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A Weighted Knowledge Graph for Representing the Results of a Systematic Literature Review

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Advanced Information Systems Engineering Workshops (CAiSE 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 482))

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Abstract

In information systems engineering, one of the most important success factors is understanding the latest scientific research on the use of IT solutions in the enterprise's field of activity. For this purpose, systemic literature reviews are often used to identify the most important concepts and their relationships in a respective domain. This paper illustrates how a knowledge graph can help to visualize and analyze the results of a systemic literature review. A simplified weighted knowledge graph, in which weights are assigned to its nodes, is constructed using the results of a systematic literature review on the application of the agile approach to the development of information systems in the public sector. The graph reflects and, also, helps to analyze the collected information on the state of the art of agile information systems engineering in public organizations.

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Authors and Affiliations

  1. Department of Artificial Intelligence and Systems Engineering, Riga Technical University, Kipsalas iela 6A, Riga, 1048, Latvia

    Jolanta Graudone & Marite Kirikova

Authors
  1. Jolanta Graudone
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  2. Marite Kirikova
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Correspondence to Jolanta Graudone .

Editor information

Editors and Affiliations

  1. Zurich University of Applied Sciences, Winterthur, Switzerland

    Marcela Ruiz

  2. University of Haifa, Haifa, Israel

    Pnina Soffer

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Graudone, J., Kirikova, M. (2023). A Weighted Knowledge Graph for Representing the Results of a Systematic Literature Review. In: Ruiz, M., Soffer, P. (eds) Advanced Information Systems Engineering Workshops. CAiSE 2023. Lecture Notes in Business Information Processing, vol 482. Springer, Cham. https://doi.org/10.1007/978-3-031-34985-0_13

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  • DOI: https://doi.org/10.1007/978-3-031-34985-0_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34984-3

  • Online ISBN: 978-3-031-34985-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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