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2015 Volume 30
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RESEARCH ARTICLE   Open Access    

Self-organising management of user-generated data and knowledge

  • Intelligent Systems and Networks Group

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  • Abstract: The proliferation of sensor networks, mobile and pervasive computing has provided the technological push for a new class of participatory-sensing applications, based on sensing and aggregating user-generated content, and transforming it into knowledge. However, given the power and value of both the raw data and the derived knowledge, to ensure that the generators are commensurate beneficiaries, we advocate an open approach to the data and intellectual property rights by treating user-generated content, as well as derived information and knowledge, as a common-pool resource. In this paper, we undertake an extensive review of experimental, commercial and social participatory sensory applications, from which we identify that a decentralised, community-oriented governance model is required to support this approach. Furthermore, we show that Ostrom’s institutional analysis and development framework, in conjunction with a framework for self-organising electronic institutions, can be used to give both an architecture and algorithmic base for the requisite governance model, in terms of operational and collective-choice rules specified in computational logic. This provides, we believe, the foundations for engineering knowledge commons for the next generation of participatory-sensing applications, in which the data generators are also the primary beneficiaries.
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  • Cite this article

    Sam Macbeth, Jeremy V. Pitt. 2015. Self-organising management of user-generated data and knowledge. The Knowledge Engineering Review 30(3)237−264, doi: 10.1017/S026988891400023X
    Sam Macbeth, Jeremy V. Pitt. 2015. Self-organising management of user-generated data and knowledge. The Knowledge Engineering Review 30(3)237−264, doi: 10.1017/S026988891400023X
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RESEARCH ARTICLE   Open Access    

Self-organising management of user-generated data and knowledge

  • Intelligent Systems and Networks Group

  • Published online: 19 November 2014
The Knowledge Engineering Review  30,  2015, 30(3): 237−264  |  Cite this article

Abstract: Abstract: The proliferation of sensor networks, mobile and pervasive computing has provided the technological push for a new class of participatory-sensing applications, based on sensing and aggregating user-generated content, and transforming it into knowledge. However, given the power and value of both the raw data and the derived knowledge, to ensure that the generators are commensurate beneficiaries, we advocate an open approach to the data and intellectual property rights by treating user-generated content, as well as derived information and knowledge, as a common-pool resource. In this paper, we undertake an extensive review of experimental, commercial and social participatory sensory applications, from which we identify that a decentralised, community-oriented governance model is required to support this approach. Furthermore, we show that Ostrom’s institutional analysis and development framework, in conjunction with a framework for self-organising electronic institutions, can be used to give both an architecture and algorithmic base for the requisite governance model, in terms of operational and collective-choice rules specified in computational logic. This provides, we believe, the foundations for engineering knowledge commons for the next generation of participatory-sensing applications, in which the data generators are also the primary beneficiaries.

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    • The first author is supported by EPSRC Studentship Grant No. EP/P505550/1.

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    Cite this article
    Sam Macbeth, Jeremy V. Pitt. 2015. Self-organising management of user-generated data and knowledge. The Knowledge Engineering Review 30(3)237−264, doi: 10.1017/S026988891400023X
    Sam Macbeth, Jeremy V. Pitt. 2015. Self-organising management of user-generated data and knowledge. The Knowledge Engineering Review 30(3)237−264, doi: 10.1017/S026988891400023X
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