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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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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
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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
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