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Applying the Ecological Interface Design Framework to a Proactively Controlled Network Routing System

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Advances in Artificial Intelligence, Software and Systems Engineering (AHFE 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 965))

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Abstract

The focus system of this study is the proactively controlled signal routing system used by BBC News Division to broadcast content around its global network. The Work Domain Analysis and Decision Ladder Analysis both associated with the Ecological Interface Design (EID) approach will be used to analyze the system. [7] states the EID approach can improve performance in a variety of domains based on the novel information requirements it uncovers, however we propose that certain alterations to how EID approaches proactively controlled systems would be beneficial. Specifically, when we conducted a work domain analysis, we focused on the object level of the model that specifies that system objects are normally arranged spatially on a display to reflect the actual layout of a system. We feel that explicit reconceptualization of how the objects are arranged is necessary when approaching proactively controlled displays. Specifically, we propose an addition in the form of a temporal arrangement of objects to the current guidelines for the spatial arrangement of objects. The reason for this is so that the trend-based element can be more explicitly stated in the work domain model. We also conducted a Decision Ladder analysis where the system state node of the framework which included the technical specification as well as time orientated usage profiles of resources. The analyses inform subsequent design of a time tunnel visualization to support proactive control of the BBC Broadcast Signal Routing System.

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References

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Correspondence to Alexandros Eftychiou .

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Eftychiou, A. (2020). Applying the Ecological Interface Design Framework to a Proactively Controlled Network Routing System. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2019. Advances in Intelligent Systems and Computing, vol 965. Springer, Cham. https://doi.org/10.1007/978-3-030-20454-9_39

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  • DOI: https://doi.org/10.1007/978-3-030-20454-9_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20453-2

  • Online ISBN: 978-3-030-20454-9

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