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The financial industry business ontology: Best practice for big data

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  • Mike Bennett

Abstract

This article describes the Financial Industry Business Ontology (FIBO) as a set of formal models that define unambiguous shared meaning for financial industry concepts. An account is given of the history and development of the FIBO series of standards and the theoretical underpinnings of these as a business or ‘conceptual’ model. Some initial proof of concept work is described, demonstrating how in addition to the use of FIBO as a conceptual model, it is possible to derive semantic technology-based applications that may be used to carry out novel types of processing on data. The development roadmap of the FIBO series of standards within the Object Management Group is also described, so that readers can have an idea of what to expect from FIBO and when.

Suggested Citation

  • Mike Bennett, 2013. "The financial industry business ontology: Best practice for big data," Journal of Banking Regulation, Palgrave Macmillan, vol. 14(3-4), pages 255-268, July.
  • Handle: RePEc:pal:jbkreg:v:14:y:2013:i:3:p:255-268
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    Cited by:

    1. Bholat, David, 2016. "Modelling metadata in central banks," Statistics Paper Series 13, European Central Bank.
    2. Caterina Pietra & Roberto De Lotto & Rakan Bahshwan, 2021. "Approaching Healthy City Ontology: First-Level Classes Definition Using BFO," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    3. Maria V. Sigova & Igor K. Klyuchnikov & Oleg I. Klyuchnikov, 2024. "Sustainability and Security of Green Finance from the Multi-agent Games Perspective," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 78-95, February.
    4. Bell Raj Eapen & Vishwanath V. Baba & Maarif Sohail, 2023. "Evidence-Based Management: A Design Theory, Template, and Technology for a Knowledge Delivery Platform," Metamorphosis: A Journal of Management Research, , vol. 22(1), pages 73-84, June.
    5. Frizzo-Barker, Julie & Chow-White, Peter A. & Mozafari, Maryam & Ha, Dung, 2016. "An empirical study of the rise of big data in business scholarship," International Journal of Information Management, Elsevier, vol. 36(3), pages 403-413.
    6. Seddon, Jonathan J.J.M. & Currie, Wendy L., 2017. "A model for unpacking big data analytics in high-frequency trading," Journal of Business Research, Elsevier, vol. 70(C), pages 300-307.
    7. Shasha Liu & Bingjia Shao & Yuan Gao & Su Hu & Yi Li & Weigui Zhou, 2018. "Game theoretic approach of a novel decision policy for customers based on big data," Electronic Commerce Research, Springer, vol. 18(2), pages 225-240, June.

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