• English
  • Deutsch
  • Log In
    or
  • Research Outputs
  • Projects
  • Researchers
  • Institutes
  • Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Artikel
  4. Steering data quality with visual analytics: The complexity challenge
 
  • Details
  • Full
Options
2018
Journal Article
Titel

Steering data quality with visual analytics: The complexity challenge

Abstract
Data quality management, especially data cleansing, has been extensively studied for many years in the areas of data management and visual analytics. In the paper, we first review and explore the relevant work from the research areas of data management, visual analytics and human-computer interaction. Then for different types of data such as multimedia data, textual data, trajectory data, and graph data, we summarize the common methods for improving data quality by leveraging data cleansing techniques at different analysis stages. Based on a thorough analysis, we propose a general visual analytics framework for interactively cleansing data. Finally, the challenges and opportunities are analyzed and discussed in the context of data and humans.
Author(s)
Liu, S.
Andrienko, G.
Wu, Y.
Cao, N.
Jiang, L.
Shi, C.
Wang, Y.-S.
Hong, S.
Zeitschrift
Visual informatics
Thumbnail Image
DOI
10.1016/j.visinf.2018.12.001
Externer Link
Externer Link
Language
English
google-scholar
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Send Feedback
© 2022