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Towards Interactive Visualization of Time Series Data to Support Knowledge Discovery

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F15%3A00083876" target="_blank" >RIV/00216224:14330/15:00083876 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-23485-4_57" target="_blank" >http://dx.doi.org/10.1007/978-3-319-23485-4_57</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-23485-4_57" target="_blank" >10.1007/978-3-319-23485-4_57</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Towards Interactive Visualization of Time Series Data to Support Knowledge Discovery

  • Original language description

    Higher education institutions have a significant interest in increasing the educational quality and effectiveness. A major challenge in modern education is the large amount of time-dependent data, which requires efficient tools and methods to provide efficient decision making. Methods like motion charts (MC) show changes over time by presenting animations in two-dimensional space and by changing element appearances. In this paper, we present a visual analytics tool which makes use of enhanced animated data visualization methods. The tool is primarily designed for exploratory analysis of academic analytics (AA) and offers several interactive visualization methods that enhance the MC design. AA is the business intelligence term used in academic settingsand particularly facilitates creation of actionable intelligence to enhance learning and improve student retention.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Progress in Artificial Intelligence - 17th Portuguese Conference on Artificial Inteligence - EPIA 2015

  • ISBN

    9783319234847

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    578-583

  • Publisher name

    Springer International Publishing

  • Place of publication

    Portugal

  • Event location

    Coimbra, Portugal

  • Event date

    Jan 1, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article