New tool for visualization of time series and anomalies in streaming data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00236681" target="_blank" >RIV/68407700:21230/16:00236681 - isvavai.cz</a>
Result on the web
<a href="https://www.researchgate.net/publication/291774971_NEW_TOOL_FOR_VISUALIZATION_OF_TIME-SERIES_AND_ANOMALIES_IN_STREAMING_DATA_-_short_version" target="_blank" >https://www.researchgate.net/publication/291774971_NEW_TOOL_FOR_VISUALIZATION_OF_TIME-SERIES_AND_ANOMALIES_IN_STREAMING_DATA_-_short_version</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.11118/actaun201664041353" target="_blank" >10.11118/actaun201664041353</a>
Alternative languages
Result language
angličtina
Original language name
New tool for visualization of time series and anomalies in streaming data
Original language description
Presented is a new visualization module which is available as an open source solution and features some novel combination of capabilities. The focus is on its lightweight, interactive & intuitive use and ease of deployment – including a setup for a live monitoring system with anomaly detection and highlighting abilities. This study describes the design and development process of our new tool for visualization of time-series data with focus on anomaly detection and streaming data. We frame the examples and motivation from our research activities, which include design and evaluation of neural network models, systems for continuous monitoring and anomaly detection (for example in IT or medical domains), and from usage in signal analysis applications. The most important aspects of the proposed visualization tool are ease of availability, interactive graph support, live monitoring and a possibility to highlight anomalies. The software is published at https://github.com/nupic-community/nupic.visualizations (OTAHAL, M., FOHL, J., 2015); there is also available an extended version of the article with more details and figures (OTAHAL, M., STEPANKOVA, O., 2015).
Czech name
—
Czech description
—
Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JC - Computer hardware and software
OECD FORD branch
—
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
ISSN
1211-8516
e-ISSN
—
Volume of the periodical
2016
Issue of the periodical within the volume
64
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
12
Pages from-to
1353-1364
UT code for WoS article
—
EID of the result in the Scopus database
2-s2.0-84990891747