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However, data defects that are more dependent of data context knowledge challenge the data quality assessment since the process involves human supervision. Visualization systems belong to a class of supervised tools that can make visible data defect structures. Despite their considerable design knowledge encodings, there is little support design to visual quality assessment of data defects. Therefore, this work reports a case study that has explored which and how visualization properties facilitate visual detection of data defect. Its outcomes offer a first set of implications to design visualization system to permit data quality visual assessment.<\/jats:p>","DOI":"10.1177\/1473871616629516","type":"journal-article","created":{"date-parts":[[2016,3,14]],"date-time":"2016-03-14T22:03:55Z","timestamp":1457993035000},"page":"93-112","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":13,"title":["Visualization properties for data quality visual assessment: An exploratory case study"],"prefix":"10.1177","volume":"16","author":[{"given":"Jo\u00e3o Marcelo","family":"Borovina Josko","sequence":"first","affiliation":[{"name":"University of S\u00e3o Paulo, S\u00e3o Paulo, Brazil"}]},{"given":"Jo\u00e3o Eduardo","family":"Ferreira","sequence":"additional","affiliation":[{"name":"University of S\u00e3o Paulo, S\u00e3o Paulo, 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