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A comprehensive reputation assessment framework for volunteered geographic information in crowdsensing applications

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Abstract

Volunteered geographic information (VGI) is the result of activities where individuals, supported by enabling technologies, behave like physical sensors by harvesting and organizing georeferenced content, usually in their surroundings. Both researchers and organizations have recognized the value of VGI content, however this content is typically heterogeneous in quality and spatial coverage. As a consequence, in order for applications to benefit from it, its quality and reliability need to be assessed in advance. This may not be easy since, typically, it is unknown how the process of collecting and organizing the VGI content has been conducted and by whom. In the literature, various proposals focus on an indirect process of quality assessment based on reputation scores. Following this perspective, the present paper provides as main contributions: (i) a multi-layer architecture for VGI which supports a process of reputation evaluation; (ii) a new comprehensive model for computing reputation scores for both VGI data and contributors, based on direct and indirect evaluations expressed by users, and including the concept of data aging; (iii) a variety of experiments evaluating the accuracy of the model. Finally, the relevance of adopting this framework is discussed via an applicative scenario for recommending tourist itineraries.

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Notes

  1. https://get.google.com/trips/

  2. Hereafter, we use the term reputation score, or simply score, in an interchangeable way to denote either the concept or its value, based on the context.

  3. The features in user profile can also be analyzed by machine learning techniques in order to detect fake profiles or even multiple registrations of the same user, as proposed in Xiao et al. [21]. Then, fake profiles can be disabled or submitted to human checking.

  4. https://www.mathworks.com/products/matlab.html

  5. https://www.quora.com/What-percentage-of-buyers-write-reviews-on-Amazon

  6. Rise of the citizen scientist, http://www.nature.com/news/rise-of-the-citizen-scientist-1.18192

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Acknowledgements

The Authors are thanking the colleague Prof. Gianfranco Lamperti for his very valuable help in supporting the work described in this paper, and the former student Eng. Marco Gusmini for developing the first prototypes of the proposed solution.

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Authors and Affiliations

  1. German University of Technology in Oman (GUtech), Athaibah, Oman

    Nafaâ Jabeur

  2. Department of Information Engineering, Università degli Studi di Brescia, Brescia, Italy

    Roula Karam & Michele Melchiori

  3. ISTI, CNR, Pisa, Italy

    Chiara Renso

Authors
  1. Nafaâ Jabeur
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  2. Roula Karam
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  3. Michele Melchiori
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  4. Chiara Renso
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Correspondence to Michele Melchiori.

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Jabeur, N., Karam, R., Melchiori, M. et al. A comprehensive reputation assessment framework for volunteered geographic information in crowdsensing applications. Pers Ubiquit Comput 23, 669–685 (2019). https://doi.org/10.1007/s00779-018-1122-9

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