• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. A Knowledge Graph for Query-Induced Analyses of Hierarchically Structured Time Series Information
 
  • Details
  • Full
Options
2023
Conference Paper
Title

A Knowledge Graph for Query-Induced Analyses of Hierarchically Structured Time Series Information

Abstract
This paper introduces the concept of a knowledge graph for time series data, which allows for a structured management and propagation of characteristic time series information and the ability to support query-driven data analyses. We gradually link and enrich knowledge obtained by domain experts or previously performed analyses by representing globally and locally occurring time series insights as individual graph nodes. Supported by a utilization of techniques from automated knowledge discovery and machine learning, a recursive integration of analytical query results is exploited to generate a spectral representation of linked and successively condensed information. Besides a time series to graph mapping, we provide an ontology describing a classification of maintained knowledge and affiliated analysis methods for knowledge generation. After a discussion on gradual knowledge enrichment, we finally illustrate the concept of knowledge propagation based on an application of state-of-the-art methods for time series analysis.
Author(s)
Graß, Alexander  
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Beecks, Christian  
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Chala, Sisay Adugna
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Lange-Bever, Christoph  orcid-logo
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Decker, Stefan  
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Mainwork
New Trends in Database and Information Systems. ADBIS 2023 Short Papers, Doctoral Consortium and Workshops. Proceedings  
Conference
European Conference on Advances in Databases and Information Systems 2023  
DOI
10.1007/978-3-031-42941-5_16
Language
English
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Keyword(s)
  • Exploratory Data Analysis

  • Knowledge Discovery

  • Knowledge Graph

  • Machine Learning

  • Time Series

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024