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Using Conceptual Structures in Enterprise Architecture to Develop a New Way of Thinking and Working for Organisations

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10872)


Enterprise Architecture (EA) is a discipline that provides generic patterns that any organisation can reuse throughout its own business, informatics and technical components. However, EA’s current way of thinking and working to achieve this aim is not standardised. EA thus continues to “reinvent the wheel” that causes mistakes or wastes resources on rediscovering what should already be known. We, therefore, represent the specific business, information and technology meta-models as patterns that can be fully reintegrated in one repeatable meta-model for the whole organisation. The outcome is a new agile way of thinking and working, highlighted by how EA works better in enterprise layers, sub-layers and levels of abstraction. To test the meta-models, two forms of Conceptual Structures known as Conceptual Graphs (CGs) and Formal Concept Analysis (FCA) are brought together through the CGtoFCA algorithm. The algorithm identifies how the layered meta-models can share meaning and truth and without having to recombine them into one large, unwieldy meta-model as the repeatable structure.

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  1. 1.

    The table has the layers in columns not rows, and the levels in rows not columns. This layout allows the table to best fit on the page; it should be the other way round.

  2. 2.

    The CGs are drawn in CharGer ( as it has support for the CGIF (CG Interchange Format) in ISO/IEC 24707 Common Logic. The CGIF is passed through CGtoFCA then visualised as an FCL in FCA Concept Explorer (


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Correspondence to Simon Polovina .

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Polovina, S., von Rosing, M. (2018). Using Conceptual Structures in Enterprise Architecture to Develop a New Way of Thinking and Working for Organisations. In: Chapman, P., Endres, D., Pernelle, N. (eds) Graph-Based Representation and Reasoning. ICCS 2018. Lecture Notes in Computer Science(), vol 10872. Springer, Cham.

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  • Print ISBN: 978-3-319-91378-0

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