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Auteur Luisa Griesbaum |
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A grounding-based ontology of data quality measures / Franz-Benjamin Mocnik in Journal of Spatial Information Science, JoSIS, n° 16 ([01/02/2018])
[article]
Titre : A grounding-based ontology of data quality measures Type de document : Article/Communication Auteurs : Franz-Benjamin Mocnik, Auteur ; Amin Mobasheri, Auteur ; Luisa Griesbaum, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 1 - 25 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] données localisées des bénévoles
[Termes IGN] mesure de la qualité
[Termes IGN] OpenStreetMap
[Termes IGN] qualité des donnéesRésumé : (auteur) Data quality and fitness for purpose can be assessed by data quality measures. Existing ontologies of data quality dimensions reflect, among others, which aspects of data quality are assessed and the mechanisms that lead to poor data quality. An understanding of which source of information is used to judge about data quality and fitness for purpose is, however, lacking. This article introduces an ontology of data quality measures by their grounding, that is, the source of information to which the data is compared to in order to assess their quality. The ontology is exemplified with several examples of volunteered geographic information (VGI), while also applying to other geographical data and data in general. An evaluation of the ontology in the context of data quality measures for OpenStreetMap (OSM) data, a well-known example of VGI, provides insights about which types of quality measures for OSM data have and which have not yet been considered in literature. Numéro de notice : A2018-683 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.5311/JOSIS.2018.16.36 En ligne : https://josis.org/index.php/josis/article/view/86 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98693
in Journal of Spatial Information Science, JoSIS > n° 16 [01/02/2018] . - pp 1 - 25[article]