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Introduction to Ontologies for Defense Business Analytics

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HCI in Business, Government and Organizations (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14038))

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Abstract

In recent years, ontologies have become the leading solution for capturing corporate knowledge. Stored explicitly in documentation or tacitly in the minds of Subject Matter Experts (SMEs), enterprise knowledge, in all its forms, can be optimized into a tangible representation that gives way to more advanced business analytics. This paper seeks to review the benefits and challenges of developing ontologies through the lens of the government defense sector. To further demonstrate the learning curve in adapting to ontologies and graph-based knowledge structures in general, this paper will also provide a use-case experiment where business Subject Matter Experts (SMEs) were trained to design an ontology of the Operating Materials and Supplies (OM&S) domain at Naval Information Warfare Center (NIWC) Pacific by-hand.

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Acknowledgements

The OM&S ontology presented in this paper, as well as many of the observed benefits and challenges that were documented, would not have been realized without the help and participation of NIWC Pacific’s OM&S team: Debra Ernst, Joshua Parrish, Kristie Wood, and Tyler Renfro. This paper would also like to acknowledge the help and support of NIWC Pacific scientist Andrew Kan.

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Authors and Affiliations

  1. Naval Information Warfare Center (NIWC) Pacific, San Diego, USA

    Bethany Taylor, Christianne Izumigawa & Jonathan Sato

Authors
  1. Bethany Taylor
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  2. Christianne Izumigawa
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  3. Jonathan Sato
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Corresponding author

Correspondence to Bethany Taylor .

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Editors and Affiliations

  1. City University of Hong Kong, Kowloon, Hong Kong

    Fiona Nah

  2. City University of Hong Kong, Kowloon, Hong Kong

    Keng Siau

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Taylor, B., Izumigawa, C., Sato, J. (2023). Introduction to Ontologies for Defense Business Analytics. In: Nah, F., Siau, K. (eds) HCI in Business, Government and Organizations. HCII 2023. Lecture Notes in Computer Science, vol 14038. Springer, Cham. https://doi.org/10.1007/978-3-031-35969-9_7

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  • DOI: https://doi.org/10.1007/978-3-031-35969-9_7

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-35969-9

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