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Auteur Jianzheng Liu |
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Rethinking big data: A review on the data quality and usage issues / Jianzheng Liu in ISPRS Journal of photogrammetry and remote sensing, vol 115 (May 2016)
[article]
Titre : Rethinking big data: A review on the data quality and usage issues Type de document : Article/Communication Auteurs : Jianzheng Liu, Auteur ; Jie Li, Auteur ; Weifeng Li, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 134 – 142 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] données massives
[Termes IGN] évaluation des données
[Termes IGN] qualité des données
[Termes IGN] traitement de données localiséesRésumé : (auteur) The recent explosive publications of big data studies have well documented the rise of big data and its ongoing prevalence. Different types of “big data” have emerged and have greatly enriched spatial information sciences and related fields in terms of breadth and granularity. Studies that were difficult to conduct in the past time due to data availability can now be carried out. However, big data brings lots of “big errors” in data quality and data usage, which cannot be used as a substitute for sound research design and solid theories. We indicated and summarized the problems faced by current big data studies with regard to data collection, processing and analysis: inauthentic data collection, information incompleteness and noise of big data, unrepresentativeness, consistency and reliability, and ethical issues. Cases of empirical studies are provided as evidences for each problem. We propose that big data research should closely follow good scientific practice to provide reliable and scientific “stories”, as well as explore and develop techniques and methods to mitigate or rectify those ‘big-errors’ brought by big data. Numéro de notice : A2016-548 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.11.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.11.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81702
in ISPRS Journal of photogrammetry and remote sensing > vol 115 (May 2016) . - pp 134 – 142[article]