{'fraction_non_alphanumeric': 0.017727639000805803, 'fraction_numerical': 0.0016116035455278, 'mean_word_length': 5.46875, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Data Quality Improvement in Crowdsourcing Systems by Enabling A Positive Personal User Experience

A multiplicity of innovative applications has been developed based on the mobile crowdsourcing (MCS) paradigm. One group of applications addresses the creation of accessibility maps in large cities. In this context, a conceptual model of a system for the detection and the timely notification of the existence of temporary obstacles and other dangers in the urban environment is proposed in “Pervasive Crowd Mapping for Dynamic Environments”. This concept (PCM4DE) encompasses, among other technologies, the use of crowdsourcing. The system will be particularly useful to people with disabilities and elderly people. An exploratory literature review showed that data quality and the motivation strategies for participating in the systems based on MCS remain two of the key challenges to the effectiveness of those systems. This paper aims to contribute to the implementation of the PCM4DE concept by proposing the development of a mechanism that should improve the data quality through motivation forms which will enable a positive personal user experience, i.e., an experience which meets the participant's objectives, needs and preferences.