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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