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July 21, 2023
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Applications of Knowledge Graphs in Telecommunication Systems Management

Publicated to:Ieee Internet Computing. 27 (3): 29-34 - 2023-06-01 27(3), DOI: 10.1109/MIC.2023.3253305

Authors: Mier, FJZ; Iglesias, CA

Affiliations

Telefon IoT & Big Data Tech, Technol & Integrat, Madrid 28050, Spain - Author
Telefónica - Author
Univ Politecn Madrid, Madrid 28040, Spain - Author
Universidad Politécnica de Madrid - Author

Abstract

Telecommunications systems management represents a technical challenge with profound economic implications. Many different sources of information must be integrated, and complex decisions must be automatically taken and executed. In this article, we review the usage of knowledge graphs in this domain since they are a powerful tool for dealing with data integration and complex knowledge representation. The main insights are that they have been applied in several areas of telecommunications management, such as resource/service discovery and monitoring, with a particular focus on software-defined networks. Their main advantages are their extensibility and interoperability. However, data quality and graph performance are still challenges, and work is yet to be done for its application to the rest of the telecommunication management areas.

Keywords

automationcloud computingdata modelsdecision makingknowledge graphsmonitoringsystems engineering and theorytelecommunication network managementOntologies

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Ieee Internet Computing due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2023, it was in position 29/132, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Software Engineering.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 1.83, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-10, the following number of citations:

  • Scopus: 2
  • Google Scholar: 4

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-10:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 6 (PlumX).