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DOOR: A data model for crowdsourcing with application to emergency response

: Cuong, To Tu; Mehta, Paras; Voisard, Agnès


Giaffreda, Raffaele (Ed.):
Internet of Things. IoT Infrastructures. First International Summit, IoT360 2014 : Rome, Italy, October 27-28, 2014, Revised Selected Papers, Part II
Cham: Springer International Publishing, 2015 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 151)
ISBN: 978-3-319-19742-5 (Print)
ISBN: 978-3-319-19743-2 (Online)
International Summit "Internet of Things" (IoT) <1, 2014, Rome>
Conference Paper
Fraunhofer FOKUS ()

Crowdsourcing allows us to employ collective human intelligence and resources in completing tasks in a wide variety of domains, such as mapping, translation, emergency response, and even fund raising. It first involves identification of a problem that can be solved using crowdsourcing and then its decomposition into tasks that workers can finish in a timely manner. Worker engagement analysis and data quality analysis are done afterwards. Such analysis activities are not supported by current platforms and are done in an ad-hoc fashion leading to duplicate efforts. As a first step towards realizing such analysis mechanisms, we propose a Data mOdel for crOwdsouRcing (DOOR), which is based on a fuzzy Entity-Relationship model in order to capture the uncertainty that is inherent in any crowdsourcing process. To illustrate its application, we have chosen the problem of collection of data about incidents for emergency response.