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    A Real-time Linked Dataspace for the Internet of Things: Enabling "Pay-As-You-Go" Data Management in Smart Environments


    Curry, Edward and Derguech, Wassim and Hasan, Souleiman and Kouroupetroglou, Christos and ul Hassan, Umair (2019) A Real-time Linked Dataspace for the Internet of Things: Enabling "Pay-As-You-Go" Data Management in Smart Environments. Future Generation Computer Systems, 90. pp. 405-422. ISSN 0167-739X

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    Abstract

    As smart environments move from a research vision to concrete manifestations in real-world enabled by the Internet of Things, they are encountering a number of very practical challenges in data management in terms of the flexibility needed to bring together contextual and real-time data, the interface between new digital infrastructures and existing information systems, and how to easily share data between stakeholders in the environment. Therefore, data management approaches for smart environments need to support flexibility, dynamicity, incremental change, while keeping costs to a minimum. A Dataspace is an emerging approach to data management that has proved fruitful for personal information and scientific data management. However, their use within smart environments and for real-time data remains largely unexplored. This paper introduces a Real-time Linked Dataspace (RLD) as an enabling platform for data management within smart environments. This paper identifies common data management requirements for smart energy and water environments, details the RLD architecture and the key support services and their tiered support levels, and a principled approach to ‘‘Pay-As-You-Go’’ data management. The paper presents a dataspace query service for real-time data streams and entities to enable unified entity-centric queries across live and historical stream data. The RLD was validated in 5 real-world pilot smart environments following the OODA (Observe, Orient, Decide, and Act) Loop to build real-time analytics, decisions support, and smart apps for energy and water management. The pilots demonstrate that the RLD enables incremental pay-as-you-go data management with support services that simplify the development of applications and analytics for smart environments. Finally, the paper discusses experiences, lessons learnt, and future directions.

    Item Type: Article
    Keywords: Smart environments; Data management; Internet of Things; Water management; Energy management; Dataspace; Linked data; Semantic web; Event processing; Distributed systems;
    Academic Unit: Faculty of Social Sciences > School of Business
    Item ID: 11330
    Identification Number: https://doi.org/10.1016/j.future.2018.07.019
    Depositing User: Souleiman Hasan
    Date Deposited: 17 Oct 2019 13:15
    Journal or Publication Title: Future Generation Computer Systems
    Publisher: Elsevier
    Refereed: Yes
    URI:

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