA COSTABEL, V. "Data freshness and data accuracy : a state of the art". Reportes Técnicos 06-13. UR. FI – INCO, 2006.0797-6410http://hdl.handle.net/20.500.12008/3532In a context of Data Integration Systems (DIS) providing access to large amounts of data extracted and integrated from autonomous data sources, users are highly concerned about data quality. Traditionally, data quality is characterized via multiple quality factors. Among the quality dimensions that have been proposed in the literature, this report analyzes two main ones: data freshness and data accuracy. Concretely, we analyze the various definitions of both quality dimensions, their underlying metrics and the features of DIS that impact their evaluation. We present a taxonomy of existing works proposed for dealing with both quality dimensions in several kinds of DIS and we discuss open research problems.Made available in DSpace on 2014-12-02T16:07:39Z (GMT). No. of bitstreams: 5 TR0613.pdf: 577230 bytes, checksum: 4363be81deb28ba419588a47e23a8d8b (MD5) license_text: 21936 bytes, checksum: 9833653f73f7853880c94a6fead477b1 (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) license.txt: 4244 bytes, checksum: 528b6a3c8c7d0c6e28129d576e989607 (MD5) Previous issue date: 200636 p.application/pdfinUR. FI – INCO.Reportes Técnicos 06-13Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-ND 4.0)Data freshnessData accuracyData quality evaluationData integration systemsData freshness and data accuracy :a state of the artReporte técnicoinfo:eu-repo/semantics/reportinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaPeralta Costabel, Veronika del 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- Universidad de la Repúblicafalse |
spellingShingle | Data freshness and data accuracy :a state of the art Peralta Costabel, Veronika del Carmen Data freshness Data accuracy Data quality evaluation Data integration systems |
status_str | publishedVersion |
title | Data freshness and data accuracy :a state of the art |
title_full | Data freshness and data accuracy :a state of the art |
title_fullStr | Data freshness and data accuracy :a state of the art |
title_full_unstemmed | Data freshness and data accuracy :a state of the art |
title_short | Data freshness and data accuracy :a state of the art |
title_sort | Data freshness and data accuracy :a state of the art |
topic | Data freshness Data accuracy Data quality evaluation Data integration systems |
url | http://hdl.handle.net/20.500.12008/3532 |