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dc.contributor.authorHernández, José L.
dc.contributor.authorQuijano, Ana
dc.contributor.authorGarcía, Rubén
dc.contributor.authorNouaille, Pierre
dc.contributor.authorRisch, Lukas
dc.contributor.authorVirtanen, Mikko
dc.contributor.authorMiguel Jiménez, Ignacio de 
dc.date.accessioned2023-10-26T10:42:49Z
dc.date.available2023-10-26T10:42:49Z
dc.date.issued2022
dc.identifier.citationProceedings of the 11th International Conference on Data Science, Technology and Applications - DATA, Lisbon, Portugal, 2022, SciTePress, pp. 353-360
dc.identifier.isbn978-989-758-583-8
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/62373
dc.descriptionProducción Científicaes
dc.description.abstractThe Smart Cities concept is supported by the use of Information and Communication Technologies (ICT), which enables the digitalisation of the city assets. Then, cities are nowadays driven by data, with a clear dependency on the data collection approaches. Decisions and criteria for urban transformation therefore rely on data and Key Performance Indicators. However, one question remains and refers the reliability and credibility of data that guide the decision-making processes. Many efforts are made in the definition of the data quality methodologies, but not in analysing the real situation about data collection is smart cities. This paper applies a methodology to quantitatively analyse the real quality of the data-sets in the cities of Nantes, Hamburg and Helsinki. This work is under the umbrella of mySMARTLife project (GA #731297). The main conclusion or lessons learnt is the need for more appropriate methods to increase data quality, instead of defining new methodologies. Data qual ity requires improvements to make better informed decisions and obtain more credible Key Performance Indicators.es
dc.format.extent8 p.
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherSciTePress
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationInformation Quality
dc.subject.classificationSmart Cities and Urban Data Analytics
dc.titleAnalysis of Data Quality in Digital Smart Cities: The Cases of Nantes, Hamburg and Helsinkies
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.identifier.doi10.5220/0011271900003269
dc.relation.publisherversionhttps://doi.org/10.5220/0011271900003269
dc.title.eventProceedings of the 11th International Conference on Data Science, Technology and Applications - DATAes
dc.description.projectEU H2020 programme (GA #731297)
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones


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