2026-04-14T14:38:14Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/623732023-10-27T10:14:01Zcom_10324_1191com_10324_931com_10324_894col_10324_1381

Hernández, José L. Quijano, Ana García, Rubén Nouaille, Pierre Risch, Lukas Virtanen, Mikko Miguel Jiménez, Ignacio de 2023-10-26T10:42:49Z 2023-10-26T10:42:49Z 2022 Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA, Lisbon, Portugal, 2022, SciTePress, pp. 353-360 978-989-758-583-8 https://uvadoc.uva.es/handle/10324/62373 10.5220/0011271900003269 Producción Científica The 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. EU H2020 programme (GA #731297) 8 p. application/pdf eng SciTePress info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional Information Quality Smart Cities and Urban Data Analytics Analysis of Data Quality in Digital Smart Cities: The Cases of Nantes, Hamburg and Helsinki Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/acceptedVersion https://doi.org/10.5220/0011271900003269