A QoI Assessment Framework for Participatory Crowdsourcing Systems Ashley Rajoo, Kavi Kumar Khedo, and Utam Avinash Einstein Mungur Abstract Participatory Crowdsourcing Systems have the potential to improve services in our daily life, such as health care, transportation and to monitor even the urban landscape using participatory sensing strategies. Data are the core mechanism that enables Participatory Crowdsourcing Systems to operate. It is very important to understand the evolution and relevance of data in Participatory Crowdsourcing Systems. Thus, this paper proposes a Quality of Information assessment framework which all Participatory Crowdsourcing Systems should strive to achieve to ensure data quality. The framework operates in a matrix schema that consists of four indepen- dent classes (horizontally) and has various dimensions within each class (vertically). The proposed framework will be flexible as it can incorporate new quality classes in the case of emerging technologies or domain areas. On the other hand, the vertical layer will have two subsections namely mandatory and desired features contained within a class. Keywords Wireless systems · Participatory crowdsourcing systems · Quality of information 1 Introduction A Participatory Crowdsourcing System (PCS) is characterized by a platform that links participant’s mobile phones to a cloud service where data are collected and analyzed. In a PCS, data should be captured in real-time and the system should be able to define the relevance of the data collected for processing. This is so because the data collected within a PCS attempt to improve a domain area such as environmental, people or even task-oriented. Thus, there is a need to understand the Quality of Information (QoI) in a PCS which will define the relevance of data captured. Users often capture data while they are not connected to the crowdsourcing platform and, once connected, the data are sent to the cloud system. Therefore, timeliness and validity of the data A. Rajoo (B ) · K. K. Khedo · U. A. E. Mungur Faculty of Information, Communication and Digital Technologies, University of Mauritius, Reduit, Mauritius e-mail: ashleyrajoo10@yahoo.com © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 C. R. Panigrahi et al. (eds.), Progress in Advanced Computing and Intelligent Engineering, Advances in Intelligent Systems and Computing 1299, https://doi.org/10.1007/978-981-33-4299-6_29 351